From 3a633b01576a826ee1f54753e1f7f768fa071400 Mon Sep 17 00:00:00 2001 From: disconcision Date: Thu, 3 Oct 2024 18:42:00 -0400 Subject: [PATCH] dev merge into haz3l-modules, not compiling --- .gitattributes | 13 + .github/workflows/deploy_branches.yml | 72 +- .gitignore | 3 + INSTALL.md | 6 +- Makefile | 19 +- README.md | 17 +- docs/Change-OCaml-Dependencies.md | 12 + docs/Updating-OCaml-Version.md | 21 +- docs/hazel-architecture-july-2024.png | Bin 0 -> 403192 bytes docs/hazel-architecture-july-2024.tldr | 1 + docs/hazel-palette-august-2024.png | Bin 0 -> 212730 bytes docs/hazel-syntax-data-types.png | Bin 0 -> 97031 bytes dune-project | 43 +- dune-workspace | 9 + hazel.opam | 43 + hazel.opam.locked | 251 + opam.export | 204 - src/haz3lcore/CodeString.re | 2 +- src/haz3lcore/Measured.re | 214 +- src/haz3lcore/TermMap.re | 4 +- src/haz3lcore/TermRanges.re | 4 +- src/haz3lcore/Unicode.re | 1 + src/haz3lcore/VarMap.re | 2 +- src/haz3lcore/assistant/AssistantCtx.re | 33 +- 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create mode 100644 src/haz3lweb/www/style/toggle.css create mode 100644 src/haz3lweb/www/style/type-display.css create mode 100644 src/haz3lweb/www/style/variables.css rename src/{haz3lweb => }/util/JsUtil.re (91%) rename src/{haz3lweb => }/util/Key.re (69%) rename src/{haz3lweb => util}/Os.re (100%) create mode 100644 src/util/Point.re create mode 100644 src/util/Util.re create mode 100644 test/Test_Evaluator.re create mode 100644 test/Test_Statics.re diff --git a/.gitattributes b/.gitattributes index ad70a23062..bac26af878 100644 --- a/.gitattributes +++ b/.gitattributes @@ -2,3 +2,16 @@ # decides that the content is text, its line endings are converted to LF on # checkin. When the file has been committed with CRLF, no conversion is done. * text=auto + + +# Mark generated code and documentation as such to exclude them from PR diffs and stats. +# More information: https://github.com/github-linguist/linguist/blob/master/docs/overrides.md#generated-code +src/haz3lweb/Init.ml linguist-generated +src/haz3lweb/exercises/**/*.ml linguist-generated + +hazel.opam linguist-generated +hazel.opam.locked linguist-generated + +*.md linguist-documentation +docs/** linguist-documentation + diff --git a/.github/workflows/deploy_branches.yml b/.github/workflows/deploy_branches.yml index ef58967931..e97dabb62b 100644 --- a/.github/workflows/deploy_branches.yml +++ b/.github/workflows/deploy_branches.yml @@ -16,55 +16,42 @@ jobs: path: source - name: Add the name of the current branch to the environment as BRANCH_NAME uses: nelonoel/branch-name@v1.0.1 - - name: Retrieve the build environment if cached - id: opam-cache - uses: actions/cache@v2 - with: - path: '/home/runner/.opam/' - key: ${{ runner.os }}-modules-${{ hashFiles('./source/opam.export') }} - name: Set-up OCaml - run: | - sudo apt --assume-yes install curl m4 opam - export OPAMYES=1 - opam init --compiler=ocaml-base-compiler.5.0.0 + uses: ocaml/setup-ocaml@v3 + with: + ocaml-compiler: 5.2.0 + dune-cache: true + - name: Retrieve the switch environment if cached + id: opam-cache-switch + uses: actions/cache@v4 + with: + path: '_opam' + key: ${{ runner.os }}-modules-${{ hashFiles('./source/hazel.opam.locked') }} - name: Install dependencies run: | eval $(opam env) export OPAMYES=1 - make deps + export DUNE_CACHE=enabled + opam install . --deps-only --with-test --locked working-directory: ./source - - name: Build Hazel + - name: Clean opam switch run: | eval $(opam env) - make release - working-directory: ./source - - name: Run Tests - id: test - continue-on-error: true + export OPAMYES=1 + opam clean --all-switches --download-cache --logs --repo-cache --unused-repositories + - name: Build Release run: | - eval $(opam env) - make test > test_output - if [ $? -eq 0 ]; then - echo "::set-output name=tests_passed::true" - else - echo "::set-output name=tests_passed::false" - fi + export DUNE_CACHE=enabled + opam exec -- dune build @src/fmt --auto-promote src --profile release working-directory: ./source - - name: Test Report - uses: dorny/test-reporter@v1 - continue-on-error: true - with: - name: Test Report - path: junit_tests*.xml - reporter: java-junit - fail-on-error: true - working-directory: ./source - name: Checkout the website build artifacts repo - uses: actions/checkout@v2 + uses: actions/checkout@v4 with: repository: hazelgrove/build token: ${{ secrets.ACCESS_TOKEN }} path: server + sparse-checkout: | + ${{ env.BRANCH_NAME }} - name: Clear any old build of this branch run: if [ -d "${BRANCH_NAME}" ] ; then rm -rf "${BRANCH_NAME}" ; fi working-directory: ./server @@ -78,4 +65,19 @@ jobs: git pull --no-edit git status git diff-index --quiet HEAD || (git commit -m "github-deploy-action-${BRANCH_NAME}"; git push) - working-directory: ./server \ No newline at end of file + working-directory: ./server + - name: Run Tests + id: test + run: | + eval $(opam env) + make test + working-directory: ./source + - name: Test Report + uses: dorny/test-reporter@v1 + with: + name: Test Report + path: junit_tests*.xml + reporter: java-junit + fail-on-error: true + fail-on-empty: true # Use an empty test report to detect when something failed with the test runner + working-directory: ./source \ No newline at end of file diff --git a/.gitignore b/.gitignore index 7916107af5..ec464113b6 100644 --- a/.gitignore +++ b/.gitignore @@ -53,3 +53,6 @@ setup.log # unit tests *.xml + +# Backup of opam lock file +hazel.opam.locked.old diff --git a/INSTALL.md b/INSTALL.md index e237ae6721..76142d0a29 100644 --- a/INSTALL.md +++ b/INSTALL.md @@ -119,16 +119,16 @@ follow these instructions instead of the shorter instructions in the opam update ``` -- Install OCaml 5.0.0 (some older versions may also work; see the +- Install OCaml 5.2.0 (some older versions may also work; see the ["Current version" section of `Updating.md`](docs/Updating-OCaml-Version.md) for why we may not use the newest version of OCaml). ```sh - opam switch create 5.0.0 ocaml-base-compiler.5.0.0 + opam switch create 5.2.0 ocaml-base-compiler.5.2.0 ``` - Update the current switch environment ```sh - eval $(opam env --switch=5.0.0) + eval $(opam env --switch=5.2.0) ``` ## Clone the Source Code diff --git a/Makefile b/Makefile index 48e813a625..c1f5943d07 100644 --- a/Makefile +++ b/Makefile @@ -8,10 +8,14 @@ all: dev deps: opam update - opam switch import opam.export + opam install ./hazel.opam.locked --deps-only --with-test --with-doc change-deps: - opam switch export opam.export + opam update + dune build hazel.opam + opam install ./hazel.opam --deps-only --with-test --with-doc + opam lock . + sed -i'.old' '/host-/d' hazel.opam.locked # remove host- lines which are arch-specific. Not using -i '' because of portability issues https://stackoverflow.com/questions/4247068/sed-command-with-i-option-failing-on-mac-but-works-on-linux setup-instructor: cp src/haz3lweb/ExerciseSettings_instructor.re src/haz3lweb/ExerciseSettings.re @@ -19,12 +23,13 @@ setup-instructor: setup-student: cp src/haz3lweb/ExerciseSettings_student.re src/haz3lweb/ExerciseSettings.re -dev-helper: +dev-helper: + dune fmt --auto-promote || true dune build @src/fmt --auto-promote src --profile dev dev: setup-instructor dev-helper -dev-student: setup-student dev +dev-student: setup-student dev-helper fmt: dune fmt --auto-promote @@ -39,7 +44,7 @@ release: setup-instructor dune build @src/fmt --auto-promote src --profile release release-student: setup-student - dune build @src/fmt --auto-promote src --profile dev + dune build @src/fmt --auto-promote src --profile dev # Uses dev profile for performance reasons. It may be worth it to retest since the ocaml upgrade echo-html-dir: @echo $(HTML_DIR) @@ -54,8 +59,12 @@ repl: dune utop src/haz3lcore test: + dune fmt --auto-promote || true dune build @src/fmt @test/fmt --auto-promote src test --profile dev node $(TEST_DIR)/haz3ltest.bc.js +watch-test: + dune build @fmt @runtest --auto-promote --watch + clean: dune clean diff --git a/README.md b/README.md index 7547518e8a..a15bdd424e 100644 --- a/README.md +++ b/README.md @@ -17,7 +17,7 @@ can also be accessed at: ### Short version -If you already have `ocaml` version 5.0.0 and least version 2.0 of `opam` +If you already have `ocaml` version 5.2.0 and at least version 2.0 of `opam` installed, you can build Hazel by running the following commands. - `git clone git@github.com:hazelgrove/hazel.git` @@ -155,7 +155,7 @@ To obtain an clean build, you may need to: ```sh # opam switch remove ./ - opam switch create ./ 5.0.0 + opam switch create ./ 5.2.0 eval $(opam env) make deps make @@ -185,7 +185,9 @@ helper functions for printing and serializing this data. For a type named `t`, t for a type named something else like `q`, it will be `show_q`. #### Source Maps -`js_of_ocaml` does support source maps and has some other flags that might be useful. If you experiment with those and get them to work, please update this README with some notes. +Source maps for `js_of_ocaml` should be configured when making locally with the dev profile (`make`). This is configured using the env stanzas present in the `dune` files for each top-level directory. + +Since source maps are generated browser developer tools should show reason code in the debugger and source tree. Stack traces should also include reason line numbers. #### Debug Mode If Hazel is hanging on load or when you perform certain actions, you can load into Debug Mode by appending `#debug` to the URL and reloading. From there, you have some buttons that will change settings or reset local storage. Refresh without the `#debug` flag and hopefully you can resolve the situation from there. @@ -205,3 +207,12 @@ that will build that branch (in `release` mode) and deploy it to the URL It usually takes about 2 minutes if the build environment cache hits, or 20+ minutes if not. You can view the status of the build in the [Actions tab on Github](https://github.com/hazelgrove/hazel/actions). + +Builds prior to July 2024 are archived at `https://hazel.org/build/`. + +Note: If another archive needs to be performed, make sure to redeploy the following +branches manually since we refer to them in various public material (websites and +published papers): + + dev + livelits diff --git a/docs/Change-OCaml-Dependencies.md b/docs/Change-OCaml-Dependencies.md new file mode 100644 index 0000000000..34a1d51369 --- /dev/null +++ b/docs/Change-OCaml-Dependencies.md @@ -0,0 +1,12 @@ +# Instructions for Changing Ocaml Dependencies + +## How to update dependencies + +- Update the dune-project file to reflect the new dependency constraints +- `make change-deps` + - This should generate the hazel.opam file from dune. + - Depending on your installed dependencies you may need to make a new clean switch +- Interrogate the `hazel.opam.locked` file to see what dependencies have changed +- `make release` +- Test in Firefox and Chrome. +- Commit changed files and push \ No newline at end of file diff --git a/docs/Updating-OCaml-Version.md b/docs/Updating-OCaml-Version.md index dd63385991..72c324a0c9 100644 --- a/docs/Updating-OCaml-Version.md +++ b/docs/Updating-OCaml-Version.md @@ -2,7 +2,7 @@ ## Current version -The most recent version that we use is Ocaml 5.0.0. +The most recent version that we use is Ocaml 5.2.0. If there are known issues with more recent version of OCaml, we will list them here. ## How to update Hazel to use a new version of ocaml @@ -16,7 +16,7 @@ To update do the following: - `opam switch list-available` - Choose the most recent version, but no later than the public release on - ocaml.org (e.g., `5.0.0`). + ocaml.org (e.g., `5.2.0`). - Create a new branch called `update_ocaml_VERSION` where VERSION is the version of OCaml you intend to upgrade to. @@ -24,7 +24,7 @@ To update do the following: `git checkout -b update_ocaml_VERSION` - `opam switch create VERSION`, where `VERSION` is the most recent OCaml version - that does not contain a `+` character (e.g., `4.12.1`). + that does not contain a `+` character (e.g., `5.2.0`). - `make deps` @@ -59,10 +59,23 @@ To update do the following: - Merge your branch with either `dev` or `update_ocaml_VERSION` if that is tricky. - - Update your OCaml installation by running the following: + - Update your `opam`. ``` opam update + ``` + + If you get the following warning: + + ``` + [WARNING] opam is out-of-date. Please consider updating it (https://opam.ocaml.org/doc/Install.html) + ``` + + You may want to update opam by following the instructions for your platform at that link. + + - Update your OCaml installation by running the following: + + ``` opam switch create VERSION eval $(opam env) make deps diff --git a/docs/hazel-architecture-july-2024.png b/docs/hazel-architecture-july-2024.png new file mode 100644 index 0000000000000000000000000000000000000000..38a8a11377a59df6c89b5dbaeff2af10f1a094fa GIT binary patch literal 403192 zcmeEucUTi!w?0KssVYdXdQcJR0@6Xm0#XF&1O%i85_&HpO{q3|SE`gqhlD1fs6gnQ z5CYOe=ruro<2mQM_j}~KzvtfnPo5{tWM=l1wfA1@UGI8_*V>v7XsOt!NJvO%A3eOM zLqbBeO+rHHdyW#=a(%W&YSj*(gh7qoKC;aNA3e z&wDaBUH~JDk=i@i%M>R{yWuCrND9(_zPjgAAVYG{a@WPwjz^wPB1UtW^p6)LY|fN$ z4oL7TRtARiS+way$QtCXx!njyjxiBOgynsmWp*Z2vgAQcUv}Q&RX9Up)^_iX8BS60fCR4?99MO;OZDeX}GTvDC9RggVS zU-tgZ^$TQK_ajDy6@xC(&$z#G%8EN@S*UPz_H24_lf4ZM*!7MP(olgpnV;f3)jgjy zd!nuMNzL5Cqi{>ZuX*nT>7w4FScg~j@j2)C^@D4*k}h7RExXpreMT->vGoR@$)$uF 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2024-06-14 at 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complete stanza docs at https://dune.readthedocs.io/en/stable/reference/dune-project/index.html diff --git a/dune-workspace b/dune-workspace new file mode 100644 index 0000000000..480ccb1514 --- /dev/null +++ b/dune-workspace @@ -0,0 +1,9 @@ +(lang dune 3.16) + +(env + (dev + (flags + (:standard -warn-error -A))) + (release + (flags + (:standard -warn-error +A-58)))) diff --git a/hazel.opam b/hazel.opam new file mode 100644 index 0000000000..e78b188325 --- /dev/null +++ b/hazel.opam @@ -0,0 +1,43 @@ +# This file is generated by dune, edit dune-project instead +opam-version: "2.0" +synopsis: "Hazel, a live functional programming environment with typed holes" +maintainer: ["Hazel Development Team"] +authors: ["Hazel Development Team"] +license: "MIT" +homepage: "https://github.com/hazelgrove/hazel" +bug-reports: "https://github.com/hazelgrove/hazel/issues" +depends: [ + "dune" {>= "3.16"} + "ocaml" {>= "5.2.0"} + "menhir" {>= "2.0"} + "yojson" + "reason" + "ppx_yojson_conv_lib" + "ppx_yojson_conv" + "omd" {>= "2.0.0~alpha4"} + "ezjs_idb" + "bonsai" + "ppx_deriving" + "ptmap" + "uuidm" {= "0.9.8"} + "unionFind" + "ocamlformat" + "junit_alcotest" {with-test} + "ocaml-lsp-server" + "odoc" {with-doc} +] +build: [ + ["dune" "subst"] {dev} + [ + "dune" + "build" + "-p" + name + "-j" + jobs + "@install" + "@runtest" {with-test} + "@doc" {with-doc} + ] +] +dev-repo: "git+https://github.com/hazelgrove/hazel.git" diff --git a/hazel.opam.locked b/hazel.opam.locked new file mode 100644 index 0000000000..b2cfce2cea --- /dev/null +++ b/hazel.opam.locked @@ -0,0 +1,251 @@ + +opam-version: "2.0" +name: "hazel" +version: "dev" +synopsis: "Hazel, a live functional programming environment with typed holes" +maintainer: "Hazel Development Team" +authors: "Hazel Development Team" +license: "MIT" +homepage: "https://github.com/hazelgrove/hazel" +bug-reports: "https://github.com/hazelgrove/hazel/issues" +depends: [ + "abstract_algebra" {= "v0.16.0"} + "alcotest" {= "1.8.0" & with-test} + "angstrom" {= "0.16.1"} + "astring" {= "0.8.5"} + "async" {= "v0.16.0"} + "async_durable" {= "v0.16.0"} + "async_extra" {= "v0.16.0"} + "async_js" {= "v0.16.0"} + "async_kernel" {= "v0.16.0"} + "async_rpc_kernel" {= "v0.16.0"} + "async_rpc_websocket" {= "v0.16.0"} + "async_ssl" {= "v0.16.1"} + "async_unix" {= "v0.16.0"} + "async_websocket" {= "v0.16.0"} + "babel" {= "v0.16.0"} + "base" {= "v0.16.3"} + "base-bigarray" {= "base"} + "base-bytes" {= "base"} + "base-domains" {= "base"} + "base-nnp" {= "base"} + "base-threads" {= "base"} + "base-unix" {= "base"} + "base64" {= "3.5.1"} + "base_bigstring" {= "v0.16.0"} + "base_quickcheck" {= "v0.16.0"} + "bigarray-compat" {= "1.1.0"} + "bignum" {= "v0.16.0"} + "bigstringaf" {= "0.10.0"} + "bin_prot" {= "v0.16.0"} + "bonsai" {= "v0.16.0"} + "camlp-streams" {= "5.0.1"} + "chrome-trace" {= "3.16.0"} + "cmdliner" {= "1.3.0"} + "cohttp" {= "5.3.1"} + "cohttp-async" {= "5.3.0"} + "cohttp_async_websocket" {= "v0.16.0"} + "conduit" {= "7.1.0"} + "conduit-async" {= "7.1.0"} + "conf-bash" {= "1"} + "conf-gmp" {= "4"} + "conf-gmp-powm-sec" {= "3"} + "conf-libffi" {= "2.0.0"} + "conf-libssl" {= "4"} + "conf-pkg-config" {= "3"} + "conf-zlib" {= "1"} + "core" {= "v0.16.2"} + "core_bench" {= "v0.16.0"} + "core_kernel" {= "v0.16.0"} + "core_unix" {= "v0.16.0"} + "cppo" {= "1.7.0"} + "crunch" {= "3.3.1" & with-doc} + "cryptokit" {= "1.16.1"} + "csexp" {= "1.5.2"} + "ctypes" {= "0.23.0"} + "ctypes-foreign" {= "0.23.0"} + "diffable" {= "v0.16.0"} + "domain-name" {= "0.4.0"} + "dune" {= "3.16.0"} + "dune-build-info" {= "3.16.0"} + "dune-configurator" {= "3.16.0"} + "dune-rpc" {= "3.16.0"} + "dyn" {= "3.16.0"} + "either" {= "1.0.0"} + "expect_test_helpers_core" {= "v0.16.0"} + "ezjs_idb" {= "0.1.1"} + "ezjs_min" {= "0.3.0"} + "fiber" {= "3.7.0"} + "fieldslib" {= "v0.16.0"} + "fix" {= "20230505"} + "fmt" {= "0.9.0"} + "fpath" {= "0.7.3"} + "fuzzy_match" {= "v0.16.0"} + "gen" {= "1.1"} + "gen_js_api" {= "1.1.3"} + "incr_dom" {= "v0.16.0"} + "incr_map" {= "v0.16.0"} + "incr_select" {= "v0.16.0"} + "incremental" {= "v0.16.1"} + "indentation_buffer" {= "v0.16.0"} + "int_repr" {= "v0.16.0"} + "integers" {= "0.7.0"} + "ipaddr" {= "5.6.0"} + "ipaddr-sexp" {= "5.6.0"} + "jane-street-headers" {= "v0.16.0"} + "janestreet_lru_cache" {= "v0.16.1"} + "js_of_ocaml" {= "5.8.2"} + "js_of_ocaml-compiler" {= "5.8.2"} + "js_of_ocaml-ppx" {= "5.8.2"} + "js_of_ocaml_patches" {= "v0.16.0"} + "jsonm" {= "1.0.2"} + "jsonrpc" {= "1.19.0"} + "jst-config" {= "v0.16.0"} + "junit" {= "2.0.2" & with-test} + "junit_alcotest" {= "2.0.2" & with-test} + "lambdasoup" {= "1.1.1"} + "logs" {= "0.7.0"} + "lsp" {= "1.19.0"} + "macaddr" {= "5.6.0"} + "magic-mime" {= "1.3.1"} + "markup" {= "1.0.3"} + "menhir" {= "20240715"} + "menhirCST" {= "20240715"} + "menhirLib" {= "20240715"} + "menhirSdk" {= "20240715"} + "merlin-extend" {= "0.6.1"} + "merlin-lib" {= "5.2.1-502"} + "num" {= "1.5-1"} + "ocaml" {= "5.2.0"} + "ocaml-base-compiler" {= "5.2.0"} + "ocaml-compiler-libs" {= "v0.17.0"} + "ocaml-config" {= "3"} + "ocaml-embed-file" {= "v0.16.0"} + "ocaml-index" {= "1.1"} + "ocaml-lsp-server" {= "1.19.0"} + "ocaml-options-vanilla" {= "1"} + "ocaml-syntax-shims" {= "1.0.0"} + "ocaml-version" {= "3.6.9"} + "ocaml_intrinsics" {= "v0.16.1"} + "ocamlbuild" {= "0.15.0"} + "ocamlc-loc" {= "3.16.0"} + "ocamlfind" {= "1.9.6"} + "ocamlformat" {= "0.26.2"} + "ocamlformat-lib" {= "0.26.2"} + "ocamlformat-rpc-lib" {= "0.26.2"} + "ocp-indent" {= "1.8.1"} + "octavius" {= "1.2.2"} + "odoc" {= "2.4.3" & with-doc} + "odoc-parser" {= "2.4.3" & with-doc} + "ojs" {= "1.1.3"} + "omd" {= "2.0.0~alpha4"} + "ordering" {= "3.16.0"} + "ordinal_abbreviation" {= "v0.16.0"} + "parsexp" {= "v0.16.0"} + "patdiff" {= "v0.16.1"} + "patience_diff" {= "v0.16.0"} + "polling_state_rpc" {= "v0.16.0"} + "pp" {= "1.2.0"} + "ppx_assert" {= "v0.16.0"} + "ppx_base" {= "v0.16.0"} + "ppx_bench" {= "v0.16.0"} + "ppx_bin_prot" {= "v0.16.0"} + "ppx_cold" {= "v0.16.0"} + "ppx_compare" {= "v0.16.0"} + "ppx_css" {= "v0.16.0"} + "ppx_custom_printf" {= "v0.16.0"} + "ppx_derivers" {= "1.2.1"} + "ppx_deriving" {= "6.0.2"} + "ppx_disable_unused_warnings" {= "v0.16.0"} + "ppx_enumerate" {= "v0.16.0"} + "ppx_expect" {= "v0.16.0"} + "ppx_fields_conv" {= "v0.16.0"} + "ppx_fixed_literal" {= "v0.16.0"} + "ppx_globalize" {= "v0.16.0"} + "ppx_hash" {= "v0.16.0"} + "ppx_here" {= "v0.16.0"} + "ppx_ignore_instrumentation" {= "v0.16.0"} + "ppx_inline_test" {= "v0.16.1"} + "ppx_jane" {= "v0.16.0"} + "ppx_js_style" {= "v0.16.0"} + "ppx_let" {= "v0.16.0"} + "ppx_log" {= "v0.16.0"} + "ppx_module_timer" {= "v0.16.0"} + "ppx_optcomp" {= "v0.16.0"} + "ppx_optional" {= "v0.16.0"} + "ppx_pattern_bind" {= "v0.16.0"} + "ppx_pipebang" {= "v0.16.0"} + "ppx_sexp_conv" {= "v0.16.0"} + "ppx_sexp_message" {= "v0.16.0"} + "ppx_sexp_value" {= "v0.16.0"} + "ppx_stable" {= "v0.16.0"} + "ppx_stable_witness" {= "v0.16.0"} + "ppx_string" {= "v0.16.0"} + "ppx_tydi" {= "v0.16.0"} + "ppx_typed_fields" {= "v0.16.0"} + "ppx_typerep_conv" {= "v0.16.0"} + "ppx_variants_conv" {= "v0.16.0"} + "ppx_yojson_conv" {= "v0.16.0"} + "ppx_yojson_conv_lib" {= "v0.16.0"} + "ppxlib" {= "0.33.0"} + "profunctor" {= "v0.16.0"} + "protocol_version_header" {= "v0.16.0"} + "ptime" {= "1.2.0" & with-test} + "ptmap" {= "2.0.5"} + "re" {= "1.12.0"} + "reason" {= "3.12.0"} + "record_builder" {= "v0.16.0"} + "result" {= "1.5"} + "sedlex" {= "3.2"} + "seq" {= "base"} + "sexp_grammar" {= "v0.16.0"} + "sexp_pretty" {= "v0.16.0"} + "sexplib" {= "v0.16.0"} + "sexplib0" {= "v0.16.0"} + "spawn" {= "v0.15.1"} + "splittable_random" {= "v0.16.0"} + "stdio" {= "v0.16.0"} + "stdlib-shims" {= "0.3.0"} + "stdune" {= "3.16.0"} + "stored_reversed" {= "v0.16.0"} + "streamable" {= "v0.16.1"} + "stringext" {= "1.6.0"} + "textutils" {= "v0.16.0"} + "textutils_kernel" {= "v0.16.0"} + "tilde_f" {= "v0.16.0"} + "time_now" {= "v0.16.0"} + "timezone" {= "v0.16.0"} + "topkg" {= "1.0.7"} + "typerep" {= "v0.16.0"} + "tyxml" {= "4.6.0"} + "uchar" {= "0.0.2"} + "unionFind" {= "20220122"} + "uri" {= "4.4.0"} + "uri-sexp" {= "4.4.0"} + "uucp" {= "16.0.0"} + "uuidm" {= "0.9.8"} + "uunf" {= "16.0.0"} + "uuseg" {= "16.0.0"} + "uutf" {= "1.0.3"} + "variantslib" {= "v0.16.0"} + "virtual_dom" {= "v0.16.0"} + "xdg" {= "3.16.0"} + "yojson" {= "2.2.2"} + "zarith" {= "1.14"} + "zarith_stubs_js" {= "v0.16.1"} +] +build: [ + ["dune" "subst"] {dev} + [ + "dune" + "build" + "-p" + name + "-j" + jobs + "@install" + "@runtest" {with-test} + "@doc" {with-doc} + ] +] +dev-repo: "git+https://github.com/hazelgrove/hazel.git" \ No newline at end of file diff --git a/opam.export b/opam.export deleted file mode 100644 index e8a656aa66..0000000000 --- a/opam.export +++ /dev/null @@ -1,204 +0,0 @@ -opam-version: "2.0" -compiler: ["ocaml-base-compiler.5.0.0"] -roots: [ - "ezjs_idb.0.1.1" - "incr_dom.v0.15.1" - "lwt.5.7.0" - "lwt-dllist.1.0.1" - "merlin.4.13-500" - "ocaml-base-compiler.5.0.0" - "ocaml-lsp-server.1.17.0" - "ocamlformat.0.26.1" - "omd.1.3.2" - "ppx_deriving.5.2.1" - "ppx_yojson_conv.v0.15.1" - "ptmap.2.0.5" - "reason.3.10.0" - "tezt.4.0.0" - "unionFind.20220122" - "utop.2.13.1" - "uuidm.0.9.8" -] -installed: [ - "abstract_algebra.v0.15.0" - "alcotest.1.7.0" - "angstrom.0.16.0" - "astring.0.8.5" - "async_js.v0.15.1" - "async_kernel.v0.15.0" - "async_rpc_kernel.v0.15.0" - "base.v0.15.1" - "base-bigarray.base" - "base-bytes.base" - "base-domains.base" - "base-nnp.base" - "base-threads.base" - "base-unix.base" - "base_bigstring.v0.15.0" - "base_quickcheck.v0.15.0" - "bigstringaf.0.9.1" - "bin_prot.v0.15.0" - "camlp-streams.5.0.1" - "chrome-trace.3.13.1" - "clap.0.3.0" - "cmdliner.1.2.0" - "conf-autoconf.0.1" - "conf-which.1" - "core.v0.15.1" - "core_kernel.v0.15.0" - "cppo.1.6.9" - "csexp.1.5.2" - "cstruct.6.2.0" - "dot-merlin-reader.4.9" - "dune.3.13.1" - "dune-build-info.3.13.1" - "dune-configurator.3.13.1" - "dune-rpc.3.13.1" - "dyn.3.13.1" - "either.1.0.0" - "ezjs_idb.0.1.1" - "ezjs_min.0.3.0" - "ezjsonm.1.3.0" - "fiber.3.7.0" - "fieldslib.v0.15.0" - "fix.20230505" - "fmt.0.9.0" - "fpath.0.7.3" - "gen.1.1" - "gen_js_api.1.1.2" - "hex.1.5.0" - "incr_dom.v0.15.1" - "incr_map.v0.15.0" - "incr_select.v0.15.0" - "incremental.v0.15.0" - "int_repr.v0.15.0" - "jane-street-headers.v0.15.0" - "js_of_ocaml.5.6.0" - "js_of_ocaml-compiler.5.6.0" - "js_of_ocaml-ppx.5.6.0" - "jsonm.1.0.2" - "jst-config.v0.15.1" - "junit.2.0.2" - "junit_alcotest.2.0.1" - "lambda-term.3.3.2" - "lambdasoup.1.0.0" - "logs.0.7.0" - "lwt.5.7.0" - "lwt-dllist.1.0.1" - "lwt_react.1.2.0" - "markup.1.0.3" - "menhir.20231231" - "menhirCST.20231231" - "menhirLib.20231231" - "menhirSdk.20231231" - "merlin.4.13-500" - "merlin-extend.0.6.1" - "merlin-lib.4.13-500" - "mew.0.1.0" - "mew_vi.0.5.0" - "num.1.5" - "ocaml.5.0.0" - "ocaml-base-compiler.5.0.0" - "ocaml-compiler-libs.v0.12.4" - "ocaml-config.3" - "ocaml-lsp-server.1.17.0" - "ocaml-options-vanilla.1" - "ocaml-syntax-shims.1.0.0" - "ocaml-version.3.6.4" - "ocamlbuild.0.14.3" - "ocamlc-loc.3.13.1" - "ocamlfind.1.9.6" - "ocamlformat.0.26.1" - "ocamlformat-lib.0.26.1" - "ocamlformat-rpc-lib.0.26.1" - "ocp-indent.1.8.1" - "ocplib-endian.1.2" - "octavius.1.2.2" - "odoc-parser.2.4.1" - "ojs.1.1.2" - "omd.1.3.2" - "ordering.3.13.1" - "parsexp.v0.15.0" - "pp.1.2.0" - "ppx_assert.v0.15.0" - "ppx_base.v0.15.0" - "ppx_bench.v0.15.1" - "ppx_bin_prot.v0.15.0" - "ppx_cold.v0.15.0" - "ppx_compare.v0.15.0" - "ppx_custom_printf.v0.15.0" - "ppx_derivers.1.2.1" - "ppx_deriving.5.2.1" - "ppx_disable_unused_warnings.v0.15.0" - "ppx_enumerate.v0.15.0" - "ppx_expect.v0.15.1" - "ppx_fields_conv.v0.15.0" - "ppx_fixed_literal.v0.15.0" - "ppx_hash.v0.15.0" - "ppx_here.v0.15.0" - "ppx_ignore_instrumentation.v0.15.0" - "ppx_inline_test.v0.15.1" - "ppx_jane.v0.15.0" - "ppx_js_style.v0.15.0" - "ppx_let.v0.15.0" - "ppx_log.v0.15.0" - "ppx_module_timer.v0.15.0" - "ppx_optcomp.v0.15.0" - "ppx_optional.v0.15.0" - "ppx_pattern_bind.v0.15.0" - "ppx_pipebang.v0.15.0" - "ppx_sexp_conv.v0.15.1" - "ppx_sexp_message.v0.15.0" - "ppx_sexp_value.v0.15.0" - "ppx_stable.v0.15.0" - "ppx_string.v0.15.0" - "ppx_typerep_conv.v0.15.0" - "ppx_variants_conv.v0.15.0" - "ppx_yojson_conv.v0.15.1" - "ppx_yojson_conv_lib.v0.15.0" - "ppxlib.0.32.0" - "protocol_version_header.v0.15.0" - "ptmap.2.0.5" - "re.1.11.0" - "react.1.2.2" - "reason.3.10.0" - "result.1.5" - "sedlex.3.2" - "seq.base" - "sexplib.v0.15.1" - "sexplib0.v0.15.1" - "spawn.v0.15.1" - "splittable_random.v0.15.0" - "stdcompat.19" - "stdio.v0.15.0" - "stdlib-shims.0.3.0" - "stdune.3.13.1" - "stringext.1.6.0" - "tezt.4.0.0" - "time_now.v0.15.0" - "topkg.1.0.7" - "trie.1.0.0" - "typerep.v0.15.0" - "tyxml.4.6.0" - "uchar.0.0.2" - "unionFind.20220122" - "uri.4.4.0" - "uri-sexp.4.4.0" - "utop.2.13.1" - "uucp.15.1.0" - "uuidm.0.9.8" - "uunf.15.1.0" - "uuseg.15.1.0" - "uutf.1.0.3" - "variantslib.v0.15.0" - "virtual_dom.v0.15.1" - "xdg.3.13.1" - "yojson.2.1.2" - "zed.3.2.3" -] -pinned: [ - "async_js.v0.15.1" - "incr_dom.v0.15.1" - "sexplib.v0.15.1" - "virtual_dom.v0.15.1" -] diff --git a/src/haz3lcore/CodeString.re b/src/haz3lcore/CodeString.re index ddca7721bf..a6ddd14875 100644 --- a/src/haz3lcore/CodeString.re +++ b/src/haz3lcore/CodeString.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type t = string; diff --git a/src/haz3lcore/Measured.re b/src/haz3lcore/Measured.re index 5ed9d0264d..61dad8a831 100644 --- a/src/haz3lcore/Measured.re +++ b/src/haz3lcore/Measured.re @@ -1,45 +1,7 @@ -open Sexplib.Std; open Util; +open Point; -[@deriving (show({with_path: false}), sexp, yojson)] -type row = int; -[@deriving (show({with_path: false}), sexp, yojson)] -type col = int; - -module Point = { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = { - row, - col, - }; - let zero = {row: 0, col: 0}; - - let equals: (t, t) => bool = (p, q) => p.row == q.row && p.col == q.col; - - type comparison = - | Exact - | Under - | Over; - - let comp = (current, target): comparison => - switch () { - | _ when current == target => Exact - | _ when current < target => Under - | _ => Over - }; - let compare = (p1, p2) => - switch (comp(p1, p2)) { - | Exact => 0 - | Under => (-1) - | Over => 1 - }; - - let dcomp = (direction: Direction.t, a, b) => - switch (direction) { - | Right => comp(a, b) - | Left => comp(b, a) - }; -}; +module Point = Point; [@deriving (show({with_path: false}), sexp, yojson)] type measurement = { @@ -86,17 +48,13 @@ module Shards = { snd(List.hd(row)).origin.row == snd(hd).origin.row ? [[hd, ...row], ...rows] : [[hd], row, ...rows] }; - // let last = (shards: t) => - // shards - // |> List.sort(((i, _), (j, _)) => Int.compare(i, j)) - // |> ListUtil.last_opt - // |> Option.map(snd); }; type t = { tiles: Id.Map.t(Shards.t), grout: Id.Map.t(measurement), secondary: Id.Map.t(measurement), + projectors: Id.Map.t(measurement), rows: Rows.t, linebreaks: Id.Map.t(rel_indent), }; @@ -105,6 +63,7 @@ let empty = { tiles: Id.Map.empty, grout: Id.Map.empty, secondary: Id.Map.empty, + projectors: Id.Map.empty, rows: Rows.empty, linebreaks: Id.Map.empty, }; @@ -145,12 +104,17 @@ let add_w = (w: Secondary.t, m, map) => { ...map, secondary: map.secondary |> Id.Map.add(w.id, m), }; +let add_pr = (p: Base.projector, m, map) => { + ...map, + projectors: map.projectors |> Id.Map.add(p.id, m), +}; let add_p = (p: Piece.t, m, map) => p |> Piece.get( w => add_w(w, m, map), g => add_g(g, m, map), t => add_t(t, m, map), + pr => add_pr(pr, m, map), ); let add_row = (row: int, shape: Rows.shape, map) => { @@ -158,6 +122,15 @@ let add_row = (row: int, shape: Rows.shape, map) => { rows: Rows.add(row, shape, map.rows), }; +let rec add_n_rows = (origin: Point.t, row_indent, n: abs_indent, map: t): t => + switch (n) { + | 0 => map + | _ => + map + |> add_n_rows(origin, row_indent, n - 1) + |> add_row(origin.row + n - 1, {indent: row_indent, max_col: origin.col}) + }; + let add_lb = (id, indent, map) => { ...map, linebreaks: Id.Map.add(id, indent, map.linebreaks), @@ -169,7 +142,10 @@ let singleton_s = (id, shard, m) => empty |> add_s(id, shard, m); // TODO(d) rename let find_opt_shards = (t: Tile.t, map) => Id.Map.find_opt(t.id, map.tiles); -let find_shards = (t: Tile.t, map) => Id.Map.find(t.id, map.tiles); +let find_shards = (~msg="", t: Tile.t, map) => + try(Id.Map.find(t.id, map.tiles)) { + | _ => failwith("find_shards: " ++ msg) + }; let find_opt_lb = (id, map) => Id.Map.find_opt(id, map.linebreaks); @@ -179,25 +155,45 @@ let find_shards' = (id: Id.t, map) => | Some(ss) => ss }; -let find_w = (w: Secondary.t, map): measurement => - Id.Map.find(w.id, map.secondary); -let find_g = (g: Grout.t, map): measurement => Id.Map.find(g.id, map.grout); +let find_w = (~msg="", w: Secondary.t, map): measurement => + try(Id.Map.find(w.id, map.secondary)) { + | _ => failwith("find_w: " ++ msg) + }; +let find_g = (~msg="", g: Grout.t, map): measurement => + try(Id.Map.find(g.id, map.grout)) { + | _ => failwith("find_g: " ++ msg) + }; +let find_pr = (~msg="", p: Base.projector, map): measurement => + try(Id.Map.find(p.id, map.projectors)) { + | _ => failwith("find_g: " ++ msg) + }; +let find_pr_opt = (p: Base.projector, map): option(measurement) => + Id.Map.find_opt(p.id, map.projectors); // returns the measurement spanning the whole tile let find_t = (t: Tile.t, map): measurement => { let shards = Id.Map.find(t.id, map.tiles); - let first = ListUtil.assoc_err(Tile.l_shard(t), shards, "find_t"); - let last = ListUtil.assoc_err(Tile.r_shard(t), shards, "find_t"); + let (first, last) = + try({ + let first = ListUtil.assoc_err(Tile.l_shard(t), shards, "find_t"); + let last = ListUtil.assoc_err(Tile.r_shard(t), shards, "find_t"); + (first, last); + }) { + | _ => failwith("find_t: inconsistent shard infor between tile and map") + }; {origin: first.origin, last: last.last}; }; -// let find_a = ({shards: (l, r), _} as a: Ancestor.t, map) => -// List.assoc(l @ r, Id.Map.find(a.id, map.tiles)); -let find_p = (p: Piece.t, map): measurement => - p - |> Piece.get( - w => find_w(w, map), - g => find_g(g, map), - t => find_t(t, map), - ); +let find_p = (~msg="", p: Piece.t, map): measurement => + try( + p + |> Piece.get( + w => find_w(w, map), + g => find_g(g, map), + t => find_t(t, map), + p => find_pr(p, map), + ) + ) { + | _ => failwith("find_p: " ++ msg ++ "id: " ++ Id.to_string(p |> Piece.id)) + }; let find_by_id = (id: Id.t, map: t): option(measurement) => { switch (Id.Map.find_opt(id, map.secondary)) { @@ -218,8 +214,15 @@ let find_by_id = (id: Id.t, map: t): option(measurement) => { ); Some({origin: first.origin, last: last.last}); | None => - Printf.printf("Measured.WARNING: id %s not found", Id.to_string(id)); - None; + switch (Id.Map.find_opt(id, map.projectors)) { + | Some(m) => Some(m) + | None => + Printf.printf( + "Measured.WARNING: id %s not found", + Id.to_string(id), + ); + None; + } } } }; @@ -255,6 +258,7 @@ let is_indented_map = (seg: Segment.t) => { ) | Secondary(_) | Grout(_) => (is_indented, map) + | Projector(_) => (is_indented, map) | Tile(t) => let is_indented = is_indented || post_tile_indent(t); let map = @@ -271,7 +275,14 @@ let is_indented_map = (seg: Segment.t) => { go(seg); }; -let of_segment = (~old: t=empty, ~touched=Touched.empty, seg: Segment.t): t => { +let last_of_token = (token: string, origin: Point.t): Point.t => + /* Supports multi-line tokens e.g. projector placeholders */ + Point.{ + col: origin.col + StringUtil.max_line_width(token), + row: origin.row + StringUtil.num_linebreaks(token), + }; + +let of_segment = (seg: Segment.t, info_map: Statics.Map.t): t => { let is_indented = is_indented_map(seg); // recursive across seg's bidelimited containers @@ -283,24 +294,6 @@ let of_segment = (~old: t=empty, ~touched=Touched.empty, seg: Segment.t): t => { seg: Segment.t, ) : (Point.t, t) => { - let first_touched_incomplete = - switch (Segment.incomplete_tiles(seg)) { - | [] => None - | ts => - ts - |> List.map((t: Tile.t) => Touched.find_opt(t.id, touched)) - |> List.fold_left( - (acc, touched) => - switch (acc, touched) { - | (Some(time), Some(time')) => Some(Time.min(time, time')) - | (Some(time), _) - | (_, Some(time)) => Some(time) - | _ => None - }, - None, - ) - }; - // recursive across seg's list structure let rec go_seq = ( @@ -323,6 +316,11 @@ let of_segment = (~old: t=empty, ~touched=Touched.empty, seg: Segment.t): t => { ); (origin, map); | [hd, ...tl] => + let extra_rows = (token, origin, map) => { + let row_indent = container_indent + contained_indent; + let num_extra_rows = StringUtil.num_linebreaks(token); + add_n_rows(origin, row_indent, num_extra_rows, map); + }; let (contained_indent, origin, map) = switch (hd) { | Secondary(w) when Secondary.is_linebreak(w) => @@ -331,16 +329,7 @@ let of_segment = (~old: t=empty, ~touched=Touched.empty, seg: Segment.t): t => { if (Segment.sameline_secondary(tl)) { 0; } else { - switch ( - Touched.find_opt(w.id, touched), - first_touched_incomplete, - find_opt_lb(w.id, old), - ) { - | (Some(touched), Some(touched'), Some(indent)) - when Time.lt(touched, touched') => indent - | _ => - contained_indent + (Id.Map.find(w.id, is_indented) ? 2 : 0) - }; + contained_indent + (Id.Map.find(w.id, is_indented) ? 2 : 0); }; let last = Point.{row: origin.row + 1, col: container_indent + indent}; @@ -363,15 +352,19 @@ let of_segment = (~old: t=empty, ~touched=Touched.empty, seg: Segment.t): t => { let last = {...origin, col: origin.col + 1}; let map = map |> add_g(g, {origin, last}); (contained_indent, last, map); + | Projector(p) => + let token = + Projector.placeholder(p, Id.Map.find_opt(p.id, info_map)); + let last = last_of_token(token, origin); + let map = extra_rows(token, origin, map); + let map = add_pr(p, {origin, last}, map); + (contained_indent, last, map); | Tile(t) => - let token = List.nth(t.label); let add_shard = (origin, shard, map) => { - let last = - Point.{ - ...origin, - col: origin.col + String.length(token(shard)), - }; - let map = map |> add_s(t.id, shard, {origin, last}); + let token = List.nth(t.label, shard); + let map = extra_rows(token, origin, map); + let last = last_of_token(token, origin); + let map = add_s(t.id, shard, {origin, last}, map); (last, map); }; let (last, map) = @@ -410,28 +403,3 @@ let length = (seg: Segment.t, map: t): int => let last = find_p(ListUtil.last(tl), map); last.last.col - first.origin.col; }; - -let segment_origin = (seg: Segment.t): option(Point.t) => - Option.map( - first => find_p(first, of_segment(seg)).origin, - ListUtil.hd_opt(seg), - ); - -let segment_last = (seg: Segment.t): option(Point.t) => - Option.map( - last => find_p(last, of_segment(seg)).last, - ListUtil.last_opt(seg), - ); - -let segment_height = (seg: Segment.t) => - switch (segment_last(seg), segment_origin(seg)) { - | (Some(last), Some(first)) => 1 + last.row - first.row - | _ => 0 - }; - -let segment_width = (seg: Segment.t): int => - IntMap.fold( - (_, {max_col, _}: Rows.shape, acc) => max(max_col, acc), - of_segment(seg).rows, - 0, - ); diff --git a/src/haz3lcore/TermMap.re b/src/haz3lcore/TermMap.re index 8f42eb012f..df0f6341de 100644 --- a/src/haz3lcore/TermMap.re +++ b/src/haz3lcore/TermMap.re @@ -1,5 +1,5 @@ include Id.Map; -type t = Id.Map.t(Term.t); +type t = Id.Map.t(Any.t); -let add_all = (ids: list(Id.t), tm: Term.t, map: t) => +let add_all = (ids: list(Id.t), tm: Any.t, map: t) => ids |> List.fold_left((map, id) => add(id, tm, map), map); diff --git a/src/haz3lcore/TermRanges.re b/src/haz3lcore/TermRanges.re index 6cbc1dfe75..f6f857f14a 100644 --- a/src/haz3lcore/TermRanges.re +++ b/src/haz3lcore/TermRanges.re @@ -8,9 +8,7 @@ let union = union((_, range, _) => Some(range)); /* PERF: Up to 50% reduction in some cases by memoizing * this function. Might be better though to just do an - * unmemoized traversal building a hashtbl avoiding unioning. - - TODO(andrew): Consider setting a limit for the hashtbl size */ + * unmemoized traversal building a hashtbl avoiding unioning */ let range_hash: Hashtbl.t(Tile.segment, Id.Map.t(range)) = Hashtbl.create(1000); diff --git a/src/haz3lcore/Unicode.re b/src/haz3lcore/Unicode.re index 8f02baeb5a..e869072048 100644 --- a/src/haz3lcore/Unicode.re +++ b/src/haz3lcore/Unicode.re @@ -8,6 +8,7 @@ let zwsp = "​"; let typeArrowSym = "→"; // U+2192 "Rightwards Arrow" let castArrowSym = "⇨"; +let castBackArrowSym = "⇦"; let ellipsis = "\xE2\x80\xA6"; diff --git a/src/haz3lcore/VarMap.re b/src/haz3lcore/VarMap.re index fdd282979c..dbee5045bb 100644 --- a/src/haz3lcore/VarMap.re +++ b/src/haz3lcore/VarMap.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type t_('a) = list((Token.t, 'a)); diff --git a/src/haz3lcore/assistant/AssistantCtx.re b/src/haz3lcore/assistant/AssistantCtx.re index 1697229700..0caee1f921 100644 --- a/src/haz3lcore/assistant/AssistantCtx.re +++ b/src/haz3lcore/assistant/AssistantCtx.re @@ -1,7 +1,5 @@ open Suggestion; -let expander = AssistantExpander.c; - /* For suggestions in patterns, suggest variables which * occur free in that pattern's scope. */ let free_variables = @@ -50,12 +48,12 @@ let bound_constructors = let bound_aps = (ty_expect: Typ.t, ctx: Ctx.t): list(Suggestion.t) => List.filter_map( fun - | Ctx.VarEntry({typ: Arrow(_, ty_out) as ty_arr, name, _}) + | Ctx.VarEntry({typ: {term: Arrow(_, ty_out), _} as ty_arr, name, _}) when Typ.is_consistent(ctx, ty_expect, ty_out) && !Typ.is_consistent(ctx, ty_expect, ty_arr) => { Some({ - content: name ++ "(" ++ expander, + content: name ++ "(", strategy: Exp(Common(FromCtxAp(ty_out))), }); } @@ -66,14 +64,15 @@ let bound_aps = (ty_expect: Typ.t, ctx: Ctx.t): list(Suggestion.t) => let bound_constructor_aps = (wrap, ty: Typ.t, ctx: Ctx.t): list(Suggestion.t) => List.filter_map( fun - | Ctx.ConstructorEntry({typ: Arrow(_, ty_out) as ty_arr, name, _}) + | Ctx.ConstructorEntry({ + typ: {term: Arrow(_, ty_out), _} as ty_arr, + name, + _, + }) when Typ.is_consistent(ctx, ty, ty_out) && !Typ.is_consistent(ctx, ty, ty_arr) => - Some({ - content: name ++ "(" ++ expander, - strategy: wrap(FromCtxAp(ty_out)), - }) + Some({content: name ++ "(", strategy: wrap(FromCtxAp(ty_out))}) | _ => None, ctx, ); @@ -141,7 +140,7 @@ let suggest_lookahead_variable = (ci: Info.t): list(Suggestion.t) => { let exp_aps = ty => bound_aps(ty, ctx) @ bound_constructor_aps(x => Exp(Common(x)), ty, ctx); - switch (Mode.ty_of(mode)) { + switch (Mode.ty_of(mode) |> Typ.term_of) { | List(ty) => List.map(restrategize(" )::"), exp_aps(ty)) @ List.map(restrategize("::"), exp_refs(ty)) @@ -152,12 +151,12 @@ let suggest_lookahead_variable = (ci: Info.t): list(Suggestion.t) => { @ List.map(restrategize(commas), exp_refs(ty)); | Bool => /* TODO: Find a UI to make these less confusing */ - exp_refs(Int) - @ exp_refs(Float) - @ exp_refs(String) - @ exp_aps(Int) - @ exp_aps(Float) - @ exp_aps(String) + exp_refs(Int |> Typ.fresh) + @ exp_refs(Float |> Typ.fresh) + @ exp_refs(String |> Typ.fresh) + @ exp_aps(Int |> Typ.fresh) + @ exp_aps(Float |> Typ.fresh) + @ exp_aps(String |> Typ.fresh) | _ => [] }; | InfoPat({mode, co_ctx, _}) => @@ -165,7 +164,7 @@ let suggest_lookahead_variable = (ci: Info.t): list(Suggestion.t) => { free_variables(ty, ctx, co_ctx) @ bound_constructors(x => Pat(Common(x)), ty, ctx); let pat_aps = ty => bound_constructor_aps(x => Pat(Common(x)), ty, ctx); - switch (Mode.ty_of(mode)) { + switch (Mode.ty_of(mode) |> Typ.term_of) { | List(ty) => List.map(restrategize(" )::"), pat_aps(ty)) @ List.map(restrategize("::"), pat_refs(ty)) diff --git a/src/haz3lcore/assistant/AssistantExpander.re b/src/haz3lcore/assistant/AssistantExpander.re index 51501cd7a5..f24be63756 100644 --- a/src/haz3lcore/assistant/AssistantExpander.re +++ b/src/haz3lcore/assistant/AssistantExpander.re @@ -1,24 +1,16 @@ -/* Bit of a hack. We want to decorate suggestions which will trigger - an expansion to telegraph that expansion. Easiest way metrics wise - is to keep that deco in the syntax. Want to decorate with ellipses - character, but OCaml string functions don't support unicode, so - we use $, then swap it out for the unicode character in Code. - Eventually replace this by extending the suggestion data structure */ -let c = "$"; +/* We decorate buffers whose content will result in an + * expansion with a trailing "...". Note that this ... + * (at least in the current implementation) is not literally + * inserted into the syntax so will not be reflected + * in the decoration metrics */ -let is_expander_tok = (t: Token.t) => - String.sub(t, String.length(t) - 1, 1) == c; - -let trim_last = (t: Token.t) => String.sub(t, 0, String.length(t) - 1); +let last = t => String.sub(t, String.length(t) - 1, 1); let is_expander = (label: Label.t) => switch (label) { - | [t] => is_expander_tok(t) + | [t] => last(t) == " " || last(t) == "(" | _ => false }; let mark = (label: Label.t): Label.t => - is_expander(label) ? List.map(t => trim_last(t) ++ "…", label) : label; - -let trim = (completion: Token.t): Token.t => - is_expander_tok(completion) ? trim_last(completion) : completion; + is_expander(label) ? List.map(t => t ++ "…", label) : label; diff --git a/src/haz3lcore/assistant/AssistantForms.re b/src/haz3lcore/assistant/AssistantForms.re index 2080d9427f..f3551ac0eb 100644 --- a/src/haz3lcore/assistant/AssistantForms.re +++ b/src/haz3lcore/assistant/AssistantForms.re @@ -4,49 +4,52 @@ open OptUtil.Syntax; /* This module generates TyDi suggestions which depend * neither on the typing context or the backpack */ -let leading_expander = " " ++ AssistantExpander.c; +let leading_expander = " "; /* Specifies type information for syntactic forms. Could in principle be * derived by generating segments from Forms, parsing them to terms, and * running Statics, but for now, new forms e.g. operators must be added * below manually. */ module Typ = { - let unk: Typ.t = Unknown(Internal); + let unk: Typ.t = Unknown(Internal) |> Typ.fresh; let of_const_mono_delim: list((Token.t, Typ.t)) = [ - ("true", Bool), - ("false", Bool), + ("true", Bool |> Typ.fresh), + ("false", Bool |> Typ.fresh), //("[]", List(unk)), / *NOTE: would need to refactor buffer for this to show up */ //("()", Prod([])), /* NOTE: would need to refactor buffer for this to show up */ - ("\"\"", String), /* NOTE: Irrelevent as second quote appears automatically */ + ("\"\"", String |> Typ.fresh), /* NOTE: Irrelevent as second quote appears automatically */ ("_", unk), ]; let of_leading_delim: list((Token.t, Typ.t)) = [ ("case" ++ leading_expander, unk), - ("fun" ++ leading_expander, Arrow(unk, unk)), - ("typfun" ++ leading_expander, Forall("", unk)), + ("fun" ++ leading_expander, Arrow(unk, unk) |> Typ.fresh), + ( + "typfun" ++ leading_expander, + Forall(Var("") |> TPat.fresh, unk) |> Typ.fresh, + ), ("if" ++ leading_expander, unk), ("let" ++ leading_expander, unk), - ("test" ++ leading_expander, Prod([])), + ("test" ++ leading_expander, Prod([]) |> Typ.fresh), ("type" ++ leading_expander, unk), ]; - let of_infix_delim: list((Token.t, Typ.t)) = [ - ("|>", unk), /* */ + let of_infix_delim: list((Token.t, Typ.term)) = [ + //("|>", Unknown(Internal)), /* annoying during case rules */ (",", Prod([unk, unk])), /* NOTE: Current approach doesn't work for this, but irrelevant as 1-char */ - ("::", List(unk)), + ("::", List(unk)), /* annoying in patterns */ ("@", List(unk)), - (";", unk), + (";", Unknown(Internal)), ("&&", Bool), ("\\/", Bool), ("||", Bool), ("$==", Bool), ("==.", Bool), ("==", Bool), - ("!", Bool), // maybe doesnt belong here? but blocks autocomplete of ! to != - ("!=", Bool), - ("!=.", Bool), + ("!", Bool), + //("!=", Bool), /* annoying as != is more common */ + //("!=.", Bool), /* annoying as != is more common */ ("<", Bool), (">", Bool), ("<=", Bool), @@ -72,7 +75,7 @@ module Typ = { fun | InfoExp({mode, _}) | InfoPat({mode, _}) => Mode.ty_of(mode) - | _ => Unknown(Internal); + | _ => Unknown(Internal) |> Typ.fresh; let filter_by = ( @@ -194,7 +197,10 @@ let suggest_form = (ty_map, delims_of_sort, ci: Info.t): list(Suggestion.t) => { }; let suggest_operator: Info.t => list(Suggestion.t) = - suggest_form(Typ.of_infix_delim, Delims.infix); + suggest_form( + List.map(((a, b)) => (a, IdTagged.fresh(b)), Typ.of_infix_delim), + Delims.infix, + ); let suggest_operand: Info.t => list(Suggestion.t) = suggest_form(Typ.of_const_mono_delim, Delims.const_mono); diff --git a/src/haz3lcore/assistant/Suggestion.re b/src/haz3lcore/assistant/Suggestion.re index b97f92cfc0..2f416a80f4 100644 --- a/src/haz3lcore/assistant/Suggestion.re +++ b/src/haz3lcore/assistant/Suggestion.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; /* TyDi: Type-Directed Next-Token Suggestions diff --git a/src/haz3lcore/assistant/TyDi.re b/src/haz3lcore/assistant/TyDi.re index 0832e76075..1118fc115f 100644 --- a/src/haz3lcore/assistant/TyDi.re +++ b/src/haz3lcore/assistant/TyDi.re @@ -67,17 +67,6 @@ let suffix_of = (candidate: Token.t, current: Token.t): option(Token.t) => { candidate_suffix == "" ? None : Some(candidate_suffix); }; -/* PERF: This is quite expensive */ -let z_to_ci = (~settings: CoreSettings.t, ~ctx: Ctx.t, z: Zipper.t) => { - let map = - z - |> MakeTerm.from_zip_for_sem - |> fst - |> Interface.Statics.mk_map_ctx(settings, ctx); - let* index = Indicated.index(z); - Id.Map.find_opt(index, map); -}; - /* Returns the text content of the suggestion buffer */ let get_buffer = (z: Zipper.t): option(Token.t) => switch (z.selection.mode, z.selection.content) { @@ -87,9 +76,10 @@ let get_buffer = (z: Zipper.t): option(Token.t) => }; /* Populates the suggestion buffer with a type-directed suggestion */ -let set_buffer = (~settings, ~ctx: Ctx.t, z: Zipper.t): option(Zipper.t) => { +let set_buffer = (~info_map: Statics.Map.t, z: Zipper.t): option(Zipper.t) => { let* tok_to_left = token_to_left(z); - let* ci = z_to_ci(~settings, ~ctx, z); + let* index = Indicated.index(z); + let* ci = Id.Map.find_opt(index, info_map); let suggestions = suggest(ci, z); let suggestions = suggestions diff --git a/src/haz3lcore/dune b/src/haz3lcore/dune index 2bfd69309d..77e2ca3fe1 100644 --- a/src/haz3lcore/dune +++ b/src/haz3lcore/dune @@ -2,15 +2,20 @@ (library (name haz3lcore) - (libraries util re sexplib unionFind uuidm) - (js_of_ocaml - (flags - (:include js-of-ocaml-flags-%{profile}))) + (libraries util sexplib unionFind uuidm virtual_dom yojson core) + (js_of_ocaml) (preprocess - (pps ppx_let ppx_sexp_conv ppx_deriving.show ppx_yojson_conv))) + (pps + ppx_yojson_conv + js_of_ocaml-ppx + ppx_let + ppx_sexp_conv + ppx_deriving.show))) -(rule - (write-file js-of-ocaml-flags-dev "(:standard --debuginfo --noinline)")) - -(rule - (write-file js-of-ocaml-flags-release "(:standard)")) +(env + (dev + (js_of_ocaml + (flags :standard --debuginfo --noinline --dynlink --linkall --sourcemap))) + (release + (js_of_ocaml + (flags :standard)))) diff --git a/src/haz3lcore/dynamics/Builtins.re b/src/haz3lcore/dynamics/Builtins.re index 385f6e0317..4479989fd5 100644 --- a/src/haz3lcore/dynamics/Builtins.re +++ b/src/haz3lcore/dynamics/Builtins.re @@ -9,111 +9,153 @@ open DHExp; See the existing ones for reference. */ -[@deriving (show({with_path: false}), sexp, yojson)] +[@deriving (show({with_path: false}), sexp)] type builtin = | Const(Typ.t, DHExp.t) | Fn(Typ.t, Typ.t, DHExp.t => DHExp.t); -[@deriving (show({with_path: false}), sexp, yojson)] +[@deriving (show({with_path: false}), sexp)] type t = VarMap.t_(builtin); -[@deriving (show({with_path: false}), sexp, yojson)] +[@deriving (show({with_path: false}), sexp)] type forms = VarMap.t_(DHExp.t => DHExp.t); type result = Result.t(DHExp.t, EvaluatorError.t); -let const = (name: Var.t, typ: Typ.t, v: DHExp.t, builtins: t): t => - VarMap.extend(builtins, (name, Const(typ, v))); +let const = (name: Var.t, typ: Typ.term, v: DHExp.t, builtins: t): t => + VarMap.extend(builtins, (name, Const(typ |> Typ.fresh, v))); let fn = - (name: Var.t, t1: Typ.t, t2: Typ.t, impl: DHExp.t => DHExp.t, builtins: t) + ( + name: Var.t, + t1: Typ.term, + t2: Typ.term, + impl: DHExp.t => DHExp.t, + builtins: t, + ) : t => - VarMap.extend(builtins, (name, Fn(t1, t2, impl))); + VarMap.extend( + builtins, + (name, Fn(t1 |> Typ.fresh, t2 |> Typ.fresh, impl)), + ); module Pervasives = { module Impls = { /* constants */ - let infinity = DHExp.FloatLit(Float.infinity); - let neg_infinity = DHExp.FloatLit(Float.neg_infinity); - let nan = DHExp.FloatLit(Float.nan); - let epsilon_float = DHExp.FloatLit(epsilon_float); - let pi = DHExp.FloatLit(Float.pi); - let max_int = DHExp.IntLit(Int.max_int); - let min_int = DHExp.IntLit(Int.min_int); - - let unary = (f: DHExp.t => result, r: DHExp.t) => - switch (f(r)) { + let infinity = DHExp.Float(Float.infinity) |> fresh; + let neg_infinity = DHExp.Float(Float.neg_infinity) |> fresh; + let nan = DHExp.Float(Float.nan) |> fresh; + let epsilon_float = DHExp.Float(epsilon_float) |> fresh; + let pi = DHExp.Float(Float.pi) |> fresh; + let max_int = DHExp.Int(Int.max_int) |> fresh; + let min_int = DHExp.Int(Int.min_int) |> fresh; + + let unary = (f: DHExp.t => result, d: DHExp.t) => { + switch (f(d)) { | Ok(r') => r' | Error(e) => EvaluatorError.Exception(e) |> raise }; + }; + + let binary = (f: (DHExp.t, DHExp.t) => result, d: DHExp.t) => { + switch (term_of(d)) { + | Tuple([d1, d2]) => + switch (f(d1, d2)) { + | Ok(r) => r + | Error(e) => EvaluatorError.Exception(e) |> raise + } + | _ => raise(EvaluatorError.Exception(InvalidBoxedTuple(d))) + }; + }; + + let ternary = (f: (DHExp.t, DHExp.t, DHExp.t) => result, d: DHExp.t) => { + switch (term_of(d)) { + | Tuple([d1, d2, d3]) => + switch (f(d1, d2, d3)) { + | Ok(r) => r + | Error(e) => EvaluatorError.Exception(e) |> raise + } + | _ => raise(EvaluatorError.Exception(InvalidBoxedTuple(d))) + }; + }; let is_finite = - unary( - fun - | FloatLit(f) => Ok(BoolLit(Float.is_finite(f))) - | d => Error(InvalidBoxedFloatLit(d)), + unary(d => + switch (term_of(d)) { + | Float(f) => Ok(fresh(Bool(Float.is_finite(f)))) + | _ => Error(InvalidBoxedFloatLit(d)) + } ); let is_infinite = - unary( - fun - | FloatLit(f) => Ok(BoolLit(Float.is_infinite(f))) - | d => Error(InvalidBoxedFloatLit(d)), + unary(d => + switch (term_of(d)) { + | Float(f) => Ok(fresh(Bool(Float.is_infinite(f)))) + | _ => Error(InvalidBoxedFloatLit(d)) + } ); let is_nan = - unary( - fun - | FloatLit(f) => Ok(BoolLit(Float.is_nan(f))) - | d => Error(InvalidBoxedFloatLit(d)), + unary(d => + switch (term_of(d)) { + | Float(f) => Ok(fresh(Bool(Float.is_nan(f)))) + | _ => Error(InvalidBoxedFloatLit(d)) + } ); let string_of_int = - unary( - fun - | IntLit(n) => Ok(StringLit(string_of_int(n))) - | d => Error(InvalidBoxedIntLit(d)), + unary(d => + switch (term_of(d)) { + | Int(n) => Ok(fresh(String(string_of_int(n)))) + | _ => Error(InvalidBoxedIntLit(d)) + } ); let string_of_float = - unary( - fun - | FloatLit(f) => Ok(StringLit(string_of_float(f))) - | d => Error(InvalidBoxedFloatLit(d)), + unary(d => + switch (term_of(d)) { + | Float(f) => Ok(fresh(String(string_of_float(f)))) + | _ => Error(InvalidBoxedFloatLit(d)) + } ); let string_of_bool = - unary( - fun - | BoolLit(b) => Ok(StringLit(string_of_bool(b))) - | d => Error(InvalidBoxedBoolLit(d)), + unary(d => + switch (term_of(d)) { + | Bool(b) => Ok(fresh(String(string_of_bool(b)))) + | _ => Error(InvalidBoxedBoolLit(d)) + } ); let int_of_float = - unary( - fun - | FloatLit(f) => Ok(IntLit(int_of_float(f))) - | d => Error(InvalidBoxedFloatLit(d)), + unary(d => + switch (term_of(d)) { + | Float(f) => Ok(fresh(Int(int_of_float(f)))) + | _ => Error(InvalidBoxedFloatLit(d)) + } ); let float_of_int = - unary( - fun - | IntLit(n) => Ok(FloatLit(float_of_int(n))) - | d => Error(InvalidBoxedIntLit(d)), + unary(d => + switch (term_of(d)) { + | Int(n) => Ok(fresh(Float(float_of_int(n)))) + | _ => Error(InvalidBoxedIntLit(d)) + } ); let abs = - unary( - fun - | IntLit(n) => Ok(IntLit(abs(n))) - | d => Error(InvalidBoxedIntLit(d)), + unary(d => + switch (term_of(d)) { + | Int(n) => Ok(fresh(Int(abs(n)))) + | _ => Error(InvalidBoxedIntLit(d)) + } ); let float_op = fn => - unary( - fun - | FloatLit(f) => Ok(FloatLit(fn(f))) - | d => Error(InvalidBoxedFloatLit(d)), + unary(d => + switch (term_of(d)) { + | Float(f) => Ok(fresh(Float(fn(f)))) + | _ => Error(InvalidBoxedFloatLit(d)) + } ); let abs_float = float_op(abs_float); @@ -132,84 +174,110 @@ module Pervasives = { let of_string = (convert: string => option('a), wrap: 'a => DHExp.t, name: string) => - unary( - fun - | StringLit(s) as d => + unary(d => + switch (term_of(d)) { + | String(s) => switch (convert(s)) { | Some(n) => Ok(wrap(n)) | None => - let d' = DHExp.Ap(DHExp.BuiltinFun(name), d); - Ok(InvalidOperation(d', InvalidOfString)); + let d' = DHExp.BuiltinFun(name) |> DHExp.fresh; + let d' = DHExp.Ap(Forward, d', d) |> DHExp.fresh; + let d' = DynamicErrorHole(d', InvalidOfString) |> DHExp.fresh; + Ok(d'); } - | d => Error(InvalidBoxedStringLit(d)), + | _ => Error(InvalidBoxedStringLit(d)) + } ); - let int_of_string = of_string(int_of_string_opt, n => IntLit(n)); - let float_of_string = of_string(float_of_string_opt, f => FloatLit(f)); - let bool_of_string = of_string(bool_of_string_opt, b => BoolLit(b)); + let int_of_string = + of_string(int_of_string_opt, n => Int(n) |> DHExp.fresh); + let float_of_string = + of_string(float_of_string_opt, f => Float(f) |> DHExp.fresh); + let bool_of_string = + of_string(bool_of_string_opt, b => Bool(b) |> DHExp.fresh); let int_mod = (name, d1) => - switch (d1) { - | Tuple([IntLit(n), IntLit(m)]) => - switch (m) { - | 0 => - InvalidOperation( - DHExp.Ap(DHExp.BuiltinFun(name), d1), - DivideByZero, - ) - | _ => IntLit(n mod m) - } - | d1 => raise(EvaluatorError.Exception(InvalidBoxedTuple(d1))) - }; + binary( + (d1, d2) => + switch (term_of(d1), term_of(d2)) { + | (Int(_), Int(0)) => + Ok( + fresh( + DynamicErrorHole( + DHExp.Ap(Forward, DHExp.BuiltinFun(name) |> fresh, d1) + |> fresh, + DivideByZero, + ), + ), + ) + | (Int(n), Int(m)) => Ok(Int(n mod m) |> fresh) + | (Int(_), _) => + raise(EvaluatorError.Exception(InvalidBoxedIntLit(d2))) + | (_, _) => + raise(EvaluatorError.Exception(InvalidBoxedIntLit(d1))) + }, + d1, + ); let string_length = - unary( - fun - | StringLit(s) => Ok(IntLit(String.length(s))) - | d => Error(InvalidBoxedStringLit(d)), + unary(d => + switch (term_of(d)) { + | String(s) => Ok(Int(String.length(s)) |> fresh) + | _ => Error(InvalidBoxedStringLit(d)) + } ); let string_compare = - unary( - fun - | Tuple([StringLit(s1), StringLit(s2)]) => - Ok(IntLit(String.compare(s1, s2))) - | d => Error(InvalidBoxedTuple(d)), + binary((d1, d2) => + switch (term_of(d1), term_of(d2)) { + | (String(s1), String(s2)) => + Ok(Int(String.compare(s1, s2)) |> fresh) + | (String(_), _) => Error(InvalidBoxedStringLit(d2)) + | (_, _) => Error(InvalidBoxedStringLit(d1)) + } ); let string_trim = - unary( - fun - | StringLit(s) => Ok(StringLit(String.trim(s))) - | d => Error(InvalidBoxedStringLit(d)), + unary(d => + switch (term_of(d)) { + | String(s) => Ok(String(String.trim(s)) |> fresh) + | _ => Error(InvalidBoxedStringLit(d)) + } ); let string_of: DHExp.t => option(string) = - fun - | StringLit(s) => Some(s) - | _ => None; + d => + switch (term_of(d)) { + | String(s) => Some(s) + | _ => None + }; let string_concat = - unary( - fun - | Tuple([StringLit(s1), ListLit(_, _, _, xs)]) => + binary((d1, d2) => + switch (term_of(d1), term_of(d2)) { + | (String(s1), ListLit(xs)) => switch (xs |> List.map(string_of) |> Util.OptUtil.sequence) { | None => Error(InvalidBoxedStringLit(List.hd(xs))) - | Some(xs) => Ok(StringLit(String.concat(s1, xs))) + | Some(xs) => Ok(String(String.concat(s1, xs)) |> fresh) } - | d => Error(InvalidBoxedTuple(d)), + | (String(_), _) => Error(InvalidBoxedListLit(d2)) + | (_, _) => Error(InvalidBoxedStringLit(d1)) + } ); - let string_sub = name => - unary( - fun - | Tuple([StringLit(s), IntLit(idx), IntLit(len)]) as d => - try(Ok(StringLit(String.sub(s, idx, len)))) { + let string_sub = _ => + ternary((d1, d2, d3) => + switch (term_of(d1), term_of(d2), term_of(d3)) { + | (String(s), Int(idx), Int(len)) => + try(Ok(String(String.sub(s, idx, len)) |> fresh)) { | _ => - let d' = DHExp.Ap(DHExp.BuiltinFun(name), d); - Ok(InvalidOperation(d', IndexOutOfBounds)); + // TODO: make it clear that the problem could be with d3 too + Ok(DynamicErrorHole(d2, IndexOutOfBounds) |> fresh) } - | d => Error(InvalidBoxedTuple(d)), + | (String(_), Int(_), _) => Error(InvalidBoxedIntLit(d3)) + | (String(_), _, _) => Error(InvalidBoxedIntLit(d2)) + | (_, _, _) => Error(InvalidBoxedIntLit(d1)) + } ); }; @@ -253,37 +321,50 @@ module Pervasives = { |> fn("asin", Float, Float, asin) |> fn("acos", Float, Float, acos) |> fn("atan", Float, Float, atan) - |> fn("mod", Prod([Int, Int]), Int, int_mod("mod")) + |> fn( + "mod", + Prod([Int |> Typ.fresh, Int |> Typ.fresh]), + Int, + int_mod("mod"), + ) |> fn("string_length", String, Int, string_length) - |> fn("string_compare", Prod([String, String]), Int, string_compare) + |> fn( + "string_compare", + Prod([String |> Typ.fresh, String |> Typ.fresh]), + Int, + string_compare, + ) |> fn("string_trim", String, String, string_trim) |> fn( "string_concat", - Prod([String, List(String)]), + Prod([String |> Typ.fresh, List(String |> Typ.fresh) |> Typ.fresh]), String, string_concat, ) |> fn( "string_sub", - Prod([String, Int, Int]), + Prod([String |> Typ.fresh, Int |> Typ.fresh, Int |> Typ.fresh]), String, string_sub("string_sub"), ); }; let ctx_init: Ctx.t = { - let meta_cons_map = ConstructorMap.of_list([("$e", None), ("$v", None)]); + let meta_cons_map: ConstructorMap.t(Typ.t) = [ + Variant("$e", [Id.mk()], None), + Variant("$v", [Id.mk()], None), + ]; let meta = Ctx.TVarEntry({ name: "$Meta", id: Id.invalid, - kind: Kind.Singleton(Sum(meta_cons_map)), + kind: Ctx.Singleton(Sum(meta_cons_map) |> Typ.fresh), }); List.map( fun | (name, Const(typ, _)) => Ctx.VarEntry({name, typ, id: Id.invalid}) | (name, Fn(t1, t2, _)) => - Ctx.VarEntry({name, typ: Arrow(t1, t2), id: Id.invalid}), + Ctx.VarEntry({name, typ: Arrow(t1, t2) |> Typ.fresh, id: Id.invalid}), Pervasives.builtins, ) |> Ctx.extend(_, meta) @@ -303,7 +384,8 @@ let env_init: Environment.t = env => fun | (name, Const(_, d)) => Environment.extend(env, (name, d)) - | (name, Fn(_)) => Environment.extend(env, (name, BuiltinFun(name))), + | (name, Fn(_)) => + Environment.extend(env, (name, BuiltinFun(name) |> fresh)), Environment.empty, Pervasives.builtins, ); diff --git a/src/haz3lcore/dynamics/Casts.re b/src/haz3lcore/dynamics/Casts.re new file mode 100644 index 0000000000..b9087f1f8f --- /dev/null +++ b/src/haz3lcore/dynamics/Casts.re @@ -0,0 +1,252 @@ +open Util; + +/* The cast calculus is based off the POPL 2019 paper: + https://arxiv.org/pdf/1805.00155.pdf */ + +/* GROUND TYPES */ + +/* You can think of a ground type as a typet that tells you what the root of the + type expression is, but nothing more. For example: Int, [?], ? -> ?, ... are + ground types and [Int], ? -> Float are not. + + The most important property of ground types is: + If two types are ground types, + and the two types are consistent, + then they are equal. + + Make sure this holds for your new feature!! + + e.g. [?] and [?] are equal, but [?] and [Int] are not (because [Int] is not + ground, even though [Int] and [?] are consistent). + + */ + +[@deriving sexp] +type ground_cases = + | Hole + | Ground + | NotGroundOrHole(Typ.t) /* the argument is the corresponding ground type */; + +let grounded_Arrow = + NotGroundOrHole( + Arrow(Unknown(Internal) |> Typ.temp, Unknown(Internal) |> Typ.temp) + |> Typ.temp, + ); +let grounded_Type = + NotGroundOrHole( + Type(EmptyHole |> TPat.fresh, Unknown(Internal) |> Typ.temp) |> Typ.temp, + ); +let grounded_Forall = + NotGroundOrHole( + Forall(EmptyHole |> Pat.fresh, Unknown(Internal) |> Typ.temp) |> Typ.temp, + ); +let grounded_Equals = + NotGroundOrHole( + Equals(EmptyHole |> Exp.fresh, EmptyHole |> Exp.fresh) |> Typ.temp, + ); +let grounded_Prod = length => + NotGroundOrHole( + Prod(ListUtil.replicate(length, Typ.Unknown(Internal) |> Typ.temp)) + |> Typ.temp, + ); +let grounded_Sum: unit => Typ.sum_map = + () => [BadEntry(Typ.temp(Unknown(Internal)))]; +let grounded_List = + NotGroundOrHole(List(Unknown(Internal) |> Typ.temp) |> Typ.temp); + +let grounded_Module = (ctx: Ctx.t) => + NotGroundOrHole( + Typ.Module({ + inner_ctx: + List.map( + fun + | Ctx.VarEntry(var_entry) => + Ctx.VarEntry({...var_entry, typ: Unknown(Internal) |> Typ.temp}) + | Ctx.ConstructorEntry(var_entry) => + Ctx.ConstructorEntry({ + ...var_entry, + typ: Unknown(Internal) |> Typ.temp, + }) + | Ctx.TVarEntry(tvar_entry) => Ctx.TVarEntry(tvar_entry), + ctx, + ), + incomplete: false, + }), + ); + +let rec ground_cases_of = (ty: Typ.t): ground_cases => { + let is_hole: Typ.t => bool = + fun + | {term: Typ.Unknown(_), _} => true + | _ => false; + switch (Typ.term_of(ty)) { + | Unknown(_) => Hole + | Bool + | Int + | Float + | String + | Var(_) + | Rec(_) + | Type(_, {term: Unknown(_), _}) + | Arrow({term: Unknown(_), _}, {term: Unknown(_), _}) + | List({term: Unknown(_), _}) => Ground + | Parens(ty) => ground_cases_of(ty) + | Prod(tys) => + if (List.for_all( + fun + | ({term: Typ.Unknown(_), _}: Typ.t) => true + | _ => false, + tys, + )) { + Ground; + } else { + tys |> List.length |> grounded_Prod; + } + | Sum(sm) => + sm |> ConstructorMap.is_ground(is_hole) + ? Ground : NotGroundOrHole(Sum(grounded_Sum()) |> Typ.temp) + | Arrow(_, _) => grounded_Arrow + | Type(_) => grounded_Type + | Forall(_) => grounded_Forall + | Equals(_) => grounded_Equals + | List(_) => grounded_List + | Ap(_) => failwith("type application in dynamics") + | Module({inner_ctx: [], incomplete: true}) => Ground + | Module(_) => NotGroundOrHole(Module({inner_ctx: [], incomplete: true})) + | Member(_, ty) => ground_cases_of(ty) + }; +}; + +/* CAST CALCULUS */ + +/* Rules are taken from figure 12 of https://arxiv.org/pdf/1805.00155.pdf */ + +/* gives a transition step that can be taken by the cast calculus here if applicable. */ +let rec transition = (~recursive=false, d: DHExp.t): option(DHExp.t) => { + switch (DHExp.term_of(d)) { + | Cast(d1, t1, t2) => + let d1 = + if (recursive) { + d1 |> transition(~recursive) |> Option.value(~default=d1); + } else { + d1; + }; + switch (ground_cases_of(t1), ground_cases_of(t2)) { + | (Hole, Hole) + | (Ground, Ground) => + /* if two types are ground and consistent, then they are eq */ + Some(d1) // Rule ITCastId + + | (Ground, Hole) => + /* can't remove the cast or do anything else here, so we're done */ + None + + | (Hole, Ground) => + switch (DHExp.term_of(d1)) { + | Cast(d2, t3, {term: Unknown(_), _}) => + /* by canonical forms, d1' must be of the form d ?> */ + if (Typ.eq(t3, t2)) { + Some + (d2); // Rule ITCastSucceed + } else { + Some + (FailedCast(d2, t3, t2) |> DHExp.fresh); // Rule ITCastFail + } + | _ => None + } + + | (Hole, NotGroundOrHole(t2_grounded)) => + /* ITExpand rule */ + print_endline("called with d= " ++ DHExp.show(d)); + let inner_cast = Cast(d1, t1, t2_grounded) |> DHExp.fresh; + print_endline("inner_cast: " ++ DHExp.show(inner_cast)); + // HACK: we need to check the inner cast here + let inner_cast = + switch (transition(~recursive, inner_cast)) { + | Some(d1) => d1 + | None => inner_cast + }; + Some(DHExp.Cast(inner_cast, t2_grounded, t2) |> DHExp.fresh); + + | (NotGroundOrHole(t1_grounded), Hole) => + /* ITGround rule */ + Some( + DHExp.Cast(Cast(d1, t1, t1_grounded) |> DHExp.fresh, t1_grounded, t2) + |> DHExp.fresh, + ) + + | (Ground, NotGroundOrHole(_)) => + switch (DHExp.term_of(d1)) { + | Cast(d2, t3, _) => + if (Typ.eq(t3, t2)) { + Some(d2); + } else { + None; + } + | _ => None + } + | (NotGroundOrHole(_), Ground) => + /* can't do anything when casting between diseq, non-hole types */ + None + + | (NotGroundOrHole(_), NotGroundOrHole(_)) => + /* they might be eq in this case, so remove cast if so */ + if (Typ.eq(t1, t2)) { + Some + (d1); // Rule ITCastId + } else { + None; + } + }; + | _ => None + }; +}; + +let rec transition_multiple = (d: DHExp.t): DHExp.t => { + switch (transition(~recursive=true, d)) { + | Some(d'') => transition_multiple(d'') + | None => d + }; +}; + +// So that we don't have to regenerate its id +let hole = EmptyHole |> DHExp.fresh; + +// Hacky way to do transition_multiple on patterns by transferring +// the cast to the expression and then back to the pattern. +let pattern_fixup = (p: DHPat.t): DHPat.t => { + let rec unwrap_casts = (p: DHPat.t): (DHPat.t, DHExp.t) => { + switch (DHPat.term_of(p)) { + | Cast(p1, t1, t2) => + let (p1, d1) = unwrap_casts(p1); + ( + p1, + {term: DHExp.Cast(d1, t1, t2), copied: p.copied, ids: p.ids} + |> transition_multiple, + ); + | _ => (p, hole) + }; + }; + let rec rewrap_casts = ((p: DHPat.t, d: DHExp.t)): DHPat.t => { + switch (DHExp.term_of(d)) { + | EmptyHole => p + | Cast(d1, t1, t2) => + let p1 = rewrap_casts((p, d1)); + {term: DHPat.Cast(p1, t1, t2), copied: d.copied, ids: d.ids}; + | FailedCast(d1, t1, t2) => + let p1 = rewrap_casts((p, d1)); + { + term: + DHPat.Cast( + DHPat.Cast(p1, t1, Typ.fresh(Unknown(Internal))) |> DHPat.fresh, + Typ.fresh(Unknown(Internal)), + t2, + ), + copied: d.copied, + ids: d.ids, + }; + | _ => failwith("unexpected term in rewrap_casts") + }; + }; + p |> unwrap_casts |> rewrap_casts; +}; diff --git a/src/haz3lcore/dynamics/ClosureEnvironment.re b/src/haz3lcore/dynamics/ClosureEnvironment.re index 95342373fa..52b9ab4d51 100644 --- a/src/haz3lcore/dynamics/ClosureEnvironment.re +++ b/src/haz3lcore/dynamics/ClosureEnvironment.re @@ -1 +1 @@ -include DH.ClosureEnvironment; +include TermBase.ClosureEnvironment; diff --git a/src/haz3lcore/dynamics/ClosureEnvironment.rei b/src/haz3lcore/dynamics/ClosureEnvironment.rei index ccb9ea0284..d2cffb2310 100644 --- a/src/haz3lcore/dynamics/ClosureEnvironment.rei +++ b/src/haz3lcore/dynamics/ClosureEnvironment.rei @@ -1,3 +1,3 @@ include - (module type of DH.ClosureEnvironment) with - type t = DH.ClosureEnvironment.t; + (module type of TermBase.ClosureEnvironment) with + type t = TermBase.ClosureEnvironment.t; diff --git a/src/haz3lcore/dynamics/Constraint.re b/src/haz3lcore/dynamics/Constraint.re index a56f435e55..3fcff59bea 100644 --- a/src/haz3lcore/dynamics/Constraint.re +++ b/src/haz3lcore/dynamics/Constraint.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type t = @@ -129,9 +129,11 @@ let of_ap = (ctx, mode, ctr: option(Constructor.t), arg: t, syn_ty): t => }; switch (ty) { | Some(ty) => - switch (Typ.weak_head_normalize(ctx, ty)) { + switch (Typ.weak_head_normalize(ctx, ty) |> Typ.term_of) { + | Rec(_, {term: Sum(map), _}) | Sum(map) => - let num_variants = ConstructorMap.cardinal(map); + let num_variants = + ConstructorMap.get_constructors(map) |> List.length; switch (ConstructorMap.nth(map, name)) { | Some(nth) => arg |> ctr_of_nth_variant(num_variants, nth) | None => Falsity diff --git a/src/haz3lcore/dynamics/DH.re b/src/haz3lcore/dynamics/DH.re index af7cc1259a..deb94b3555 100644 --- a/src/haz3lcore/dynamics/DH.re +++ b/src/haz3lcore/dynamics/DH.re @@ -1,658 +1,587 @@ -open Sexplib.Std; - -[@deriving (show({with_path: false}), sexp, yojson)] -type if_consistency = - | ConsistentIf - | InconsistentIf; - -module rec DHExp: { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - | EmptyHole(MetaVar.t, HoleInstanceId.t) - | NonEmptyHole(ErrStatus.HoleReason.t, MetaVar.t, HoleInstanceId.t, t) - | FreeVar(MetaVar.t, HoleInstanceId.t, Var.t) - | InvalidText(MetaVar.t, HoleInstanceId.t, string) - | InconsistentBranches(MetaVar.t, HoleInstanceId.t, case) - | Closure([@opaque] ClosureEnvironment.t, t) - | Filter(DHFilter.t, t) - | BoundVar(Var.t) - | Sequence(t, t) - | Let(DHPat.t, t, t) - | Module(DHPat.t, t, t) - | Dot(t, t) - | FixF(Var.t, Typ.t, t) - | Fun(DHPat.t, Typ.t, t, option(Var.t)) - | TypFun(Term.UTPat.t, t, option(Var.t)) - | TypAp(t, Typ.t) - | Ap(t, t) - | ApBuiltin(string, t) - | BuiltinFun(string) - | Test(KeywordID.t, t) - | BoolLit(bool) - | IntLit(int) - | FloatLit(float) - | StringLit(string) - | BinBoolOp(TermBase.UExp.op_bin_bool, t, t) - | BinIntOp(TermBase.UExp.op_bin_int, t, t) - | BinFloatOp(TermBase.UExp.op_bin_float, t, t) - | BinStringOp(TermBase.UExp.op_bin_string, t, t) - | ListLit(MetaVar.t, MetaVarInst.t, Typ.t, list(t)) - | Cons(t, t) - | ListConcat(t, t) - | Tuple(list(t)) - | Prj(t, int) - | Constructor(string) - | ConsistentCase(case) - | Cast(t, Typ.t, Typ.t) - | FailedCast(t, Typ.t, Typ.t) - | InvalidOperation(t, InvalidOperationError.t) - | ModuleVal(ClosureEnvironment.t, list(Var.t)) - | IfThenElse(if_consistency, t, t, t) // use bool tag to track if branches are consistent - and case = - | Case(t, list(rule), int) - and rule = - | Rule(DHPat.t, t); - - let constructor_string: t => string; - - let mk_tuple: list(t) => t; - - let cast: (t, Typ.t, Typ.t) => t; - - let apply_casts: (t, list((Typ.t, Typ.t))) => t; - let strip_casts: t => t; - - let fast_equal: (t, t) => bool; - - let assign_name_if_none: (t, option(Var.t)) => t; - let ty_subst: (Typ.t, TypVar.t, t) => t; -} = { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - /* Hole types */ - | EmptyHole(MetaVar.t, HoleInstanceId.t) - | NonEmptyHole(ErrStatus.HoleReason.t, MetaVar.t, HoleInstanceId.t, t) - | FreeVar(MetaVar.t, HoleInstanceId.t, Var.t) - | InvalidText(MetaVar.t, HoleInstanceId.t, string) - | InconsistentBranches(MetaVar.t, HoleInstanceId.t, case) - /* Generalized closures */ - | Closure(ClosureEnvironment.t, t) - | Filter(DHFilter.t, t) - /* Other expressions forms */ - | BoundVar(Var.t) - | Sequence(t, t) - | Let(DHPat.t, t, t) - | Module(DHPat.t, t, t) - | Dot(t, t) - | FixF(Var.t, Typ.t, t) - | Fun(DHPat.t, Typ.t, t, option(Var.t)) - | TypFun(Term.UTPat.t, t, option(Var.t)) - | TypAp(t, Typ.t) - | Ap(t, t) - | ApBuiltin(string, t) - | BuiltinFun(string) - | Test(KeywordID.t, t) - | BoolLit(bool) - | IntLit(int) - | FloatLit(float) - | StringLit(string) - | BinBoolOp(TermBase.UExp.op_bin_bool, t, t) - | BinIntOp(TermBase.UExp.op_bin_int, t, t) - | BinFloatOp(TermBase.UExp.op_bin_float, t, t) - | BinStringOp(TermBase.UExp.op_bin_string, t, t) - | ListLit(MetaVar.t, MetaVarInst.t, Typ.t, list(t)) - | Cons(t, t) - | ListConcat(t, t) - | Tuple(list(t)) - | Prj(t, int) - | Constructor(string) - | ConsistentCase(case) - | Cast(t, Typ.t, Typ.t) - | FailedCast(t, Typ.t, Typ.t) - | InvalidOperation(t, InvalidOperationError.t) - | ModuleVal(ClosureEnvironment.t, list(Var.t)) - | IfThenElse(if_consistency, t, t, t) - and case = - | Case(t, list(rule), int) - and rule = - | Rule(DHPat.t, t); - - let constructor_string = (d: t): string => - switch (d) { - | EmptyHole(_, _) => "EmptyHole" - | NonEmptyHole(_, _, _, _) => "NonEmptyHole" - | FreeVar(_, _, _) => "FreeVar" - | InvalidText(_) => "InvalidText" - | BoundVar(_) => "BoundVar" - | Sequence(_, _) => "Sequence" - | Filter(_, _) => "Filter" - | Let(_, _, _) => "Let" - | Module(_, _, _) => "Module" - | Dot(_, _) => "DotMember" - | FixF(_, _, _) => "FixF" - | Fun(_, _, _, _) => "Fun" - | TypFun(_) => "TypFun" - | Closure(_, _) => "Closure" - | Ap(_, _) => "Ap" - | TypAp(_) => "TypAp" - | ApBuiltin(_, _) => "ApBuiltin" - | BuiltinFun(_) => "BuiltinFun" - | Test(_) => "Test" - | BoolLit(_) => "BoolLit" - | IntLit(_) => "IntLit" - | FloatLit(_) => "FloatLit" - | StringLit(_) => "StringLit" - | BinBoolOp(_, _, _) => "BinBoolOp" - | BinIntOp(_, _, _) => "BinIntOp" - | BinFloatOp(_, _, _) => "BinFloatOp" - | BinStringOp(_, _, _) => "BinStringOp" - | ListLit(_) => "ListLit" - | Cons(_, _) => "Cons" - | ListConcat(_, _) => "ListConcat" - | Tuple(_) => "Tuple" - | Prj(_) => "Prj" - | Constructor(_) => "Constructor" - | ConsistentCase(_) => "ConsistentCase" - | InconsistentBranches(_, _, _) => "InconsistentBranches" - | Cast(_, _, _) => "Cast" - | FailedCast(_, _, _) => "FailedCast" - | InvalidOperation(_) => "InvalidOperation" - | ModuleVal(_) => "ModuleVal" - | IfThenElse(_, _, _, _) => "IfThenElse" - }; - - let mk_tuple: list(t) => t = - fun - | [] - | [_] => failwith("mk_tuple: expected at least 2 elements") - | xs => Tuple(xs); - - let cast = (d: t, t1: Typ.t, t2: Typ.t): t => - if (Typ.eq(t1, t2) || t2 == Unknown(SynSwitch)) { - d; - } else { - Cast(d, t1, t2); - }; - - let apply_casts = (d: t, casts: list((Typ.t, Typ.t))): t => - List.fold_left((d, (ty1, ty2)) => cast(d, ty1, ty2), d, casts); - - let rec strip_casts = - fun - | Closure(ei, d) => Closure(ei, strip_casts(d)) - | Cast(d, _, _) => strip_casts(d) - | FailedCast(d, _, _) => strip_casts(d) - | Tuple(ds) => Tuple(ds |> List.map(strip_casts)) - | Prj(d, n) => Prj(strip_casts(d), n) - | Cons(d1, d2) => Cons(strip_casts(d1), strip_casts(d2)) - | ListConcat(d1, d2) => ListConcat(strip_casts(d1), strip_casts(d2)) - | ListLit(a, b, c, ds) => ListLit(a, b, c, List.map(strip_casts, ds)) - | NonEmptyHole(err, u, i, d) => NonEmptyHole(err, u, i, strip_casts(d)) - | Sequence(a, b) => Sequence(strip_casts(a), strip_casts(b)) - | Filter(f, b) => Filter(DHFilter.strip_casts(f), strip_casts(b)) - | Let(dp, b, c) => Let(dp, strip_casts(b), strip_casts(c)) - | Module(dp, b, c) => Module(dp, strip_casts(b), strip_casts(c)) - | Dot(a, b) => Dot(strip_casts(a), strip_casts(b)) - | FixF(a, b, c) => FixF(a, b, strip_casts(c)) - | Fun(a, b, c, d) => Fun(a, b, strip_casts(c), d) - | TypFun(a, b, c) => TypFun(a, strip_casts(b), c) - | Ap(a, b) => Ap(strip_casts(a), strip_casts(b)) - | TypAp(a, b) => TypAp(strip_casts(a), b) - | Test(id, a) => Test(id, strip_casts(a)) - | ApBuiltin(fn, args) => ApBuiltin(fn, strip_casts(args)) - | BuiltinFun(fn) => BuiltinFun(fn) - | BinBoolOp(a, b, c) => BinBoolOp(a, strip_casts(b), strip_casts(c)) - | BinIntOp(a, b, c) => BinIntOp(a, strip_casts(b), strip_casts(c)) - | BinFloatOp(a, b, c) => BinFloatOp(a, strip_casts(b), strip_casts(c)) - | BinStringOp(a, b, c) => - BinStringOp(a, strip_casts(b), strip_casts(c)) - | ConsistentCase(Case(a, rs, b)) => - ConsistentCase( - Case(strip_casts(a), List.map(strip_casts_rule, rs), b), - ) - | InconsistentBranches(u, i, Case(scrut, rules, n)) => - InconsistentBranches( - u, - i, - Case(strip_casts(scrut), List.map(strip_casts_rule, rules), n), - ) - | EmptyHole(_) as d - | FreeVar(_) as d - | InvalidText(_) as d - | BoundVar(_) as d - | BoolLit(_) as d - | IntLit(_) as d - | FloatLit(_) as d - | StringLit(_) as d - | Constructor(_) as d - | ModuleVal(_) as d - | InvalidOperation(_) as d => d - | IfThenElse(consistent, c, d1, d2) => - IfThenElse( - consistent, - strip_casts(c), - strip_casts(d1), - strip_casts(d2), - ) - and strip_casts_rule = (Rule(a, d)) => Rule(a, strip_casts(d)); - - let rec fast_equal = (d1: t, d2: t): bool => { - switch (d1, d2) { - /* Primitive forms: regular structural equality */ - | (BoundVar(_), _) - /* TODO: Not sure if this is right... */ - | (BoolLit(_), _) - | (IntLit(_), _) - | (FloatLit(_), _) - | (Constructor(_), _) => d1 == d2 - | (StringLit(s1), StringLit(s2)) => String.equal(s1, s2) - | (StringLit(_), _) => false - - /* Non-hole forms: recurse */ - | (Test(id1, d1), Test(id2, d2)) => id1 == id2 && fast_equal(d1, d2) - | (Sequence(d11, d21), Sequence(d12, d22)) => - fast_equal(d11, d12) && fast_equal(d21, d22) - | (Filter(f1, d1), Filter(f2, d2)) => - DHFilter.fast_equal(f1, f2) && fast_equal(d1, d2) - | (Let(dp1, d11, d21), Let(dp2, d12, d22)) => - dp1 == dp2 && fast_equal(d11, d12) && fast_equal(d21, d22) - | (Module(dp1, d11, d21), Module(dp2, d12, d22)) => - dp1 == dp2 && fast_equal(d11, d12) && fast_equal(d21, d22) - | (Dot(d11, d21), Dot(d12, d22)) => - fast_equal(d11, d12) && fast_equal(d21, d22) - | (FixF(f1, ty1, d1), FixF(f2, ty2, d2)) => - f1 == f2 && ty1 == ty2 && fast_equal(d1, d2) - | (Fun(dp1, ty1, d1, s1), Fun(dp2, ty2, d2, s2)) => - dp1 == dp2 && ty1 == ty2 && fast_equal(d1, d2) && s1 == s2 - | (TypFun(_tpat1, d1, s1), TypFun(_tpat2, d2, s2)) => - _tpat1 == _tpat2 && fast_equal(d1, d2) && s1 == s2 - | (TypAp(d1, ty1), TypAp(d2, ty2)) => fast_equal(d1, d2) && ty1 == ty2 - | (Ap(d11, d21), Ap(d12, d22)) - | (Cons(d11, d21), Cons(d12, d22)) => - fast_equal(d11, d12) && fast_equal(d21, d22) - | (ListConcat(d11, d21), ListConcat(d12, d22)) => - fast_equal(d11, d12) && fast_equal(d21, d22) - | (Tuple(ds1), Tuple(ds2)) => - List.length(ds1) == List.length(ds2) - && List.for_all2(fast_equal, ds1, ds2) - | (Prj(d1, n), Prj(d2, m)) => n == m && fast_equal(d1, d2) - | (ApBuiltin(f1, d1), ApBuiltin(f2, d2)) => f1 == f2 && d1 == d2 - | (BuiltinFun(f1), BuiltinFun(f2)) => f1 == f2 - | (ListLit(_, _, _, ds1), ListLit(_, _, _, ds2)) => - List.length(ds1) == List.length(ds2) - && List.for_all2(fast_equal, ds1, ds2) - | (BinBoolOp(op1, d11, d21), BinBoolOp(op2, d12, d22)) => - op1 == op2 && fast_equal(d11, d12) && fast_equal(d21, d22) - | (BinIntOp(op1, d11, d21), BinIntOp(op2, d12, d22)) => - op1 == op2 && fast_equal(d11, d12) && fast_equal(d21, d22) - | (BinFloatOp(op1, d11, d21), BinFloatOp(op2, d12, d22)) => - op1 == op2 && fast_equal(d11, d12) && fast_equal(d21, d22) - | (BinStringOp(op1, d11, d21), BinStringOp(op2, d12, d22)) => - op1 == op2 && fast_equal(d11, d12) && fast_equal(d21, d22) - | (Cast(d1, ty11, ty21), Cast(d2, ty12, ty22)) - | (FailedCast(d1, ty11, ty21), FailedCast(d2, ty12, ty22)) => - fast_equal(d1, d2) && ty11 == ty12 && ty21 == ty22 - | (InvalidOperation(d1, reason1), InvalidOperation(d2, reason2)) => - fast_equal(d1, d2) && reason1 == reason2 - | (ConsistentCase(case1), ConsistentCase(case2)) => - fast_equal_case(case1, case2) - | (ModuleVal(mv1, names1), ModuleVal(mv2, names2)) => - mv1 == mv2 && names1 == names2 - | (IfThenElse(c1, d11, d12, d13), IfThenElse(c2, d21, d22, d23)) => - c1 == c2 - && fast_equal(d11, d21) - && fast_equal(d12, d22) - && fast_equal(d13, d23) - /* We can group these all into a `_ => false` clause; separating - these so that we get exhaustiveness checking. */ - | (Sequence(_), _) - | (Filter(_), _) - | (Let(_), _) - | (Module(_), _) - | (Dot(_), _) - | (FixF(_), _) - | (Fun(_), _) - | (TypFun(_), _) - | (Test(_), _) - | (Ap(_), _) - | (TypAp(_), _) - | (ApBuiltin(_), _) - | (BuiltinFun(_), _) - | (Cons(_), _) - | (ListConcat(_), _) - | (ListLit(_), _) - | (Tuple(_), _) - | (Prj(_), _) - | (BinBoolOp(_), _) - | (BinIntOp(_), _) - | (BinFloatOp(_), _) - | (BinStringOp(_), _) - | (Cast(_), _) - | (FailedCast(_), _) - | (InvalidOperation(_), _) - | (ModuleVal(_), _) - | (IfThenElse(_), _) - | (ConsistentCase(_), _) => false - - /* Hole forms: when checking environments, only check that - environment ID's are equal, don't check structural equality. - - (This resolves a performance issue with many nested holes.) */ - | (EmptyHole(u1, i1), EmptyHole(u2, i2)) => u1 == u2 && i1 == i2 - | (NonEmptyHole(reason1, u1, i1, d1), NonEmptyHole(reason2, u2, i2, d2)) => - reason1 == reason2 && u1 == u2 && i1 == i2 && fast_equal(d1, d2) - | (FreeVar(u1, i1, x1), FreeVar(u2, i2, x2)) => - u1 == u2 && i1 == i2 && x1 == x2 - | (InvalidText(u1, i1, text1), InvalidText(u2, i2, text2)) => - u1 == u2 && i1 == i2 && text1 == text2 - | (Closure(sigma1, d1), Closure(sigma2, d2)) => - ClosureEnvironment.id_equal(sigma1, sigma2) && fast_equal(d1, d2) - | ( - InconsistentBranches(u1, i1, case1), - InconsistentBranches(u2, i2, case2), - ) => - u1 == u2 && i1 == i2 && fast_equal_case(case1, case2) - | (EmptyHole(_), _) - | (NonEmptyHole(_), _) - | (FreeVar(_), _) - | (InvalidText(_), _) - | (Closure(_), _) - | (InconsistentBranches(_), _) => false - }; - } - and fast_equal_case = (Case(d1, rules1, i1), Case(d2, rules2, i2)) => { - fast_equal(d1, d2) - && List.length(rules1) == List.length(rules2) - && List.for_all2( - (Rule(dp1, d1), Rule(dp2, d2)) => - dp1 == dp2 && fast_equal(d1, d2), - rules1, - rules2, - ) - && i1 == i2; - }; - - let assign_name_if_none = (t, name) => - switch (t) { - | Fun(arg, ty, body, None) => Fun(arg, ty, body, name) - | TypFun(utpat, body, None) => TypFun(utpat, body, name) - | _ => t - }; - - let rec ty_subst = (s: Typ.t, x: TypVar.t, exp: DHExp.t): t => { - let re = e2 => ty_subst(s, x, e2); - let t_re = ty => Typ.subst(s, x, ty); - switch (exp) { - | Cast(t, t1, t2) => Cast(re(t), t_re(t1), t_re(t2)) - | FixF(arg, ty, body) => FixF(arg, t_re(ty), re(body)) - | Fun(arg, ty, body, var) => Fun(arg, t_re(ty), re(body), var) - | TypAp(tfun, ty) => TypAp(re(tfun), t_re(ty)) - | ListLit(mv, mvi, t, lst) => - ListLit(mv, mvi, t_re(t), List.map(re, lst)) - | TypFun(utpat, body, var) => - switch (Term.UTPat.tyvar_of_utpat(utpat)) { - | Some(x') when x == x' => exp - | _ => - /* Note that we do not have to worry about capture avoidance, since s will always be closed. */ - TypFun(utpat, re(body), var) - } - | NonEmptyHole(errstat, mv, hid, t) => - NonEmptyHole(errstat, mv, hid, re(t)) - | Test(id, t) => Test(id, re(t)) - | InconsistentBranches(mv, hid, case) => - InconsistentBranches(mv, hid, ty_subst_case(s, x, case)) - | Closure(ce, t) => Closure(ce, re(t)) - | Sequence(t1, t2) => Sequence(re(t1), re(t2)) - | Let(dhpat, t1, t2) => Let(dhpat, re(t1), re(t2)) - | Module(dhpat, t1, t2) => Module(dhpat, re(t1), re(t2)) - | Dot(t1, t2) => Dot(re(t1), re(t2)) - | Ap(t1, t2) => Ap(re(t1), re(t2)) - | ApBuiltin(s, args) => ApBuiltin(s, re(args)) - | BinBoolOp(op, t1, t2) => BinBoolOp(op, re(t1), re(t2)) - | BinIntOp(op, t1, t2) => BinIntOp(op, re(t1), re(t2)) - | BinFloatOp(op, t1, t2) => BinFloatOp(op, re(t1), re(t2)) - | BinStringOp(op, t1, t2) => BinStringOp(op, re(t1), re(t2)) - | Cons(t1, t2) => Cons(re(t1), re(t2)) - | ListConcat(t1, t2) => ListConcat(re(t1), re(t2)) - | Tuple(args) => Tuple(List.map(re, args)) - | Prj(t, n) => Prj(re(t), n) - | ConsistentCase(case) => ConsistentCase(ty_subst_case(s, x, case)) - | InvalidOperation(t, err) => InvalidOperation(re(t), err) - | Filter(filt, exp) => Filter(DHFilter.map(re, filt), re(exp)) - | IfThenElse(consis, i, t, e) => - IfThenElse(consis, re(i), re(t), re(e)) - - | BuiltinFun(_) - | EmptyHole(_) - | FreeVar(_, _, _) - | InvalidText(_, _, _) - | Constructor(_) - | BoundVar(_) - | BoolLit(_) - | IntLit(_) - | FloatLit(_) - | StringLit(_) - | ModuleVal(_) - | FailedCast(_, _, _) => exp - }; - } - and ty_subst_case = (s, x, Case(t, rules, n)) => - Case( - ty_subst(s, x, t), - List.map( - (DHExp.Rule(dhpat, t)) => DHExp.Rule(dhpat, ty_subst(s, x, t)), - rules, - ), - n, - ); - //TODO: Inconsistent cases: need to check again for inconsistency? -} - -and Environment: { - include - (module type of VarBstMap.Ordered) with - type t_('a) = VarBstMap.Ordered.t_('a); - - [@deriving (show({with_path: false}), sexp, yojson)] - type t = t_(DHExp.t); -} = { - include VarBstMap.Ordered; - - [@deriving (show({with_path: false}), sexp, yojson)] - type t = t_(DHExp.t); -} - -and ClosureEnvironment: { - [@deriving (show({with_path: false}), sexp, yojson)] - type t; - - let wrap: (EnvironmentId.t, Environment.t) => t; - - let id_of: t => EnvironmentId.t; - let map_of: t => Environment.t; - - let to_list: t => list((Var.t, DHExp.t)); - - let of_environment: Environment.t => t; - - let id_equal: (t, t) => bool; - - let empty: t; - let is_empty: t => bool; - let length: t => int; - - let lookup: (t, Var.t) => option(DHExp.t); - let contains: (t, Var.t) => bool; - let update: (Environment.t => Environment.t, t) => t; - let update_keep_id: (Environment.t => Environment.t, t) => t; - let extend: (t, (Var.t, DHExp.t)) => t; - let extend_keep_id: (t, (Var.t, DHExp.t)) => t; - let union: (t, t) => t; - let union_keep_id: (t, t) => t; - let map: (((Var.t, DHExp.t)) => DHExp.t, t) => t; - let map_keep_id: (((Var.t, DHExp.t)) => DHExp.t, t) => t; - let filter: (((Var.t, DHExp.t)) => bool, t) => t; - let filter_keep_id: (((Var.t, DHExp.t)) => bool, t) => t; - let fold: (((Var.t, DHExp.t), 'b) => 'b, 'b, t) => 'b; - - let without_keys: (list(Var.t), t) => t; - - let placeholder: t; -} = { - module Inner: { - [@deriving (show({with_path: false}), sexp, yojson)] - type t; - - let wrap: (EnvironmentId.t, Environment.t) => t; - - let id_of: t => EnvironmentId.t; - let map_of: t => Environment.t; - } = { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = (EnvironmentId.t, Environment.t); - - let wrap = (ei, map): t => (ei, map); - - let id_of = ((ei, _)) => ei; - let map_of = ((_, map)) => map; - let (sexp_of_t, t_of_sexp) = - StructureShareSexp.structure_share_here(id_of, sexp_of_t, t_of_sexp); - }; - include Inner; - - let to_list = env => env |> map_of |> Environment.to_listo; - - let of_environment = map => { - let ei = Id.mk(); - wrap(ei, map); - }; - - /* Equals only needs to check environment id's (faster than structural equality - * checking.) */ - let id_equal = (env1, env2) => id_of(env1) == id_of(env2); - - let empty = Environment.empty |> of_environment; - - let is_empty = env => env |> map_of |> Environment.is_empty; - - let length = env => Environment.length(map_of(env)); - - let lookup = (env, x) => - env |> map_of |> (map => Environment.lookup(map, x)); - - let contains = (env, x) => - env |> map_of |> (map => Environment.contains(map, x)); - - let update = (f, env) => env |> map_of |> f |> of_environment; - - let update_keep_id = (f, env) => env |> map_of |> f |> wrap(env |> id_of); - - let extend = (env, xr) => - env |> update(map => Environment.extend(map, xr)); - - let extend_keep_id = (env, xr) => - env |> update_keep_id(map => Environment.extend(map, xr)); - - let union = (env1, env2) => - env2 |> update(map2 => Environment.union(env1 |> map_of, map2)); - - let union_keep_id = (env1, env2) => - env2 |> update_keep_id(map2 => Environment.union(env1 |> map_of, map2)); - - let map = (f, env) => env |> update(Environment.mapo(f)); - - let map_keep_id = (f, env) => env |> update_keep_id(Environment.mapo(f)); - - let filter = (f, env) => env |> update(Environment.filtero(f)); - - let filter_keep_id = (f, env) => - env |> update_keep_id(Environment.filtero(f)); - - let fold = (f, init, env) => env |> map_of |> Environment.foldo(f, init); - - let placeholder = wrap(EnvironmentId.invalid, Environment.empty); - - let without_keys = keys => update(Environment.without_keys(keys)); -} - -and Filter: { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = { - pat: DHExp.t, - act: FilterAction.t, - }; - - let mk: (DHExp.t, FilterAction.t) => t; - - let map: (DHExp.t => DHExp.t, t) => t; - - let strip_casts: t => t; - - let fast_equal: (t, t) => bool; -} = { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = { - pat: DHExp.t, - act: FilterAction.t, - }; - - let mk = (pat: DHExp.t, act: FilterAction.t): t => {pat, act}; - - let map = (f: DHExp.t => DHExp.t, filter: t): t => { - ...filter, - pat: f(filter.pat), - }; - - let fast_equal = (f1: t, f2: t): bool => { - DHExp.fast_equal(f1.pat, f2.pat) && f1.act == f2.act; - }; - - let strip_casts = (f: t): t => {...f, pat: f.pat |> DHExp.strip_casts}; -} - -and DHFilter: { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - | Filter(Filter.t) - | Residue(int, FilterAction.t); - let fast_equal: (t, t) => bool; - let strip_casts: t => t; - let map: (DHExp.t => DHExp.t, t) => t; -} = { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - | Filter(Filter.t) - | Residue(int, FilterAction.t); - let fast_equal = (f1: t, f2: t) => { - switch (f1, f2) { - | (Filter(flt1), Filter(flt2)) => Filter.fast_equal(flt1, flt2) - | (Residue(idx1, act1), Residue(idx2, act2)) => - idx1 == idx2 && act1 == act2 - | _ => false - }; - }; - let strip_casts = f => { - switch (f) { - | Filter(flt) => Filter(Filter.strip_casts(flt)) - | Residue(idx, act) => Residue(idx, act) - }; - }; - let map = (mapper, filter) => { - switch (filter) { - | Filter(flt) => Filter(Filter.map(mapper, flt)) - | Residue(idx, act) => Residue(idx, act) - }; - }; -} - -and FilterEnvironment: { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = list(Filter.t); - - let extends: (Filter.t, t) => t; -} = { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = list(Filter.t); - - let extends = (flt, env) => [flt, ...env]; -}; +// open Sexplib.Std; + // [@deriving (show({with_path: false}), sexp, yojson)] + // type if_consistency = + // | ConsistentIf + // | InconsistentIf; + // module rec DHExp: { + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t = + // | EmptyHole(MetaVar.t, HoleInstanceId.t) + // | NonEmptyHole(ErrStatus.HoleReason.t, MetaVar.t, HoleInstanceId.t, t) + // | FreeVar(MetaVar.t, HoleInstanceId.t, Var.t) + // | InvalidText(MetaVar.t, HoleInstanceId.t, string) + // | InconsistentBranches(MetaVar.t, HoleInstanceId.t, case) + // | Closure([@opaque] ClosureEnvironment.t, t) + // | Filter(DHFilter.t, t) + // | BoundVar(Var.t) + // | Sequence(t, t) + // | Let(DHPat.t, t, t) + // | Module(DHPat.t, t, t) + // | Dot(t, t) + // | FixF(Var.t, Typ.t, t) + // | Fun(DHPat.t, Typ.t, t, option(Var.t)) + // | TypFun(Term.UTPat.t, t, option(Var.t)) + // | TypAp(t, Typ.t) + // | Ap(t, t) + // | ApBuiltin(string, t) + // | BuiltinFun(string) + // | Test(KeywordID.t, t) + // | BoolLit(bool) + // | IntLit(int) + // | FloatLit(float) + // | StringLit(string) + // | BinBoolOp(TermBase.UExp.op_bin_bool, t, t) + // | BinIntOp(TermBase.UExp.op_bin_int, t, t) + // | BinFloatOp(TermBase.UExp.op_bin_float, t, t) + // | BinStringOp(TermBase.UExp.op_bin_string, t, t) + // | ListLit(MetaVar.t, MetaVarInst.t, Typ.t, list(t)) + // | Cons(t, t) + // | ListConcat(t, t) + // | Tuple(list(t)) + // | Prj(t, int) + // | Constructor(string) + // | ConsistentCase(case) + // | Cast(t, Typ.t, Typ.t) + // | FailedCast(t, Typ.t, Typ.t) + // | InvalidOperation(t, InvalidOperationError.t) + // | ModuleVal(ClosureEnvironment.t, list(Var.t)) + // | IfThenElse(if_consistency, t, t, t) // use bool tag to track if branches are consistent + // and case = + // | Case(t, list(rule), int) + // and rule = + // | Rule(DHPat.t, t); + // let constructor_string: t => string; + // let mk_tuple: list(t) => t; + // let cast: (t, Typ.t, Typ.t) => t; + // let apply_casts: (t, list((Typ.t, Typ.t))) => t; + // let strip_casts: t => t; + // let fast_equal: (t, t) => bool; + // let assign_name_if_none: (t, option(Var.t)) => t; + // let ty_subst: (Typ.t, TypVar.t, t) => t; + // } = { + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t = + // /* Hole types */ + // | EmptyHole(MetaVar.t, HoleInstanceId.t) + // | NonEmptyHole(ErrStatus.HoleReason.t, MetaVar.t, HoleInstanceId.t, t) + // | FreeVar(MetaVar.t, HoleInstanceId.t, Var.t) + // | InvalidText(MetaVar.t, HoleInstanceId.t, string) + // | InconsistentBranches(MetaVar.t, HoleInstanceId.t, case) + // /* Generalized closures */ + // | Closure(ClosureEnvironment.t, t) + // | Filter(DHFilter.t, t) + // /* Other expressions forms */ + // | BoundVar(Var.t) + // | Sequence(t, t) + // | Let(DHPat.t, t, t) + // | Module(DHPat.t, t, t) + // | Dot(t, t) + // | FixF(Var.t, Typ.t, t) + // | Fun(DHPat.t, Typ.t, t, option(Var.t)) + // | TypFun(Term.UTPat.t, t, option(Var.t)) + // | TypAp(t, Typ.t) + // | Ap(t, t) + // | ApBuiltin(string, t) + // | BuiltinFun(string) + // | Test(KeywordID.t, t) + // | BoolLit(bool) + // | IntLit(int) + // | FloatLit(float) + // | StringLit(string) + // | BinBoolOp(TermBase.UExp.op_bin_bool, t, t) + // | BinIntOp(TermBase.UExp.op_bin_int, t, t) + // | BinFloatOp(TermBase.UExp.op_bin_float, t, t) + // | BinStringOp(TermBase.UExp.op_bin_string, t, t) + // | ListLit(MetaVar.t, MetaVarInst.t, Typ.t, list(t)) + // | Cons(t, t) + // | ListConcat(t, t) + // | Tuple(list(t)) + // | Prj(t, int) + // | Constructor(string) + // | ConsistentCase(case) + // | Cast(t, Typ.t, Typ.t) + // | FailedCast(t, Typ.t, Typ.t) + // | InvalidOperation(t, InvalidOperationError.t) + // | ModuleVal(ClosureEnvironment.t, list(Var.t)) + // | IfThenElse(if_consistency, t, t, t) + // and case = + // | Case(t, list(rule), int) + // and rule = + // | Rule(DHPat.t, t); + // let constructor_string = (d: t): string => + // switch (d) { + // | EmptyHole(_, _) => "EmptyHole" + // | NonEmptyHole(_, _, _, _) => "NonEmptyHole" + // | FreeVar(_, _, _) => "FreeVar" + // | InvalidText(_) => "InvalidText" + // | BoundVar(_) => "BoundVar" + // | Sequence(_, _) => "Sequence" + // | Filter(_, _) => "Filter" + // | Let(_, _, _) => "Let" + // | Module(_, _, _) => "Module" + // | Dot(_, _) => "DotMember" + // | FixF(_, _, _) => "FixF" + // | Fun(_, _, _, _) => "Fun" + // | TypFun(_) => "TypFun" + // | Closure(_, _) => "Closure" + // | Ap(_, _) => "Ap" + // | TypAp(_) => "TypAp" + // | ApBuiltin(_, _) => "ApBuiltin" + // | BuiltinFun(_) => "BuiltinFun" + // | Test(_) => "Test" + // | BoolLit(_) => "BoolLit" + // | IntLit(_) => "IntLit" + // | FloatLit(_) => "FloatLit" + // | StringLit(_) => "StringLit" + // | BinBoolOp(_, _, _) => "BinBoolOp" + // | BinIntOp(_, _, _) => "BinIntOp" + // | BinFloatOp(_, _, _) => "BinFloatOp" + // | BinStringOp(_, _, _) => "BinStringOp" + // | ListLit(_) => "ListLit" + // | Cons(_, _) => "Cons" + // | ListConcat(_, _) => "ListConcat" + // | Tuple(_) => "Tuple" + // | Prj(_) => "Prj" + // | Constructor(_) => "Constructor" + // | ConsistentCase(_) => "ConsistentCase" + // | InconsistentBranches(_, _, _) => "InconsistentBranches" + // | Cast(_, _, _) => "Cast" + // | FailedCast(_, _, _) => "FailedCast" + // | InvalidOperation(_) => "InvalidOperation" + // | ModuleVal(_) => "ModuleVal" + // | IfThenElse(_, _, _, _) => "IfThenElse" + // }; + // let mk_tuple: list(t) => t = + // fun + // | [] + // | [_] => failwith("mk_tuple: expected at least 2 elements") + // | xs => Tuple(xs); + // let cast = (d: t, t1: Typ.t, t2: Typ.t): t => + // if (Typ.eq(t1, t2) || t2 == Unknown(SynSwitch)) { + // d; + // } else { + // Cast(d, t1, t2); + // }; + // let apply_casts = (d: t, casts: list((Typ.t, Typ.t))): t => + // List.fold_left((d, (ty1, ty2)) => cast(d, ty1, ty2), d, casts); + // let rec strip_casts = + // fun + // | Closure(ei, d) => Closure(ei, strip_casts(d)) + // | Cast(d, _, _) => strip_casts(d) + // | FailedCast(d, _, _) => strip_casts(d) + // | Tuple(ds) => Tuple(ds |> List.map(strip_casts)) + // | Prj(d, n) => Prj(strip_casts(d), n) + // | Cons(d1, d2) => Cons(strip_casts(d1), strip_casts(d2)) + // | ListConcat(d1, d2) => ListConcat(strip_casts(d1), strip_casts(d2)) + // | ListLit(a, b, c, ds) => ListLit(a, b, c, List.map(strip_casts, ds)) + // | NonEmptyHole(err, u, i, d) => NonEmptyHole(err, u, i, strip_casts(d)) + // | Sequence(a, b) => Sequence(strip_casts(a), strip_casts(b)) + // | Filter(f, b) => Filter(DHFilter.strip_casts(f), strip_casts(b)) + // | Let(dp, b, c) => Let(dp, strip_casts(b), strip_casts(c)) + // | Module(dp, b, c) => Module(dp, strip_casts(b), strip_casts(c)) + // | Dot(a, b) => Dot(strip_casts(a), strip_casts(b)) + // | FixF(a, b, c) => FixF(a, b, strip_casts(c)) + // | Fun(a, b, c, d) => Fun(a, b, strip_casts(c), d) + // | TypFun(a, b, c) => TypFun(a, strip_casts(b), c) + // | Ap(a, b) => Ap(strip_casts(a), strip_casts(b)) + // | TypAp(a, b) => TypAp(strip_casts(a), b) + // | Test(id, a) => Test(id, strip_casts(a)) + // | ApBuiltin(fn, args) => ApBuiltin(fn, strip_casts(args)) + // | BuiltinFun(fn) => BuiltinFun(fn) + // | BinBoolOp(a, b, c) => BinBoolOp(a, strip_casts(b), strip_casts(c)) + // | BinIntOp(a, b, c) => BinIntOp(a, strip_casts(b), strip_casts(c)) + // | BinFloatOp(a, b, c) => BinFloatOp(a, strip_casts(b), strip_casts(c)) + // | BinStringOp(a, b, c) => + // BinStringOp(a, strip_casts(b), strip_casts(c)) + // | ConsistentCase(Case(a, rs, b)) => + // ConsistentCase( + // Case(strip_casts(a), List.map(strip_casts_rule, rs), b), + // ) + // | InconsistentBranches(u, i, Case(scrut, rules, n)) => + // InconsistentBranches( + // u, + // i, + // Case(strip_casts(scrut), List.map(strip_casts_rule, rules), n), + // ) + // | EmptyHole(_) as d + // | FreeVar(_) as d + // | InvalidText(_) as d + // | BoundVar(_) as d + // | BoolLit(_) as d + // | IntLit(_) as d + // | FloatLit(_) as d + // | StringLit(_) as d + // | Constructor(_) as d + // | ModuleVal(_) as d + // | InvalidOperation(_) as d => d + // | IfThenElse(consistent, c, d1, d2) => + // IfThenElse( + // consistent, + // strip_casts(c), + // strip_casts(d1), + // strip_casts(d2), + // ) + // and strip_casts_rule = (Rule(a, d)) => Rule(a, strip_casts(d)); + // let rec fast_equal = (d1: t, d2: t): bool => { + // switch (d1, d2) { + // /* Primitive forms: regular structural equality */ + // | (BoundVar(_), _) + // /* TODO: Not sure if this is right... */ + // | (BoolLit(_), _) + // | (IntLit(_), _) + // | (FloatLit(_), _) + // | (Constructor(_), _) => d1 == d2 + // | (StringLit(s1), StringLit(s2)) => String.equal(s1, s2) + // | (StringLit(_), _) => false + // /* Non-hole forms: recurse */ + // | (Test(id1, d1), Test(id2, d2)) => id1 == id2 && fast_equal(d1, d2) + // | (Sequence(d11, d21), Sequence(d12, d22)) => + // fast_equal(d11, d12) && fast_equal(d21, d22) + // | (Filter(f1, d1), Filter(f2, d2)) => + // DHFilter.fast_equal(f1, f2) && fast_equal(d1, d2) + // | (Let(dp1, d11, d21), Let(dp2, d12, d22)) => + // dp1 == dp2 && fast_equal(d11, d12) && fast_equal(d21, d22) + // | (Module(dp1, d11, d21), Module(dp2, d12, d22)) => + // dp1 == dp2 && fast_equal(d11, d12) && fast_equal(d21, d22) + // | (Dot(d11, d21), Dot(d12, d22)) => + // fast_equal(d11, d12) && fast_equal(d21, d22) + // | (FixF(f1, ty1, d1), FixF(f2, ty2, d2)) => + // f1 == f2 && ty1 == ty2 && fast_equal(d1, d2) + // | (Fun(dp1, ty1, d1, s1), Fun(dp2, ty2, d2, s2)) => + // dp1 == dp2 && ty1 == ty2 && fast_equal(d1, d2) && s1 == s2 + // | (TypFun(_tpat1, d1, s1), TypFun(_tpat2, d2, s2)) => + // _tpat1 == _tpat2 && fast_equal(d1, d2) && s1 == s2 + // | (TypAp(d1, ty1), TypAp(d2, ty2)) => fast_equal(d1, d2) && ty1 == ty2 + // | (Ap(d11, d21), Ap(d12, d22)) + // | (Cons(d11, d21), Cons(d12, d22)) => + // fast_equal(d11, d12) && fast_equal(d21, d22) + // | (ListConcat(d11, d21), ListConcat(d12, d22)) => + // fast_equal(d11, d12) && fast_equal(d21, d22) + // | (Tuple(ds1), Tuple(ds2)) => + // List.length(ds1) == List.length(ds2) + // && List.for_all2(fast_equal, ds1, ds2) + // | (Prj(d1, n), Prj(d2, m)) => n == m && fast_equal(d1, d2) + // | (ApBuiltin(f1, d1), ApBuiltin(f2, d2)) => f1 == f2 && d1 == d2 + // | (BuiltinFun(f1), BuiltinFun(f2)) => f1 == f2 + // | (ListLit(_, _, _, ds1), ListLit(_, _, _, ds2)) => + // List.length(ds1) == List.length(ds2) + // && List.for_all2(fast_equal, ds1, ds2) + // | (BinBoolOp(op1, d11, d21), BinBoolOp(op2, d12, d22)) => + // op1 == op2 && fast_equal(d11, d12) && fast_equal(d21, d22) + // | (BinIntOp(op1, d11, d21), BinIntOp(op2, d12, d22)) => + // op1 == op2 && fast_equal(d11, d12) && fast_equal(d21, d22) + // | (BinFloatOp(op1, d11, d21), BinFloatOp(op2, d12, d22)) => + // op1 == op2 && fast_equal(d11, d12) && fast_equal(d21, d22) + // | (BinStringOp(op1, d11, d21), BinStringOp(op2, d12, d22)) => + // op1 == op2 && fast_equal(d11, d12) && fast_equal(d21, d22) + // | (Cast(d1, ty11, ty21), Cast(d2, ty12, ty22)) + // | (FailedCast(d1, ty11, ty21), FailedCast(d2, ty12, ty22)) => + // fast_equal(d1, d2) && ty11 == ty12 && ty21 == ty22 + // | (InvalidOperation(d1, reason1), InvalidOperation(d2, reason2)) => + // fast_equal(d1, d2) && reason1 == reason2 + // | (ConsistentCase(case1), ConsistentCase(case2)) => + // fast_equal_case(case1, case2) + // | (ModuleVal(mv1, names1), ModuleVal(mv2, names2)) => + // mv1 == mv2 && names1 == names2 + // | (IfThenElse(c1, d11, d12, d13), IfThenElse(c2, d21, d22, d23)) => + // c1 == c2 + // && fast_equal(d11, d21) + // && fast_equal(d12, d22) + // && fast_equal(d13, d23) + // /* We can group these all into a `_ => false` clause; separating + // these so that we get exhaustiveness checking. */ + // | (Sequence(_), _) + // | (Filter(_), _) + // | (Let(_), _) + // | (Module(_), _) + // | (Dot(_), _) + // | (FixF(_), _) + // | (Fun(_), _) + // | (TypFun(_), _) + // | (Test(_), _) + // | (Ap(_), _) + // | (TypAp(_), _) + // | (ApBuiltin(_), _) + // | (BuiltinFun(_), _) + // | (Cons(_), _) + // | (ListConcat(_), _) + // | (ListLit(_), _) + // | (Tuple(_), _) + // | (Prj(_), _) + // | (BinBoolOp(_), _) + // | (BinIntOp(_), _) + // | (BinFloatOp(_), _) + // | (BinStringOp(_), _) + // | (Cast(_), _) + // | (FailedCast(_), _) + // | (InvalidOperation(_), _) + // | (ModuleVal(_), _) + // | (IfThenElse(_), _) + // | (ConsistentCase(_), _) => false + // /* Hole forms: when checking environments, only check that + // environment ID's are equal, don't check structural equality. + // (This resolves a performance issue with many nested holes.) */ + // | (EmptyHole(u1, i1), EmptyHole(u2, i2)) => u1 == u2 && i1 == i2 + // | (NonEmptyHole(reason1, u1, i1, d1), NonEmptyHole(reason2, u2, i2, d2)) => + // reason1 == reason2 && u1 == u2 && i1 == i2 && fast_equal(d1, d2) + // | (FreeVar(u1, i1, x1), FreeVar(u2, i2, x2)) => + // u1 == u2 && i1 == i2 && x1 == x2 + // | (InvalidText(u1, i1, text1), InvalidText(u2, i2, text2)) => + // u1 == u2 && i1 == i2 && text1 == text2 + // | (Closure(sigma1, d1), Closure(sigma2, d2)) => + // ClosureEnvironment.id_equal(sigma1, sigma2) && fast_equal(d1, d2) + // | ( + // InconsistentBranches(u1, i1, case1), + // InconsistentBranches(u2, i2, case2), + // ) => + // u1 == u2 && i1 == i2 && fast_equal_case(case1, case2) + // | (EmptyHole(_), _) + // | (NonEmptyHole(_), _) + // | (FreeVar(_), _) + // | (InvalidText(_), _) + // | (Closure(_), _) + // | (InconsistentBranches(_), _) => false + // }; + // } + // and fast_equal_case = (Case(d1, rules1, i1), Case(d2, rules2, i2)) => { + // fast_equal(d1, d2) + // && List.length(rules1) == List.length(rules2) + // && List.for_all2( + // (Rule(dp1, d1), Rule(dp2, d2)) => + // dp1 == dp2 && fast_equal(d1, d2), + // rules1, + // rules2, + // ) + // && i1 == i2; + // }; + // let assign_name_if_none = (t, name) => + // switch (t) { + // | Fun(arg, ty, body, None) => Fun(arg, ty, body, name) + // | TypFun(utpat, body, None) => TypFun(utpat, body, name) + // | _ => t + // }; + // let rec ty_subst = (s: Typ.t, x: TypVar.t, exp: DHExp.t): t => { + // let re = e2 => ty_subst(s, x, e2); + // let t_re = ty => Typ.subst(s, x, ty); + // switch (exp) { + // | Cast(t, t1, t2) => Cast(re(t), t_re(t1), t_re(t2)) + // | FixF(arg, ty, body) => FixF(arg, t_re(ty), re(body)) + // | Fun(arg, ty, body, var) => Fun(arg, t_re(ty), re(body), var) + // | TypAp(tfun, ty) => TypAp(re(tfun), t_re(ty)) + // | ListLit(mv, mvi, t, lst) => + // ListLit(mv, mvi, t_re(t), List.map(re, lst)) + // | TypFun(utpat, body, var) => + // switch (Term.UTPat.tyvar_of_utpat(utpat)) { + // | Some(x') when x == x' => exp + // | _ => + // /* Note that we do not have to worry about capture avoidance, since s will always be closed. */ + // TypFun(utpat, re(body), var) + // } + // | NonEmptyHole(errstat, mv, hid, t) => + // NonEmptyHole(errstat, mv, hid, re(t)) + // | Test(id, t) => Test(id, re(t)) + // | InconsistentBranches(mv, hid, case) => + // InconsistentBranches(mv, hid, ty_subst_case(s, x, case)) + // | Closure(ce, t) => Closure(ce, re(t)) + // | Sequence(t1, t2) => Sequence(re(t1), re(t2)) + // | Let(dhpat, t1, t2) => Let(dhpat, re(t1), re(t2)) + // | Module(dhpat, t1, t2) => Module(dhpat, re(t1), re(t2)) + // | Dot(t1, t2) => Dot(re(t1), re(t2)) + // | Ap(t1, t2) => Ap(re(t1), re(t2)) + // | ApBuiltin(s, args) => ApBuiltin(s, re(args)) + // | BinBoolOp(op, t1, t2) => BinBoolOp(op, re(t1), re(t2)) + // | BinIntOp(op, t1, t2) => BinIntOp(op, re(t1), re(t2)) + // | BinFloatOp(op, t1, t2) => BinFloatOp(op, re(t1), re(t2)) + // | BinStringOp(op, t1, t2) => BinStringOp(op, re(t1), re(t2)) + // | Cons(t1, t2) => Cons(re(t1), re(t2)) + // | ListConcat(t1, t2) => ListConcat(re(t1), re(t2)) + // | Tuple(args) => Tuple(List.map(re, args)) + // | Prj(t, n) => Prj(re(t), n) + // | ConsistentCase(case) => ConsistentCase(ty_subst_case(s, x, case)) + // | InvalidOperation(t, err) => InvalidOperation(re(t), err) + // | Filter(filt, exp) => Filter(DHFilter.map(re, filt), re(exp)) + // | IfThenElse(consis, i, t, e) => + // IfThenElse(consis, re(i), re(t), re(e)) + // | BuiltinFun(_) + // | EmptyHole(_) + // | FreeVar(_, _, _) + // | InvalidText(_, _, _) + // | Constructor(_) + // | BoundVar(_) + // | BoolLit(_) + // | IntLit(_) + // | FloatLit(_) + // | StringLit(_) + // | ModuleVal(_) + // | FailedCast(_, _, _) => exp + // }; + // } + // and ty_subst_case = (s, x, Case(t, rules, n)) => + // Case( + // ty_subst(s, x, t), + // List.map( + // (DHExp.Rule(dhpat, t)) => DHExp.Rule(dhpat, ty_subst(s, x, t)), + // rules, + // ), + // n, + // ); + // //TODO: Inconsistent cases: need to check again for inconsistency? + // } + // and Environment: { + // include + // (module type of VarBstMap.Ordered) with + // type t_('a) = VarBstMap.Ordered.t_('a); + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t = t_(DHExp.t); + // } = { + // include VarBstMap.Ordered; + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t = t_(DHExp.t); + // } + // and ClosureEnvironment: { + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t; + // let wrap: (EnvironmentId.t, Environment.t) => t; + // let id_of: t => EnvironmentId.t; + // let map_of: t => Environment.t; + // let to_list: t => list((Var.t, DHExp.t)); + // let of_environment: Environment.t => t; + // let id_equal: (t, t) => bool; + // let empty: t; + // let is_empty: t => bool; + // let length: t => int; + // let lookup: (t, Var.t) => option(DHExp.t); + // let contains: (t, Var.t) => bool; + // let update: (Environment.t => Environment.t, t) => t; + // let update_keep_id: (Environment.t => Environment.t, t) => t; + // let extend: (t, (Var.t, DHExp.t)) => t; + // let extend_keep_id: (t, (Var.t, DHExp.t)) => t; + // let union: (t, t) => t; + // let union_keep_id: (t, t) => t; + // let map: (((Var.t, DHExp.t)) => DHExp.t, t) => t; + // let map_keep_id: (((Var.t, DHExp.t)) => DHExp.t, t) => t; + // let filter: (((Var.t, DHExp.t)) => bool, t) => t; + // let filter_keep_id: (((Var.t, DHExp.t)) => bool, t) => t; + // let fold: (((Var.t, DHExp.t), 'b) => 'b, 'b, t) => 'b; + // let without_keys: (list(Var.t), t) => t; + // let placeholder: t; + // } = { + // module Inner: { + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t; + // let wrap: (EnvironmentId.t, Environment.t) => t; + // let id_of: t => EnvironmentId.t; + // let map_of: t => Environment.t; + // } = { + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t = (EnvironmentId.t, Environment.t); + // let wrap = (ei, map): t => (ei, map); + // let id_of = ((ei, _)) => ei; + // let map_of = ((_, map)) => map; + // let (sexp_of_t, t_of_sexp) = + // StructureShareSexp.structure_share_here(id_of, sexp_of_t, t_of_sexp); + // }; + // include Inner; + // let to_list = env => env |> map_of |> Environment.to_listo; + // let of_environment = map => { + // let ei = Id.mk(); + // wrap(ei, map); + // }; + // /* Equals only needs to check environment id's (faster than structural equality + // * checking.) */ + // let id_equal = (env1, env2) => id_of(env1) == id_of(env2); + // let empty = Environment.empty |> of_environment; + // let is_empty = env => env |> map_of |> Environment.is_empty; + // let length = env => Environment.length(map_of(env)); + // let lookup = (env, x) => + // env |> map_of |> (map => Environment.lookup(map, x)); + // let contains = (env, x) => + // env |> map_of |> (map => Environment.contains(map, x)); + // let update = (f, env) => env |> map_of |> f |> of_environment; + // let update_keep_id = (f, env) => env |> map_of |> f |> wrap(env |> id_of); + // let extend = (env, xr) => + // env |> update(map => Environment.extend(map, xr)); + // let extend_keep_id = (env, xr) => + // env |> update_keep_id(map => Environment.extend(map, xr)); + // let union = (env1, env2) => + // env2 |> update(map2 => Environment.union(env1 |> map_of, map2)); + // let union_keep_id = (env1, env2) => + // env2 |> update_keep_id(map2 => Environment.union(env1 |> map_of, map2)); + // let map = (f, env) => env |> update(Environment.mapo(f)); + // let map_keep_id = (f, env) => env |> update_keep_id(Environment.mapo(f)); + // let filter = (f, env) => env |> update(Environment.filtero(f)); + // let filter_keep_id = (f, env) => + // env |> update_keep_id(Environment.filtero(f)); + // let fold = (f, init, env) => env |> map_of |> Environment.foldo(f, init); + // let placeholder = wrap(EnvironmentId.invalid, Environment.empty); + // let without_keys = keys => update(Environment.without_keys(keys)); + // } + // and Filter: { + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t = { + // pat: DHExp.t, + // act: FilterAction.t, + // }; + // let mk: (DHExp.t, FilterAction.t) => t; + // let map: (DHExp.t => DHExp.t, t) => t; + // let strip_casts: t => t; + // let fast_equal: (t, t) => bool; + // } = { + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t = { + // pat: DHExp.t, + // act: FilterAction.t, + // }; + // let mk = (pat: DHExp.t, act: FilterAction.t): t => {pat, act}; + // let map = (f: DHExp.t => DHExp.t, filter: t): t => { + // ...filter, + // pat: f(filter.pat), + // }; + // let fast_equal = (f1: t, f2: t): bool => { + // DHExp.fast_equal(f1.pat, f2.pat) && f1.act == f2.act; + // }; + // let strip_casts = (f: t): t => {...f, pat: f.pat |> DHExp.strip_casts}; + // } + // and DHFilter: { + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t = + // | Filter(Filter.t) + // | Residue(int, FilterAction.t); + // let fast_equal: (t, t) => bool; + // let strip_casts: t => t; + // let map: (DHExp.t => DHExp.t, t) => t; + // } = { + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t = + // | Filter(Filter.t) + // | Residue(int, FilterAction.t); + // let fast_equal = (f1: t, f2: t) => { + // switch (f1, f2) { + // | (Filter(flt1), Filter(flt2)) => Filter.fast_equal(flt1, flt2) + // | (Residue(idx1, act1), Residue(idx2, act2)) => + // idx1 == idx2 && act1 == act2 + // | _ => false + // }; + // }; + // let strip_casts = f => { + // switch (f) { + // | Filter(flt) => Filter(Filter.strip_casts(flt)) + // | Residue(idx, act) => Residue(idx, act) + // }; + // }; + // let map = (mapper, filter) => { + // switch (filter) { + // | Filter(flt) => Filter(Filter.map(mapper, flt)) + // | Residue(idx, act) => Residue(idx, act) + // }; + // }; + // } + // and FilterEnvironment: { + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t = list(Filter.t); + // let extends: (Filter.t, t) => t; + // } = { + // [@deriving (show({with_path: false}), sexp, yojson)] + // type t = list(Filter.t); + // let extends = (flt, env) => [flt, ...env]; + // }; diff --git a/src/haz3lcore/dynamics/DHExp.re b/src/haz3lcore/dynamics/DHExp.re index ca152a800e..f7651ba963 100644 --- a/src/haz3lcore/dynamics/DHExp.re +++ b/src/haz3lcore/dynamics/DHExp.re @@ -1 +1,153 @@ -include DH.DHExp; +/* DHExp.re + + This module is specifically for dynamic expressions. They are stored + using the same data structure as user expressions, have been modified + slightly as described in Elaborator.re. + */ + +include Exp; + +let term_of: t => term = IdTagged.term_of; +let fast_copy: (Id.t, t) => t = IdTagged.fast_copy; + +let mk = (ids, term): t => { + {ids, copied: true, term}; +}; + +// TODO: make this function emit a map of changes +let replace_all_ids = + map_term( + ~f_exp=(continue, exp) => {...exp, ids: [Id.mk()]} |> continue, + ~f_pat=(continue, exp) => {...exp, ids: [Id.mk()]} |> continue, + ~f_typ=(continue, exp) => {...exp, ids: [Id.mk()]} |> continue, + ~f_tpat=(continue, exp) => {...exp, ids: [Id.mk()]} |> continue, + ~f_rul=(continue, exp) => {...exp, ids: [Id.mk()]} |> continue, + ); + +// TODO: make this function emit a map of changes +let repair_ids = + map_term( + ~f_exp= + (continue, exp) => + if (exp.copied) { + replace_all_ids(exp); + } else { + continue(exp); + }, + _, + ); + +// Also strips static error holes - kinda like unelaboration +let rec strip_casts = + map_term( + ~f_exp= + (continue, exp) => { + switch (term_of(exp)) { + /* Leave non-casts unchanged */ + | Tuple(_) + | Cons(_) + | ListConcat(_) + | ListLit(_) + | MultiHole(_) + | Seq(_) + | Filter(_) + | Let(_) + | FixF(_) + | TyAlias(_) + | Fun(_) + | Ap(_) + | Deferral(_) + | DeferredAp(_) + | Test(_) + | BuiltinFun(_) + | UnOp(_) + | BinOp(_) + | Match(_) + | Parens(_) + | EmptyHole + | Invalid(_) + | Var(_) + | Bool(_) + | Int(_) + | Float(_) + | String(_) + | Constructor(_) + | DynamicErrorHole(_) + | Closure(_) + | TypFun(_) + | TypAp(_) + | Undefined + | If(_) => continue(exp) + /* Remove casts*/ + | FailedCast(d, _, _) + | Cast(d, _, _) => strip_casts(d) + } + }, + _, + ); + +let assign_name_if_none = (t, name) => { + let (term, rewrap) = unwrap(t); + switch (term) { + | Fun(arg, ty, body, None) => Fun(arg, ty, body, name) |> rewrap + | TypFun(utpat, body, None) => TypFun(utpat, body, name) |> rewrap + | _ => t + }; +}; + +let ty_subst = (s: Typ.t, tpat: TPat.t, exp: t): t => { + switch (TPat.tyvar_of_utpat(tpat)) { + | None => exp + | Some(x) => + Exp.map_term( + ~f_typ=(_, typ) => Typ.subst(s, tpat, typ), + ~f_exp= + (continue, exp) => + switch (term_of(exp)) { + | TypFun(utpat, _, _) => + switch (TPat.tyvar_of_utpat(utpat)) { + | Some(x') when x == x' => exp + | Some(_) + | None => continue(exp) + /* Note that we do not have to worry about capture avoidance, since s will always be closed. */ + } + | Cast(_) + | FixF(_) + | Fun(_) + | TypAp(_) + | ListLit(_) + | Test(_) + | Closure(_) + | Seq(_) + | Let(_) + | Ap(_) + | BuiltinFun(_) + | BinOp(_) + | Cons(_) + | ListConcat(_) + | Tuple(_) + | Match(_) + | DynamicErrorHole(_) + | Filter(_) + | If(_) + | EmptyHole + | Invalid(_) + | Undefined + | Constructor(_) + | Var(_) + | Bool(_) + | Int(_) + | Float(_) + | String(_) + | FailedCast(_, _, _) + | MultiHole(_) + | Deferral(_) + | TyAlias(_) + | DeferredAp(_) + | Parens(_) + | UnOp(_) => continue(exp) + }, + exp, + ) + }; +}; diff --git a/src/haz3lcore/dynamics/DHPat.re b/src/haz3lcore/dynamics/DHPat.re index fd7c821445..f9e4adbddb 100644 --- a/src/haz3lcore/dynamics/DHPat.re +++ b/src/haz3lcore/dynamics/DHPat.re @@ -1,68 +1,54 @@ -open Sexplib.Std; +include Pat; -[@deriving (show({with_path: false}), sexp, yojson)] -type t = - | EmptyHole(MetaVar.t, MetaVarInst.t) - | NonEmptyHole(ErrStatus.HoleReason.t, MetaVar.t, MetaVarInst.t, t) - | Wild - | InvalidText(MetaVar.t, MetaVarInst.t, string) - | BadConstructor(MetaVar.t, MetaVarInst.t, string) - | Var(Var.t) - | IntLit(int) - | FloatLit(float) - | BoolLit(bool) - | StringLit(string) - | ListLit(Typ.t, list(t)) - | Cons(t, t) - | Tuple(list(t)) - | Constructor(string) - | Ap(t, t); - -let mk_tuple: list(t) => t = - fun - | [] - | [_] => failwith("mk_tuple: expected at least 2 elements") - | dps => Tuple(dps); +/* A Dynamic Pattern (DHPat) is a pattern that is part of an expression + that has been type-checked. Hence why these functions take both a + pattern, dp, and an info map, m, with type information. */ /** * Whether dp contains the variable x outside of a hole. */ -let rec binds_var = (x: Var.t, dp: t): bool => - switch (dp) { - | EmptyHole(_, _) - | NonEmptyHole(_, _, _, _) - | Wild - | InvalidText(_) - | BadConstructor(_) - | IntLit(_) - | FloatLit(_) - | BoolLit(_) - | StringLit(_) - | Constructor(_) => false - | Var(y) => Var.eq(x, y) - | Tuple(dps) => dps |> List.exists(binds_var(x)) - | Cons(dp1, dp2) => binds_var(x, dp1) || binds_var(x, dp2) - | ListLit(_, d_list) => - let new_list = List.map(binds_var(x), d_list); - List.fold_left((||), false, new_list); - | Ap(_, _) => false +let rec binds_var = (m: Statics.Map.t, x: Var.t, dp: t): bool => + switch (Statics.get_pat_error_at(m, rep_id(dp))) { + | Some(_) => false + | None => + switch (dp |> term_of) { + | EmptyHole + | MultiHole(_) + | Wild + | Invalid(_) + | Int(_) + | Float(_) + | Bool(_) + | String(_) + | Constructor(_) => false + | Cast(y, _, _) + | Parens(y) => binds_var(m, x, y) + | Var(y) => Var.eq(x, y) + | Tuple(dps) => dps |> List.exists(binds_var(m, x)) + | Cons(dp1, dp2) => binds_var(m, x, dp1) || binds_var(m, x, dp2) + | ListLit(d_list) => + let new_list = List.map(binds_var(m, x), d_list); + List.fold_left((||), false, new_list); + | Ap(_, _) => false + } }; let rec bound_vars = (dp: t): list(Var.t) => - switch (dp) { - | EmptyHole(_, _) - | NonEmptyHole(_, _, _, _) + switch (dp |> term_of) { + | EmptyHole + | MultiHole(_) | Wild - | InvalidText(_) - | BadConstructor(_) - | IntLit(_) - | FloatLit(_) - | BoolLit(_) - | StringLit(_) + | Invalid(_) + | Int(_) + | Float(_) + | Bool(_) + | String(_) | Constructor(_) => [] + | Cast(y, _, _) + | Parens(y) => bound_vars(y) | Var(y) => [y] | Tuple(dps) => List.flatten(List.map(bound_vars, dps)) | Cons(dp1, dp2) => bound_vars(dp1) @ bound_vars(dp2) - | ListLit(_, dps) => List.flatten(List.map(bound_vars, dps)) + | ListLit(dps) => List.flatten(List.map(bound_vars, dps)) | Ap(_, dp1) => bound_vars(dp1) }; diff --git a/src/haz3lcore/dynamics/Delta.re b/src/haz3lcore/dynamics/Delta.re index 8a492c9c20..fee0455685 100644 --- a/src/haz3lcore/dynamics/Delta.re +++ b/src/haz3lcore/dynamics/Delta.re @@ -4,5 +4,9 @@ type hole_sort = | PatternHole; [@deriving sexp] -type t = MetaVarMap.t((hole_sort, Typ.t, VarCtx.t)); -let empty: t = (MetaVarMap.empty: t); +type val_ty = (hole_sort, Typ.t, Ctx.t); + +[@deriving sexp] +type t = Id.Map.t(val_ty); + +let empty: t = (Id.Map.empty: t); diff --git a/src/haz3lcore/dynamics/Delta.rei b/src/haz3lcore/dynamics/Delta.rei index d37de1926b..ce58db058d 100644 --- a/src/haz3lcore/dynamics/Delta.rei +++ b/src/haz3lcore/dynamics/Delta.rei @@ -4,6 +4,9 @@ type hole_sort = | PatternHole; [@deriving sexp] -type t = MetaVarMap.t((hole_sort, Typ.t, VarCtx.t)); +type val_ty = (hole_sort, Typ.t, Ctx.t); + +[@deriving sexp] +type t = Id.Map.t(val_ty); let empty: t; diff --git a/src/haz3lcore/dynamics/Elaborator.re b/src/haz3lcore/dynamics/Elaborator.re index b72067c38b..b71166dd87 100644 --- a/src/haz3lcore/dynamics/Elaborator.re +++ b/src/haz3lcore/dynamics/Elaborator.re @@ -1,5 +1,15 @@ +/* + A nice property would be that elaboration is idempotent... + */ + open Util; -open OptUtil.Syntax; + +exception MissingTypeInfo; + +module Elaboration = { + [@deriving (show({with_path: false}), sexp, yojson)] + type t = {d: DHExp.t}; +}; module ElaborationResult = { [@deriving sexp] @@ -8,531 +18,610 @@ module ElaborationResult = { | DoesNotElaborate; }; -let exp_binop_of: Term.UExp.op_bin => (Typ.t, (_, _) => DHExp.t) = - fun - | Int(op) => (Int, ((e1, e2) => BinIntOp(op, e1, e2))) - | Float(op) => (Float, ((e1, e2) => BinFloatOp(op, e1, e2))) - | Bool(op) => (Bool, ((e1, e2) => BinBoolOp(op, e1, e2))) - | String(op) => (String, ((e1, e2) => BinStringOp(op, e1, e2))); +let fresh_cast = (d: DHExp.t, t1: Typ.t, t2: Typ.t): DHExp.t => { + Typ.eq(t1, t2) + ? d + : { + let d' = + DHExp.Cast(d, t1, Typ.temp(Unknown(Internal))) + |> DHExp.fresh + |> Casts.transition_multiple; + DHExp.Cast(d', Typ.temp(Unknown(Internal)), t2) + |> DHExp.fresh + |> Casts.transition_multiple; + }; +}; -let fixed_exp_typ = (m: Statics.Map.t, e: Term.UExp.t): option(Typ.t) => - switch (Id.Map.find_opt(Term.UExp.rep_id(e), m)) { - | Some(InfoExp({ty, _})) => Some(ty) - | _ => None - }; +let fresh_pat_cast = (p: DHPat.t, t1: Typ.t, t2: Typ.t): DHPat.t => { + Typ.eq(t1, t2) + ? p + : { + Cast( + DHPat.fresh(Cast(p, t1, Typ.temp(Unknown(Internal)))) + |> Casts.pattern_fixup, + Typ.temp(Unknown(Internal)), + t2, + ) + |> DHPat.fresh + |> Casts.pattern_fixup; + }; +}; -let fixed_pat_typ = (m: Statics.Map.t, p: Term.UPat.t): option(Typ.t) => - switch (Id.Map.find_opt(Term.UPat.rep_id(p), m)) { - | Some(InfoPat({ty, _})) => Some(ty) - | _ => None - }; +let elaborated_type = (m: Statics.Map.t, uexp: UExp.t): (Typ.t, Ctx.t, 'a) => { + let (mode, self_ty, ctx, co_ctx) = + switch (Id.Map.find_opt(Exp.rep_id(uexp), m)) { + | Some(Info.InfoExp({mode, ty, ctx, co_ctx, _})) => ( + mode, + ty, + ctx, + co_ctx, + ) + | _ => raise(MissingTypeInfo) + }; + let elab_ty = + switch (mode) { + | Syn => self_ty + | SynFun => + let (ty1, ty2) = Typ.matched_arrow(ctx, self_ty); + Typ.Arrow(ty1, ty2) |> Typ.temp; + | SynTypFun => + let (tpat, ty) = Typ.matched_forall(ctx, self_ty); + let tpat = Option.value(tpat, ~default=TPat.fresh(EmptyHole)); + Typ.Forall(tpat, ty) |> Typ.temp; + // We need to remove the synswitches from this type. + | Ana(ana_ty) => Typ.match_synswitch(ana_ty, self_ty) + }; + (elab_ty |> Typ.normalize(ctx), ctx, co_ctx); +}; -let cast = (ctx: Ctx.t, mode: Mode.t, self_ty: Typ.t, d: DHExp.t) => - switch (mode) { - | Syn => d - | SynFun => - switch (self_ty) { - | Unknown(prov) => - DHExp.cast(d, Unknown(prov), Arrow(Unknown(prov), Unknown(prov))) - | Arrow(_) => d - | _ => failwith("Elaborator.wrap: SynFun non-arrow-type") - } - | SynTypFun => - switch (self_ty) { - | Unknown(prov) => - /* ? |> forall _. ? */ - DHExp.cast(d, Unknown(prov), Forall("_", Unknown(prov))) - | Forall(_) => d - | _ => failwith("Elaborator.wrap: SynTypFun non-forall-type") - } - | Ana(ana_ty) => - let ana_ty = Typ.normalize(ctx, ana_ty); - /* Forms with special ana rules get cast from their appropriate Matched types */ - switch (d) { - | ListLit(_) - | ListConcat(_) - | Cons(_) => - switch (ana_ty) { - | Unknown(prov) => DHExp.cast(d, List(Unknown(prov)), Unknown(prov)) - | _ => d - } - | Fun(_) => - /* See regression tests in Documentation/Dynamics */ - let (_, ana_out) = Typ.matched_arrow(ctx, ana_ty); - let (self_in, _) = Typ.matched_arrow(ctx, self_ty); - DHExp.cast(d, Arrow(self_in, ana_out), ana_ty); - | TypFun(_) => - switch (ana_ty) { - | Unknown(prov) => - DHExp.cast(d, Forall("grounded_forall", Unknown(prov)), ana_ty) - | _ => d - } - | Tuple(ds) => - switch (ana_ty) { - | Unknown(prov) => - let us = List.init(List.length(ds), _ => Typ.Unknown(prov)); - DHExp.cast(d, Prod(us), Unknown(prov)); - | _ => d - } - | Ap(NonEmptyHole(_, _, _, Constructor(_)), _) - | Ap(Constructor(_), _) - | TypAp(Constructor(_), _) - | Constructor(_) => - switch (ana_ty, self_ty) { - | (Unknown(prov), Rec(_, Sum(_))) - | (Unknown(prov), Sum(_)) => DHExp.cast(d, self_ty, Unknown(prov)) - | (_, Module(_)) - | (Module(_), _) => DHExp.cast(d, self_ty, ana_ty) - | _ => d +let elaborated_pat_type = (m: Statics.Map.t, upat: UPat.t): (Typ.t, Ctx.t) => { + let (mode, self_ty, ctx, prev_synswitch) = + switch (Id.Map.find_opt(UPat.rep_id(upat), m)) { + | Some(Info.InfoPat({mode, ty, ctx, prev_synswitch, _})) => ( + mode, + ty, + ctx, + prev_synswitch, + ) + | _ => raise(MissingTypeInfo) + }; + let elab_ty = + switch (mode) { + | Syn => self_ty + | SynFun => + let (ty1, ty2) = Typ.matched_arrow(ctx, self_ty); + Typ.Arrow(ty1, ty2) |> Typ.temp; + | SynTypFun => + let (tpat, ty) = Typ.matched_forall(ctx, self_ty); + let tpat = Option.value(tpat, ~default=TPat.fresh(EmptyHole)); + Typ.Forall(tpat, ty) |> Typ.temp; + | Ana(ana_ty) => + switch (prev_synswitch) { + | None => ana_ty + | Some(syn_ty) => Typ.match_synswitch(syn_ty, ana_ty) } - /* Forms with special ana rules but no particular typing requirements */ - | ConsistentCase(_) - | InconsistentBranches(_) - | IfThenElse(_) - | Sequence(_) - | Let(_) - | Module(_) - | Dot(_) - | FixF(_) => d - /* Hole-like forms: Don't cast */ - | InvalidText(_) - | FreeVar(_) - | EmptyHole(_) - | NonEmptyHole(_) => d - /* DHExp-specific forms: Don't cast */ - | Cast(_) - | Closure(_) - | Filter(_) - | FailedCast(_) - | InvalidOperation(_) => d - /* Normal cases: wrap */ - | BoundVar(_) - | ModuleVal(_) - | Ap(_) - | ApBuiltin(_) - | BuiltinFun(_) - | Prj(_) - | BoolLit(_) - | IntLit(_) - | FloatLit(_) - | StringLit(_) - | BinBoolOp(_) - | BinIntOp(_) - | BinFloatOp(_) - | BinStringOp(_) - | Test(_) - | TypAp(_) => - // TODO: check with andrew - DHExp.cast(d, self_ty, ana_ty) }; - }; + (elab_ty |> Typ.normalize(ctx), ctx); +}; -/* Handles cast insertion and non-empty-hole wrapping - for elaborated expressions */ -let wrap = (ctx: Ctx.t, u: Id.t, mode: Mode.t, self, d: DHExp.t): DHExp.t => - switch (Info.status_exp(ctx, mode, self)) { - | NotInHole(_) => - let self_ty = - switch (Self.typ_of_exp(ctx, self)) { - | Some(self_ty) => Typ.normalize(ctx, self_ty) - | None => Unknown(Internal) - }; - cast(ctx, mode, self_ty, d); - | InHole(_) => NonEmptyHole(TypeInconsistent, u, 0, d) - }; +let rec elaborate_pattern = + (m: Statics.Map.t, upat: UPat.t): (DHPat.t, Typ.t) => { + let (elaborated_type, ctx) = elaborated_pat_type(m, upat); + let cast_from = (ty, exp) => fresh_pat_cast(exp, ty, elaborated_type); + let (term, rewrap) = UPat.unwrap(upat); + let dpat = + switch (term) { + | Int(_) => upat |> cast_from(Int |> Typ.temp) + | Bool(_) => upat |> cast_from(Bool |> Typ.temp) + | Float(_) => upat |> cast_from(Float |> Typ.temp) + | String(_) => upat |> cast_from(String |> Typ.temp) + | ListLit(ps) => + let (ps, tys) = List.map(elaborate_pattern(m), ps) |> ListUtil.unzip; + let inner_type = + tys + |> Typ.join_all(~empty=Unknown(Internal) |> Typ.temp, ctx) + |> Option.value(~default=Typ.temp(Unknown(Internal))); + ps + |> List.map2((p, t) => fresh_pat_cast(p, t, inner_type), _, tys) + |> ( + ps' => + DHPat.ListLit(ps') + |> rewrap + |> cast_from(List(inner_type) |> Typ.temp) + ); + | Cons(p1, p2) => + let (p1', ty1) = elaborate_pattern(m, p1); + let (p2', ty2) = elaborate_pattern(m, p2); + let ty2_inner = Typ.matched_list(ctx, ty2); + let ty_inner = + Typ.join(~fix=false, ctx, ty1, ty2_inner) + |> Option.value(~default=Typ.temp(Unknown(Internal))); + let p1'' = fresh_pat_cast(p1', ty1, ty_inner); + let p2'' = fresh_pat_cast(p2', ty2, List(ty_inner) |> Typ.temp); + DHPat.Cons(p1'', p2'') + |> rewrap + |> cast_from(List(ty_inner) |> Typ.temp); + | Tuple(ps) => + let (ps', tys) = List.map(elaborate_pattern(m), ps) |> ListUtil.unzip; + DHPat.Tuple(ps') |> rewrap |> cast_from(Typ.Prod(tys) |> Typ.temp); + | Ap(p1, p2) => + let (p1', ty1) = elaborate_pattern(m, p1); + let (p2', ty2) = elaborate_pattern(m, p2); + let (ty1l, ty1r) = Typ.matched_arrow(ctx, ty1); + let p1'' = fresh_pat_cast(p1', ty1, Arrow(ty1l, ty1r) |> Typ.temp); + let p2'' = fresh_pat_cast(p2', ty2, ty1l); + DHPat.Ap(p1'', p2'') |> rewrap |> cast_from(ty1r); + | Invalid(_) + | EmptyHole + | MultiHole(_) + | Wild => upat |> cast_from(Typ.temp(Unknown(Internal))) + | Var(v) => + upat + |> cast_from( + Ctx.lookup_var(ctx, v) + |> Option.map((x: Ctx.var_entry) => x.typ |> Typ.normalize(ctx)) + |> Option.value(~default=Typ.temp(Unknown(Internal))), + ) + // Type annotations should already appear + | Parens(p) + | Cast(p, _, _) => + let (p', ty) = elaborate_pattern(m, p); + p' |> cast_from(ty |> Typ.normalize(ctx)); + | Constructor(c, _) => + let mode = + switch (Id.Map.find_opt(Pat.rep_id(upat), m)) { + | Some(Info.InfoPat({mode, _})) => mode + | _ => raise(MissingTypeInfo) + }; + let t = + switch (Mode.ctr_ana_typ(ctx, mode, c), Ctx.lookup_ctr(ctx, c)) { + | (Some(ana_ty), _) => ana_ty + | (_, Some({typ: syn_ty, _})) => syn_ty + | _ => Unknown(Internal) |> Typ.temp + }; + let t = t |> Typ.normalize(ctx); + Constructor(c, t) |> rewrap |> cast_from(t); + }; + (dpat, elaborated_type); +}; -let rec dhexp_of_uexp = - (m: Statics.Map.t, uexp: Term.UExp.t, in_filter: bool) - : option(DHExp.t) => { - let dhexp_of_uexp = (~in_filter=in_filter, m, uexp) => { - dhexp_of_uexp(m, uexp, in_filter); - }; - switch (Id.Map.find_opt(Term.UExp.rep_id(uexp), m)) { - | Some(InfoExp({mode, self, ctx, ancestors, co_ctx, _})) => - let err_status = Info.status_exp(ctx, mode, self); - let id = Term.UExp.rep_id(uexp); /* NOTE: using term uids for hole ids */ - let+ d: DHExp.t = - switch (uexp.term) { - | Invalid(t) => Some(DHExp.InvalidText(id, 0, t)) - | EmptyHole => Some(DHExp.EmptyHole(id, 0)) - | MultiHole(_tms) => - /* TODO: add a dhexp case and eval logic for multiholes. - Make sure new dhexp form is properly considered Indet - to avoid casting issues. */ - Some(EmptyHole(id, 0)) - | Triv => Some(Tuple([])) - | Deferral(_) => Some(DHExp.InvalidText(id, 0, "_")) - | Bool(b) => Some(BoolLit(b)) - | Int(n) => Some(IntLit(n)) - | Float(n) => Some(FloatLit(n)) - | String(s) => Some(StringLit(s)) - | ListLit(es) => - let* ds = es |> List.map(dhexp_of_uexp(m)) |> OptUtil.sequence; - let+ ty = fixed_exp_typ(m, uexp); - let ty = Typ.matched_list(ctx, ty); - DHExp.ListLit(id, 0, ty, ds); - | Fun(p, body) => - let* dp = dhpat_of_upat(m, p); - let* d1 = dhexp_of_uexp(m, body); - let+ ty = fixed_pat_typ(m, p); - DHExp.Fun(dp, ty, d1, None); - | TypFun(tpat, body) => - let+ d1 = dhexp_of_uexp(m, body); - DHExp.TypFun(tpat, d1, None); - | Tuple(es) => - let+ ds = es |> List.map(dhexp_of_uexp(m)) |> OptUtil.sequence; - DHExp.Tuple(ds); - | Cons(e1, e2) => - let* dc1 = dhexp_of_uexp(m, e1); - let+ dc2 = dhexp_of_uexp(m, e2); - DHExp.Cons(dc1, dc2); - | ListConcat(e1, e2) => - let* dc1 = dhexp_of_uexp(m, e1); - let+ dc2 = dhexp_of_uexp(m, e2); - DHExp.ListConcat(dc1, dc2); - | UnOp(Meta(Unquote), e) => - switch (e.term) { - | Var("e") when in_filter => Some(Constructor("$e")) - | Var("v") when in_filter => Some(Constructor("$v")) - | _ => Some(DHExp.EmptyHole(id, 0)) - } - | UnOp(Int(Minus), e) => - let+ dc = dhexp_of_uexp(m, e); - DHExp.BinIntOp(Minus, IntLit(0), dc); - | UnOp(Bool(Not), e) => - let+ d_scrut = dhexp_of_uexp(m, e); - let d_rules = - DHExp.[ - Rule(BoolLit(true), BoolLit(false)), - Rule(BoolLit(false), BoolLit(true)), - ]; - let d = DHExp.ConsistentCase(DHExp.Case(d_scrut, d_rules, 0)); - /* Manually construct cast (case is not otherwise cast) */ - switch (mode) { - | Ana(ana_ty) => DHExp.cast(d, Bool, ana_ty) - | _ => d +/* The primary goal of elaboration is to convert from a type system + where we have consistency, to a type system where types are either + equal or they're not. Anything that was just consistent needs to + become a cast. [The one other thing elaboration does is make + recursive let bindings explicit.] + + At the top of this function we work out the "elaborated type" of + of the expression. We also return this elaborated type so we can + use it in the recursive call. When elaborate returns, you can trust + that the returned expression will have the returned type. There is + however, no guarantee that the returned type is even consistent with + the "elaborated type" at the top, so you should fresh_cast EVERYWHERE + just in case. + + Important invariant: any cast in an elaborated expression should have + normalized types. + + [Matt] A lot of these fresh_cast calls are redundant, however if you + want to remove one, I'd ask you instead comment it out and leave + a comment explaining why it's redundant. */ +let rec elaborate = (m: Statics.Map.t, uexp: UExp.t): (DHExp.t, Typ.t) => { + let (elaborated_type, ctx, co_ctx) = elaborated_type(m, uexp); + let cast_from = (ty, exp) => fresh_cast(exp, ty, elaborated_type); + let (term, rewrap) = UExp.unwrap(uexp); + let dhexp = + switch (term) { + | Invalid(_) + | Undefined + | EmptyHole => uexp |> cast_from(Typ.temp(Typ.Unknown(Internal))) + | MultiHole(stuff) => + Any.map_term( + ~f_exp=(_, exp) => {elaborate(m, exp) |> fst}, + ~f_pat=(_, pat) => {elaborate_pattern(m, pat) |> fst}, + _, + ) + |> List.map(_, stuff) + |> ( + stuff => + DHExp.MultiHole(stuff) + |> rewrap + |> cast_from(Typ.temp(Typ.Unknown(Internal))) + ) + | DynamicErrorHole(e, err) => + let (e', _) = elaborate(m, e); + DynamicErrorHole(e', err) + |> rewrap + |> cast_from(Typ.temp(Unknown(Internal))); + | Cast(e, _, _) // We remove these casts because they should be re-inserted in the recursive call + | FailedCast(e, _, _) + | Parens(e) => + let (e', ty) = elaborate(m, e); + e' |> cast_from(ty); + | Deferral(_) => uexp + | Int(_) => uexp |> cast_from(Int |> Typ.temp) + | Bool(_) => uexp |> cast_from(Bool |> Typ.temp) + | Float(_) => uexp |> cast_from(Float |> Typ.temp) + | String(_) => uexp |> cast_from(String |> Typ.temp) + | ListLit(es) => + let (ds, tys) = List.map(elaborate(m), es) |> ListUtil.unzip; + let inner_type = + Typ.join_all(~empty=Typ.Unknown(Internal) |> Typ.temp, ctx, tys) + |> Option.value(~default=Typ.temp(Typ.Unknown(Internal))); + let ds' = List.map2((d, t) => fresh_cast(d, t, inner_type), ds, tys); + Exp.ListLit(ds') |> rewrap |> cast_from(List(inner_type) |> Typ.temp); + | Constructor(c, _) => + let mode = + switch (Id.Map.find_opt(Exp.rep_id(uexp), m)) { + | Some(Info.InfoExp({mode, _})) => mode + | _ => raise(MissingTypeInfo) }; - | BinOp(op, e1, e2) => - let (_, cons) = exp_binop_of(op); - let* dc1 = dhexp_of_uexp(m, e1); - let+ dc2 = dhexp_of_uexp(m, e2); - cons(dc1, dc2); - | Parens(e) => dhexp_of_uexp(m, e) - | Seq(e1, e2) => - let* d1 = dhexp_of_uexp(m, e1); - let+ d2 = dhexp_of_uexp(m, e2); - DHExp.Sequence(d1, d2); - | Test(test) => - let+ dtest = dhexp_of_uexp(m, test); - DHExp.Test(id, dtest); - | Filter(act, cond, body) => - let* dcond = dhexp_of_uexp(~in_filter=true, m, cond); - let+ dbody = dhexp_of_uexp(m, body); - DHExp.Filter(Filter(Filter.mk(dcond, act)), dbody); - | Var(name) => - switch (err_status) { - | InHole(FreeVariable(_)) => Some(FreeVar(id, 0, name)) - | _ => Some(BoundVar(name)) - } - | Constructor(name) => - switch (err_status) { - | InHole(Common(NoType(FreeConstructor(_)))) => - Some(FreeVar(id, 0, name)) - | _ => Some(Constructor(name)) - } - | Let(p, def, body) => - let add_name: (option(string), DHExp.t) => DHExp.t = ( - name => - fun - | Fun(p, ty, e, _) => DHExp.Fun(p, ty, e, name) - | TypFun(tpat, e, _) => DHExp.TypFun(tpat, e, name) - | d => d - ); - let* dp = dhpat_of_upat(m, p); - let* ddef = dhexp_of_uexp(m, def); - let* dbody = dhexp_of_uexp(m, body); - let+ ty = fixed_pat_typ(m, p); - let is_recursive = - Statics.is_recursive(ctx, p, def, ty) - && Term.UPat.get_bindings(p) - |> Option.get - |> List.exists(f => VarMap.lookup(co_ctx, f) != None); - if (!is_recursive) { - /* not recursive */ - DHExp.Let( - dp, - add_name(Term.UPat.get_var(p), ddef), - dbody, - ); - } else { - switch (Term.UPat.get_bindings(p) |> Option.get) { - | [f] => - /* simple recursion */ - Let(dp, FixF(f, ty, add_name(Some(f ++ "+"), ddef)), dbody) - | fs => - /* mutual recursion */ - let ddef = - switch (ddef) { - | Tuple(a) => - DHExp.Tuple( - List.map2(s => add_name(Some(s ++ "+")), fs, a), - ) - | _ => ddef - }; - let uniq_id = List.nth(def.ids, 0); - let self_id = "__mutual__" ++ Id.to_string(uniq_id); - let self_var = DHExp.BoundVar(self_id); - let (_, substituted_def) = - fs - |> List.fold_left( - ((i, ddef), f) => { - let ddef = - Substitution.subst_var( - DHExp.Prj(self_var, i), - f, - ddef, - ); - (i + 1, ddef); - }, - (0, ddef), - ); - Let(dp, FixF(self_id, ty, substituted_def), dbody); - }; + let t = + switch (Mode.ctr_ana_typ(ctx, mode, c), Ctx.lookup_ctr(ctx, c)) { + | (Some(ana_ty), _) => ana_ty + | (_, Some({typ: syn_ty, _})) => syn_ty + | _ => Unknown(Internal) |> Typ.temp }; - | Module(p, def, body) => - let* dp = dhpat_of_upat(m, p); - let* ddef = dhexp_of_uexp(m, def); - let+ dbody = dhexp_of_uexp(m, body); - /* if get module type, apply alias(Let).*/ - let is_alias = - switch (Id.Map.find_opt(Term.UExp.rep_id(def), m)) { - | Some(InfoExp({self, _})) => - switch (self) { - | Common(Just(Module(_))) => true - | _ => false - } - | _ => false + let t = t |> Typ.normalize(ctx); + Constructor(c, t) |> rewrap |> cast_from(t); + | Fun(p, e, env, n) => + let (p', typ) = elaborate_pattern(m, p); + let (e', tye) = elaborate(m, e); + Exp.Fun(p', e', env, n) + |> rewrap + |> cast_from(Arrow(typ, tye) |> Typ.temp); + | TypFun(tpat, e, name) => + let (e', tye) = elaborate(m, e); + Exp.TypFun(tpat, e', name) + |> rewrap + |> cast_from(Typ.Forall(tpat, tye) |> Typ.temp); + | Tuple(es) => + let (ds, tys) = List.map(elaborate(m), es) |> ListUtil.unzip; + Exp.Tuple(ds) |> rewrap |> cast_from(Prod(tys) |> Typ.temp); + | Var(v) => + uexp + |> cast_from( + Ctx.lookup_var(ctx, v) + |> Option.map((x: Ctx.var_entry) => x.typ |> Typ.normalize(ctx)) + |> Option.value(~default=Typ.temp(Typ.Unknown(Internal))), + ) + | Let(p, def, body) => + let add_name: (option(string), DHExp.t) => DHExp.t = ( + (name, exp) => { + let (term, rewrap) = DHExp.unwrap(exp); + switch (term) { + | Fun(p, e, ctx, _) => Fun(p, e, ctx, name) |> rewrap + | TypFun(tpat, e, _) => TypFun(tpat, e, name) |> rewrap + | _ => exp }; - let signiture = - switch (Id.Map.find_opt(Term.UPat.rep_id(p), m)) { - | Some(InfoPat({ty, _})) => - switch (ty) { - | Module(c) => c.inner_ctx - | _ => [] - } + } + ); + let (p, ty1) = elaborate_pattern(m, p); + let is_recursive = + Statics.is_recursive(ctx, p, def, ty1) + && Pat.get_bindings(p) + |> Option.get + |> List.exists(f => VarMap.lookup(co_ctx, f) != None); + if (!is_recursive) { + let def = add_name(Pat.get_var(p), def); + let (def, ty2) = elaborate(m, def); + let (body, ty) = elaborate(m, body); + Exp.Let(p, fresh_cast(def, ty2, ty1), body) + |> rewrap + |> cast_from(ty); + } else { + // TODO: Add names to mutually recursive functions + // TODO: Don't add fixpoint if there already is one + let def = add_name(Option.map(s => s ++ "+", Pat.get_var(p)), def); + let (def, ty2) = elaborate(m, def); + let (body, ty) = elaborate(m, body); + let fixf = FixF(p, fresh_cast(def, ty2, ty1), None) |> DHExp.fresh; + Exp.Let(p, fixf, body) |> rewrap |> cast_from(ty); + }; + | Module(p, def, body) => + let* dp = dhpat_of_upat(m, p); + let* ddef = dhexp_of_uexp(m, def); + let+ dbody = dhexp_of_uexp(m, body); + /* if get module type, apply alias(Let).*/ + let is_alias = + switch (Id.Map.find_opt(Term.UExp.rep_id(def), m)) { + | Some(InfoExp({self, _})) => + switch (self) { + | Common(Just(Module(_))) => true + | _ => false + } + | _ => false + }; + let signiture = + switch (Id.Map.find_opt(Term.UPat.rep_id(p), m)) { + | Some(InfoPat({ty, _})) => + switch (ty) { + | Module(c) => c.inner_ctx | _ => [] - }; - let (closure, names) = - List.fold_left( - ((closure, names): (ClosureEnvironment.t, list(Var.t))) => - fun - | Ctx.VarEntry({name, id, _}) => ( - Environment.extend( - closure |> ClosureEnvironment.map_of, - (name, EmptyHole(id, 0)), - ) - |> ClosureEnvironment.wrap( - ClosureEnvironment.id_of(closure), - ), - [name, ...names], + } + | _ => [] + }; + let (closure, names) = + List.fold_left( + ((closure, names): (ClosureEnvironment.t, list(Var.t))) => + fun + | Ctx.VarEntry({name, id, _}) => ( + Environment.extend( + closure |> ClosureEnvironment.map_of, + (name, EmptyHole(id, 0)), ) - | Ctx.TVarEntry(_) - | Ctx.ConstructorEntry(_) => (closure, names), - (ClosureEnvironment.empty, []), - signiture, - ); - let rec body_modulize: DHExp.t => DHExp.t = ( - fun - | Let(dp, d1, d2) => Let(dp, d1, body_modulize(d2)) - | Module(dp, d1, d2) => Module(dp, d1, body_modulize(d2)) - | _ as d => is_alias ? d : ModuleVal(closure, names) + |> ClosureEnvironment.wrap(ClosureEnvironment.id_of(closure)), + [name, ...names], + ) + | Ctx.TVarEntry(_) + | Ctx.ConstructorEntry(_) => (closure, names), + (ClosureEnvironment.empty, []), + signiture, ); - let ddef = ddef |> body_modulize; - DHExp.Module(dp, ddef, dbody); - | Dot(e_mod, e_mem) => - let* e_mod = dhexp_of_uexp(m, e_mod); - let+ e_mem = dhexp_of_uexp(m, e_mem); - DHExp.Dot(e_mod, e_mem); - | Ap(fn, arg) - | Pipeline(arg, fn) => - let* c_fn = dhexp_of_uexp(m, fn); - let+ c_arg = dhexp_of_uexp(m, arg); - DHExp.Ap(c_fn, c_arg); - | TypAp(fn, uty_arg) => - let+ d_fn = dhexp_of_uexp(m, fn); - DHExp.TypAp(d_fn, Term.UTyp.to_typ(ctx, uty_arg)); - | DeferredAp(fn, args) => - switch (err_status) { - | InHole(BadPartialAp(NoDeferredArgs)) => dhexp_of_uexp(m, fn) - | InHole(BadPartialAp(ArityMismatch(_))) => - Some(DHExp.InvalidText(id, 0, "")) - | _ => - let mk_tuple = (ctor, xs) => - List.length(xs) == 1 ? List.hd(xs) : ctor(xs); - let* ty_fn = fixed_exp_typ(m, fn); - let (ty_arg, ty_ret) = Typ.matched_arrow(ctx, ty_fn); - let ty_ins = Typ.matched_args(ctx, List.length(args), ty_arg); - /* Substitute all deferrals for new variables */ - let (pats, ty_args, ap_args, ap_ctx) = - List.combine(args, ty_ins) - |> List.fold_left( - ((pats, ty_args, ap_args, ap_ctx), (e: Term.UExp.t, ty)) => - if (Term.UExp.is_deferral(e)) { - // Internal variable name for deferrals - let name = - "__deferred__" ++ string_of_int(List.length(pats)); - let var: Term.UExp.t = {ids: e.ids, term: Var(name)}; - let var_entry = - Ctx.VarEntry({ - name, - id: Term.UExp.rep_id(e), - typ: ty, - }); - ( - pats @ [DHPat.Var(name)], - ty_args @ [ty], - ap_args @ [var], - Ctx.extend(ap_ctx, var_entry), - ); - } else { - (pats, ty_args, ap_args @ [e], ap_ctx); - }, - ([], [], [], ctx), - ); - let (pat, ty_arg) = ( - mk_tuple(x => DHPat.Tuple(x), pats), - mk_tuple(x => Typ.Prod(x), ty_args), - ); - let arg: Term.UExp.t = {ids: [Id.mk()], term: Tuple(ap_args)}; - let body: Term.UExp.t = {ids: [Id.mk()], term: Ap(fn, arg)}; - let (_info, m) = - Statics.uexp_to_info_map( - ~ctx=ap_ctx, - ~mode=Ana(ty_ret), - ~ancestors, - body, - m, - ); - let+ dbody = dhexp_of_uexp(m, body); - DHExp.Fun(pat, Arrow(ty_arg, ty_ret), dbody, None); - } - | If(c, e1, e2) => - let* c' = dhexp_of_uexp(m, c); - let* d1 = dhexp_of_uexp(m, e1); - let+ d2 = dhexp_of_uexp(m, e2); - // Use tag to mark inconsistent branches - switch (err_status) { - | InHole(Common(Inconsistent(Internal(_)))) => - DHExp.IfThenElse(DH.InconsistentIf, c', d1, d2) - | _ => DHExp.IfThenElse(DH.ConsistentIf, c', d1, d2) - }; - | Match(scrut, rules) => - let* d_scrut = dhexp_of_uexp(m, scrut); - let+ d_rules = - List.map( - ((p, e)) => { - let* d_p = dhpat_of_upat(m, p); - let+ d_e = dhexp_of_uexp(m, e); - DHExp.Rule(d_p, d_e); - }, - rules, - ) - |> OptUtil.sequence; - let d = DHExp.Case(d_scrut, d_rules, 0); - switch (err_status) { - | InHole(Common(Inconsistent(Internal(_)))) - | InHole(InexhaustiveMatch(Some(Inconsistent(Internal(_))))) => - DHExp.InconsistentBranches(id, 0, d) - | _ => ConsistentCase(d) + let rec body_modulize: DHExp.t => DHExp.t = ( + fun + | Let(dp, d1, d2) => Let(dp, d1, body_modulize(d2)) + | Module(dp, d1, d2) => Module(dp, d1, body_modulize(d2)) + | _ as d => is_alias ? d : ModuleVal(closure, names) + ); + let ddef = ddef |> body_modulize; + Exp.Module(dp, ddef, dbody); + | Dot(e_mod, e_mem) => + let* e_mod = dhexp_of_uexp(m, e_mod); + let+ e_mem = dhexp_of_uexp(m, e_mem); + Exp.Dot(e_mod, e_mem); + | FixF(p, e, env) => + let (p', typ) = elaborate_pattern(m, p); + let (e', tye) = elaborate(m, e); + Exp.FixF(p', fresh_cast(e', tye, typ), env) + |> rewrap + |> cast_from(typ); + | TyAlias(_, _, e) => + let (e', tye) = elaborate(m, e); + e' |> cast_from(tye); + | Ap(dir, f, a) => + let (f', tyf) = elaborate(m, f); + let (a', tya) = elaborate(m, a); + let (tyf1, tyf2) = Typ.matched_arrow(ctx, tyf); + let f'' = fresh_cast(f', tyf, Arrow(tyf1, tyf2) |> Typ.temp); + let a'' = fresh_cast(a', tya, tyf1); + Exp.Ap(dir, f'', a'') |> rewrap |> cast_from(tyf2); + | DeferredAp(f, args) => + let (f', tyf) = elaborate(m, f); + let (args', tys) = List.map(elaborate(m), args) |> ListUtil.unzip; + let (tyf1, tyf2) = Typ.matched_arrow(ctx, tyf); + let ty_fargs = Typ.matched_prod(ctx, List.length(args), tyf1); + let f'' = + fresh_cast( + f', + tyf, + Arrow(Prod(ty_fargs) |> Typ.temp, tyf2) |> Typ.temp, + ); + let args'' = ListUtil.map3(fresh_cast, args', tys, ty_fargs); + let remaining_args = + List.filter( + ((arg, _)) => Exp.is_deferral(arg), + List.combine(args, ty_fargs), + ); + let remaining_arg_ty = Prod(List.map(snd, remaining_args)) |> Typ.temp; + DeferredAp(f'', args'') + |> rewrap + |> cast_from(Arrow(remaining_arg_ty, tyf2) |> Typ.temp); + | TypAp(e, ut) => + let (e', tye) = elaborate(m, e); + let (tpat, tye') = Typ.matched_forall(ctx, tye); + let ut' = Typ.normalize(ctx, ut); + let tye'' = + Typ.subst( + ut', + tpat |> Option.value(~default=TPat.fresh(EmptyHole)), + tye', + ); + TypAp(e', ut) |> rewrap |> cast_from(tye''); + | If(c, t, f) => + let (c', tyc) = elaborate(m, c); + let (t', tyt) = elaborate(m, t); + let (f', tyf) = elaborate(m, f); + let ty = + Typ.join(~fix=false, ctx, tyt, tyf) + |> Option.value(~default=Typ.temp(Typ.Unknown(Internal))); + let c'' = fresh_cast(c', tyc, Bool |> Typ.temp); + let t'' = fresh_cast(t', tyt, ty); + let f'' = fresh_cast(f', tyf, ty); + Exp.If(c'', t'', f'') |> rewrap |> cast_from(ty); + | Seq(e1, e2) => + let (e1', _) = elaborate(m, e1); + let (e2', ty2) = elaborate(m, e2); + Seq(e1', e2') |> rewrap |> cast_from(ty2); + | Test(e) => + let (e', t) = elaborate(m, e); + Test(fresh_cast(e', t, Bool |> Typ.temp)) + |> rewrap + |> cast_from(Prod([]) |> Typ.temp); + | Filter(kind, e) => + let (e', t) = elaborate(m, e); + let kind' = + switch (kind) { + | Residue(_) => kind + | Filter({act, pat}) => Filter({act, pat: elaborate(m, pat) |> fst}) }; - | TyAlias(_, _, e) => dhexp_of_uexp(m, e) - }; - switch (uexp.term) { - | Parens(_) => d - | _ => wrap(ctx, id, mode, self, d) - }; - | Some(InfoPat(_) | InfoTyp(_) | InfoTPat(_) | Secondary(_)) - | None => None - }; -} -and dhpat_of_upat = (m: Statics.Map.t, upat: Term.UPat.t): option(DHPat.t) => { - switch (Id.Map.find_opt(Term.UPat.rep_id(upat), m)) { - | Some(InfoPat({mode, self, ctx, _})) => - // NOTE: for the current implementation, redundancy is considered a static error - // but not a runtime error. - let self = - switch (self) { - | Redundant(self) => self - | _ => self - }; - let err_status = Info.status_pat(ctx, mode, self); - let maybe_reason: option(ErrStatus.HoleReason.t) = - switch (err_status) { - | NotInHole(_) => None - | InHole(_) => Some(TypeInconsistent) - }; - let u = Term.UPat.rep_id(upat); /* NOTE: using term uids for hole ids */ - let wrap = (d: DHPat.t): option(DHPat.t) => - switch (maybe_reason) { - | None => Some(d) - | Some(reason) => Some(NonEmptyHole(reason, u, 0, d)) - }; - switch (upat.term) { - | Invalid(t) => Some(DHPat.InvalidText(u, 0, t)) - | EmptyHole => Some(EmptyHole(u, 0)) - | MultiHole(_) => - // TODO: dhexp, eval for multiholes - Some(EmptyHole(u, 0)) - | Wild => wrap(Wild) - | Bool(b) => wrap(BoolLit(b)) - | Int(n) => wrap(IntLit(n)) - | Float(n) => wrap(FloatLit(n)) - | String(s) => wrap(StringLit(s)) - | Triv => wrap(Tuple([])) - | ListLit(ps) => - let* ds = ps |> List.map(dhpat_of_upat(m)) |> OptUtil.sequence; - let* ty = fixed_pat_typ(m, upat); - wrap(ListLit(Typ.matched_list(ctx, ty), ds)); - | Constructor(name) => - switch (err_status) { - | InHole(Common(NoType(FreeConstructor(_)))) => - Some(BadConstructor(u, 0, name)) - | _ => wrap(Constructor(name)) + Filter(kind', e') |> rewrap |> cast_from(t); + | Closure(env, e) => + // Should we be elaborating the contents of the environment? + let (e', t) = elaborate(m, e); + Closure(env, e') |> rewrap |> cast_from(t); + | Cons(e1, e2) => + let (e1', ty1) = elaborate(m, e1); + let (e2', ty2) = elaborate(m, e2); + let ty2_inner = Typ.matched_list(ctx, ty2); + let ty_inner = + Typ.join(~fix=false, ctx, ty1, ty2_inner) + |> Option.value(~default=Typ.temp(Unknown(Internal))); + let e1'' = fresh_cast(e1', ty1, ty_inner); + let e2'' = fresh_cast(e2', ty2, List(ty_inner) |> Typ.temp); + Cons(e1'', e2'') |> rewrap |> cast_from(List(ty_inner) |> Typ.temp); + | ListConcat(e1, e2) => + let (e1', ty1) = elaborate(m, e1); + let (e2', ty2) = elaborate(m, e2); + let ty_inner1 = Typ.matched_list(ctx, ty1); + let ty_inner2 = Typ.matched_list(ctx, ty2); + let ty_inner = + Typ.join(~fix=false, ctx, ty_inner1, ty_inner2) + |> Option.value(~default=Typ.temp(Unknown(Internal))); + let e1'' = fresh_cast(e1', ty1, List(ty_inner) |> Typ.temp); + let e2'' = fresh_cast(e2', ty2, List(ty_inner) |> Typ.temp); + ListConcat(e1'', e2'') + |> rewrap + |> cast_from(List(ty_inner) |> Typ.temp); + | UnOp(Meta(Unquote), e) => + switch (e.term) { + // TODO: confirm whether these types are correct + | Var("e") => + Constructor("$e", Unknown(Internal) |> Typ.temp) |> rewrap + | Var("v") => + Constructor("$v", Unknown(Internal) |> Typ.temp) |> rewrap + | _ => + DHExp.EmptyHole + |> rewrap + |> cast_from(Typ.temp(Typ.Unknown(Internal))) } - | Cons(hd, tl) => - let* d_hd = dhpat_of_upat(m, hd); - let* d_tl = dhpat_of_upat(m, tl); - wrap(Cons(d_hd, d_tl)); - | Tuple(ps) => - let* ds = ps |> List.map(dhpat_of_upat(m)) |> OptUtil.sequence; - wrap(DHPat.Tuple(ds)); - | Var(name) => Some(Var(name)) - | Parens(p) => dhpat_of_upat(m, p) - | Ap(p1, p2) => - let* d_p1 = dhpat_of_upat(m, p1); - let* d_p2 = dhpat_of_upat(m, p2); - wrap(Ap(d_p1, d_p2)); - | TypeAnn(p, _ty) => - let* dp = dhpat_of_upat(m, p); - wrap(dp); - | TyAlias(_, _) => Some(DHPat.InvalidText(u, 0, "")) + | UnOp(Int(Minus), e) => + let (e', t) = elaborate(m, e); + UnOp(Int(Minus), fresh_cast(e', t, Int |> Typ.temp)) + |> rewrap + |> cast_from(Int |> Typ.temp); + | UnOp(Bool(Not), e) => + let (e', t) = elaborate(m, e); + UnOp(Bool(Not), fresh_cast(e', t, Bool |> Typ.temp)) + |> rewrap + |> cast_from(Bool |> Typ.temp); + | BinOp(Int(Plus | Minus | Times | Power | Divide) as op, e1, e2) => + let (e1', t1) = elaborate(m, e1); + let (e2', t2) = elaborate(m, e2); + BinOp( + op, + fresh_cast(e1', t1, Int |> Typ.temp), + fresh_cast(e2', t2, Int |> Typ.temp), + ) + |> rewrap + |> cast_from(Int |> Typ.temp); + | BinOp( + Int( + LessThan | LessThanOrEqual | GreaterThan | GreaterThanOrEqual | + Equals | + NotEquals, + ) as op, + e1, + e2, + ) => + let (e1', t1) = elaborate(m, e1); + let (e2', t2) = elaborate(m, e2); + BinOp( + op, + fresh_cast(e1', t1, Int |> Typ.temp), + fresh_cast(e2', t2, Int |> Typ.temp), + ) + |> rewrap + |> cast_from(Bool |> Typ.temp); + | BinOp(Bool(And | Or) as op, e1, e2) => + let (e1', t1) = elaborate(m, e1); + let (e2', t2) = elaborate(m, e2); + BinOp( + op, + fresh_cast(e1', t1, Bool |> Typ.temp), + fresh_cast(e2', t2, Bool |> Typ.temp), + ) + |> rewrap + |> cast_from(Bool |> Typ.temp); + | BinOp(Float(Plus | Minus | Times | Divide | Power) as op, e1, e2) => + let (e1', t1) = elaborate(m, e1); + let (e2', t2) = elaborate(m, e2); + BinOp( + op, + fresh_cast(e1', t1, Float |> Typ.temp), + fresh_cast(e2', t2, Float |> Typ.temp), + ) + |> rewrap + |> cast_from(Float |> Typ.temp); + | BinOp( + Float( + LessThan | LessThanOrEqual | GreaterThan | GreaterThanOrEqual | + Equals | + NotEquals, + ) as op, + e1, + e2, + ) => + let (e1', t1) = elaborate(m, e1); + let (e2', t2) = elaborate(m, e2); + BinOp( + op, + fresh_cast(e1', t1, Float |> Typ.temp), + fresh_cast(e2', t2, Float |> Typ.temp), + ) + |> rewrap + |> cast_from(Bool |> Typ.temp); + | BinOp(String(Concat) as op, e1, e2) => + let (e1', t1) = elaborate(m, e1); + let (e2', t2) = elaborate(m, e2); + BinOp( + op, + fresh_cast(e1', t1, String |> Typ.temp), + fresh_cast(e2', t2, String |> Typ.temp), + ) + |> rewrap + |> cast_from(String |> Typ.temp); + | BinOp(String(Equals) as op, e1, e2) => + let (e1', t1) = elaborate(m, e1); + let (e2', t2) = elaborate(m, e2); + BinOp( + op, + fresh_cast(e1', t1, String |> Typ.temp), + fresh_cast(e2', t2, String |> Typ.temp), + ) + |> rewrap + |> cast_from(Bool |> Typ.temp); + | BuiltinFun(fn) => + uexp + |> cast_from( + Ctx.lookup_var(Builtins.ctx_init, fn) + |> Option.map((x: Ctx.var_entry) => x.typ) + |> Option.value(~default=Typ.temp(Typ.Unknown(Internal))), + ) + | Match(e, cases) => + let (e', t) = elaborate(m, e); + let (ps, es) = ListUtil.unzip(cases); + let (ps', ptys) = + List.map(elaborate_pattern(m), ps) |> ListUtil.unzip; + let joined_pty = + Typ.join_all(~empty=Typ.Unknown(Internal) |> Typ.temp, ctx, ptys) + |> Option.value(~default=Typ.temp(Typ.Unknown(Internal))); + let ps'' = + List.map2((p, t) => fresh_pat_cast(p, t, joined_pty), ps', ptys); + let e'' = fresh_cast(e', t, joined_pty); + let (es', etys) = List.map(elaborate(m), es) |> ListUtil.unzip; + let joined_ety = + Typ.join_all(~empty=Typ.Unknown(Internal) |> Typ.temp, ctx, etys) + |> Option.value(~default=Typ.temp(Typ.Unknown(Internal))); + let es'' = + List.map2((e, t) => fresh_cast(e, t, joined_ety), es', etys); + Match(e'', List.combine(ps'', es'')) + |> rewrap + |> cast_from(joined_ety); }; - | Some(InfoExp(_) | InfoTyp(_) | InfoTPat(_) | Secondary(_)) - | None => None - }; + (dhexp, elaborated_type); }; //let dhexp_of_uexp = Core.Memo.general(~cache_size_bound=1000, dhexp_of_uexp); -let uexp_elab = (m: Statics.Map.t, uexp: Term.UExp.t): ElaborationResult.t => - switch (dhexp_of_uexp(m, uexp, false)) { - | None => DoesNotElaborate - | Some(d) => - //let d = uexp_elab_wrap_builtins(d); - let ty = - switch (fixed_exp_typ(m, uexp)) { - | Some(ty) => ty - | None => Typ.Unknown(Internal) - }; - Elaborates(d, ty, Delta.empty); +/* This function gives a new id to all the types + in the expression. It does this to get rid of + all the invalid ids we added to prevent generating + too many new ids */ +let fix_typ_ids = + Exp.map_term(~f_typ=(cont, e) => e |> IdTagged.new_ids |> cont); + +let uexp_elab = (m: Statics.Map.t, uexp: UExp.t): ElaborationResult.t => + switch (elaborate(m, uexp)) { + | exception MissingTypeInfo => DoesNotElaborate + | (d, ty) => Elaborates(d, ty, Delta.empty) }; diff --git a/src/haz3lcore/dynamics/Environment.re b/src/haz3lcore/dynamics/Environment.re index 9a2c61a96b..726200d7d8 100644 --- a/src/haz3lcore/dynamics/Environment.re +++ b/src/haz3lcore/dynamics/Environment.re @@ -1 +1 @@ -include DH.Environment; +include TermBase.Environment; diff --git a/src/haz3lcore/dynamics/Environment.rei b/src/haz3lcore/dynamics/Environment.rei index 3408ac0aa5..bb9d5214af 100644 --- a/src/haz3lcore/dynamics/Environment.rei +++ b/src/haz3lcore/dynamics/Environment.rei @@ -1 +1,2 @@ -include (module type of DH.Environment) with type t = DH.Environment.t; +include + (module type of TermBase.Environment) with type t = TermBase.Environment.t; diff --git a/src/haz3lcore/dynamics/EnvironmentId.re b/src/haz3lcore/dynamics/EnvironmentId.re deleted file mode 100644 index 5f6be7cd46..0000000000 --- a/src/haz3lcore/dynamics/EnvironmentId.re +++ /dev/null @@ -1 +0,0 @@ -include Id; diff --git a/src/haz3lcore/dynamics/EnvironmentId.rei b/src/haz3lcore/dynamics/EnvironmentId.rei deleted file mode 100644 index e7d316dd0a..0000000000 --- a/src/haz3lcore/dynamics/EnvironmentId.rei +++ /dev/null @@ -1 +0,0 @@ -include (module type of Id); diff --git a/src/haz3lcore/dynamics/EnvironmentIdMap.re b/src/haz3lcore/dynamics/EnvironmentIdMap.re deleted file mode 100644 index 932d7b1316..0000000000 --- a/src/haz3lcore/dynamics/EnvironmentIdMap.re +++ /dev/null @@ -1 +0,0 @@ -include Id.Map; diff --git a/src/haz3lcore/dynamics/EnvironmentIdMap.rei b/src/haz3lcore/dynamics/EnvironmentIdMap.rei deleted file mode 100644 index d5194bbcf2..0000000000 --- a/src/haz3lcore/dynamics/EnvironmentIdMap.rei +++ /dev/null @@ -1,5 +0,0 @@ -/* Mapping from EnvironmentId.t (to some other type) - - Used in HoleInstanceInfo_.re - */ -include (module type of Id.Map); diff --git a/src/haz3lcore/dynamics/ErrStatus.re b/src/haz3lcore/dynamics/ErrStatus.re deleted file mode 100644 index 94fd844ffe..0000000000 --- a/src/haz3lcore/dynamics/ErrStatus.re +++ /dev/null @@ -1,15 +0,0 @@ -module HoleReason = { - /* Variable: `reason` */ - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - | TypeInconsistent - | WrongLength; - - let eq = (x, y) => x == y; -}; - -/* Variable: `err` */ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = - | NotInHole - | InHole(HoleReason.t, MetaVar.t); diff --git a/src/haz3lcore/dynamics/EvalCtx.re b/src/haz3lcore/dynamics/EvalCtx.re index 6e41cfc146..e5b20146ab 100644 --- a/src/haz3lcore/dynamics/EvalCtx.re +++ b/src/haz3lcore/dynamics/EvalCtx.re @@ -1,283 +1,172 @@ -open Sexplib.Std; -open DH; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] -type cls = - | Mark - | Closure - | FilterPattern - | Filter - | Sequence1 - | Sequence2 - | Let1 - | Let2 - | Module1 - | Module2 - | ModuleVal - | Dot1 - | Dot2 - | TypAp - | Ap1 - | Ap2 - | Fun - | FixF - | BinBoolOp1 - | BinBoolOp2 - | BinIntOp1 - | BinIntOp2 - | BinFloatOp1 - | BinFloatOp2 - | BinStringOp1 - | BinStringOp2 - | IfThenElse1 - | IfThenElse2 - | IfThenElse3 - | Tuple(int) - | ListLit(int) - | ApBuiltin - | Test - | Cons1 - | Cons2 - | ListConcat1 - | ListConcat2 - | Prj - | NonEmptyHole - | Cast - | FailedCast - | InvalidOperation - | ConsistentCase - | ConsistentCaseRule(int) - | InconsistentBranches - | InconsistentBranchesRule(int) - | FailedCastCast - // Used when entering a bound variable expression in substitution mode - | BoundVar; - -[@deriving (show({with_path: false}), sexp, yojson)] -type t = - | Mark +type term = | Closure([@show.opaque] ClosureEnvironment.t, t) - | Filter(DH.DHFilter.t, t) - | Sequence1(t, DHExp.t) - | Sequence2(DHExp.t, t) - | Let1(DHPat.t, t, DHExp.t) - | Let2(DHPat.t, DHExp.t, t) - | Module1(DHPat.t, t, DHExp.t) - | Module2(DHPat.t, DHExp.t, t) + | Filter(TermBase.StepperFilterKind.t, t) + | Seq1(t, DHExp.t) + | Seq2(DHExp.t, t) + | Let1(Pat.t, t, DHExp.t) + | Let2(Pat.t, DHExp.t, t) + | Module1(Pat.t, t, DHExp.t) + | Module2(Pat.t, DHExp.t, t) | Dot1(t, DHExp.t) | Dot2(DHExp.t, t) - | Fun(DHPat.t, Typ.t, t, option(Var.t)) - | FixF(Var.t, Typ.t, t) + | Fun(Pat.t, t, option(ClosureEnvironment.t), option(Var.t)) + | FixF(Pat.t, t, option(ClosureEnvironment.t)) | TypAp(t, Typ.t) - | Ap1(t, DHExp.t) - | Ap2(DHExp.t, t) - | IfThenElse1(if_consistency, t, DHExp.t, DHExp.t) - | IfThenElse2(if_consistency, DHExp.t, t, DHExp.t) - | IfThenElse3(if_consistency, DHExp.t, DHExp.t, t) - | BinBoolOp1(TermBase.UExp.op_bin_bool, t, DHExp.t) - | BinBoolOp2(TermBase.UExp.op_bin_bool, DHExp.t, t) - | BinIntOp1(TermBase.UExp.op_bin_int, t, DHExp.t) - | BinIntOp2(TermBase.UExp.op_bin_int, DHExp.t, t) - | BinFloatOp1(TermBase.UExp.op_bin_float, t, DHExp.t) - | BinFloatOp2(TermBase.UExp.op_bin_float, DHExp.t, t) - | BinStringOp1(TermBase.UExp.op_bin_string, t, DHExp.t) - | BinStringOp2(TermBase.UExp.op_bin_string, DHExp.t, t) + | Ap1(Operators.ap_direction, t, DHExp.t) + | Ap2(Operators.ap_direction, DHExp.t, t) + | DeferredAp1(t, list(DHExp.t)) + | DeferredAp2(DHExp.t, t, (list(DHExp.t), list(DHExp.t))) + | If1(t, DHExp.t, DHExp.t) + | If2(DHExp.t, t, DHExp.t) + | If3(DHExp.t, DHExp.t, t) + | UnOp(Operators.op_un, t) + | BinOp1(Operators.op_bin, t, DHExp.t) + | BinOp2(Operators.op_bin, DHExp.t, t) | Tuple(t, (list(DHExp.t), list(DHExp.t))) - | ApBuiltin(string, t) - | Test(KeywordID.t, t) - | ListLit( - MetaVar.t, - MetaVarInst.t, - Typ.t, - t, - (list(DHExp.t), list(DHExp.t)), - ) + | Test(t) + | ListLit(t, (list(DHExp.t), list(DHExp.t))) + | MultiHole(t, (list(Any.t), list(Any.t))) | Cons1(t, DHExp.t) | Cons2(DHExp.t, t) | ListConcat1(t, DHExp.t) | ListConcat2(DHExp.t, t) - | Prj(t, int) - | NonEmptyHole(ErrStatus.HoleReason.t, MetaVar.t, HoleInstanceId.t, t) | Cast(t, Typ.t, Typ.t) | FailedCast(t, Typ.t, Typ.t) - | InvalidOperation(t, InvalidOperationError.t) - | ConsistentCase(case) - | ConsistentCaseRule( + | DynamicErrorHole(t, InvalidOperationError.t) + | MatchScrut(t, list((UPat.t, DHExp.t))) + | MatchRule( DHExp.t, - DHPat.t, + UPat.t, t, - (list(DHExp.rule), list(DHExp.rule)), - int, + (list((UPat.t, DHExp.t)), list((UPat.t, DHExp.t))), ) - | InconsistentBranches(MetaVar.t, HoleInstanceId.t, case) - | InconsistentBranchesRule( - DHExp.t, - MetaVar.t, - HoleInstanceId.t, - DHPat.t, - t, - (list(DHExp.rule), list(DHExp.rule)), - int, - ) -and case = - | Case(t, list(rule), int) -and rule = DHExp.rule; - -let rec fuzzy_mark = - fun - | Mark => true - | Closure(_, x) - | Test(_, x) - | Cast(x, _, _) - | FailedCast(x, _, _) - | Filter(_, x) => fuzzy_mark(x) - | Sequence1(_) - | Sequence2(_) - | Let1(_) - | Let2(_) - | Module1(_) - | Module2(_) - | Dot1(_) - | Dot2(_) - | Fun(_) - | FixF(_) - | TypAp(_) - | Ap1(_) - | Ap2(_) - | IfThenElse1(_) - | IfThenElse2(_) - | IfThenElse3(_) - | BinBoolOp1(_) - | BinBoolOp2(_) - | BinIntOp1(_) - | BinIntOp2(_) - | BinFloatOp1(_) - | BinFloatOp2(_) - | BinStringOp1(_) - | BinStringOp2(_) - | Tuple(_) - | ApBuiltin(_) - | ListLit(_) - | Cons1(_) - | Cons2(_) - | ListConcat1(_) - | ListConcat2(_) - | Prj(_) - | NonEmptyHole(_) - | InvalidOperation(_) - | ConsistentCase(_) - | ConsistentCaseRule(_) - | InconsistentBranches(_) - | InconsistentBranchesRule(_) => false; +and t = + | Mark + | Term({ + term, + ids: list(Id.t), + }); -let rec unwrap = (ctx: t, sel: cls): option(t) => { - switch (sel, ctx) { - | (Mark, _) => - print_endline( - "Mark does not match with " - ++ Sexplib.Sexp.to_string_hum(sexp_of_t(ctx)), +let rec compose = (ctx: t, d: DHExp.t): DHExp.t => { + switch (ctx) { + | Mark => d + | Term({term, ids}) => + let wrap = DHExp.mk(ids); + DHExp.( + switch (term) { + | Closure(env, ctx) => + let d = compose(ctx, d); + Closure(env, d) |> wrap; + | Filter(flt, ctx) => + let d = compose(ctx, d); + Filter(flt, d) |> wrap; + | Seq1(ctx, d2) => + let d1 = compose(ctx, d); + Seq(d1, d2) |> wrap; + | Seq2(d1, ctx) => + let d2 = compose(ctx, d); + Seq(d1, d2) |> wrap; + | Ap1(dir, ctx, d2) => + let d1 = compose(ctx, d); + Ap(dir, d1, d2) |> wrap; + | Ap2(dir, d1, ctx) => + let d2 = compose(ctx, d); + Ap(dir, d1, d2) |> wrap; + | DeferredAp1(ctx, d2s) => + let d1 = compose(ctx, d); + DeferredAp(d1, d2s) |> wrap; + | DeferredAp2(d1, ctx, (ld, rd)) => + let d2 = compose(ctx, d); + DeferredAp(d1, ListUtil.rev_concat(ld, [d2, ...rd])) |> wrap; + | If1(ctx, d2, d3) => + let d' = compose(ctx, d); + If(d', d2, d3) |> wrap; + | If2(d1, ctx, d3) => + let d' = compose(ctx, d); + If(d1, d', d3) |> wrap; + | If3(d1, d2, ctx) => + let d' = compose(ctx, d); + If(d1, d2, d') |> wrap; + | Test(ctx) => + let d1 = compose(ctx, d); + Test(d1) |> wrap; + | UnOp(op, ctx) => + let d1 = compose(ctx, d); + UnOp(op, d1) |> wrap; + | BinOp1(op, ctx, d2) => + let d1 = compose(ctx, d); + BinOp(op, d1, d2) |> wrap; + | BinOp2(op, d1, ctx) => + let d2 = compose(ctx, d); + BinOp(op, d1, d2) |> wrap; + | Cons1(ctx, d2) => + let d1 = compose(ctx, d); + Cons(d1, d2) |> wrap; + | Cons2(d1, ctx) => + let d2 = compose(ctx, d); + Cons(d1, d2) |> wrap; + | ListConcat1(ctx, d2) => + let d1 = compose(ctx, d); + ListConcat(d1, d2) |> wrap; + | ListConcat2(d1, ctx) => + let d2 = compose(ctx, d); + ListConcat(d1, d2) |> wrap; + | Tuple(ctx, (ld, rd)) => + let d = compose(ctx, d); + Tuple(ListUtil.rev_concat(ld, [d, ...rd])) |> wrap; + | ListLit(ctx, (ld, rd)) => + let d = compose(ctx, d); + ListLit(ListUtil.rev_concat(ld, [d, ...rd])) |> wrap; + | MultiHole(ctx, (ld, rd)) => + let d = compose(ctx, d); + MultiHole(ListUtil.rev_concat(ld, [TermBase.Any.Exp(d), ...rd])) + |> wrap; + | Let1(dp, ctx, d2) => + let d = compose(ctx, d); + Let(dp, d, d2) |> wrap; + | Let2(dp, d1, ctx) => + let d = compose(ctx, d); + Let(dp, d1, d) |> wrap; + | Module1(dp, ctx, d2) => + let d = compose(ctx, d); + Module(dp, d, d2); + | Module2(dp, d1, ctx) => + let d = compose(ctx, d); + Module(dp, d1, d); + | Dot1(ctx, d2) => + let d1 = compose(ctx, d); + Dot(d1, d2); + | Dot2(d1, ctx) => + let d2 = compose(ctx, d); + Dot(d1, d2); + | Fun(dp, ctx, env, v) => + let d = compose(ctx, d); + Fun(dp, d, env, v) |> wrap; + | FixF(v, ctx, env) => + let d = compose(ctx, d); + FixF(v, d, env) |> wrap; + | Cast(ctx, ty1, ty2) => + let d = compose(ctx, d); + Cast(d, ty1, ty2) |> wrap; + | FailedCast(ctx, ty1, ty2) => + let d = compose(ctx, d); + FailedCast(d, ty1, ty2) |> wrap; + | DynamicErrorHole(ctx, err) => + let d = compose(ctx, d); + DynamicErrorHole(d, err) |> wrap; + | MatchScrut(ctx, rules) => + let d = compose(ctx, d); + Match(d, rules) |> wrap; + | MatchRule(scr, p, ctx, (lr, rr)) => + let d = compose(ctx, d); + Match(scr, ListUtil.rev_concat(lr, [(p, d), ...rr])) |> wrap; + | TypAp(ctx, ty) => + let d = compose(ctx, d); + TypAp(d, ty) |> wrap; + } ); - raise(EvaluatorError.Exception(StepDoesNotMatch)); - | (BoundVar, c) - | (NonEmptyHole, NonEmptyHole(_, _, _, c)) - | (Closure, Closure(_, c)) - | (Filter, Filter(_, c)) - | (Sequence1, Sequence1(c, _)) - | (Sequence2, Sequence2(_, c)) - | (Let1, Let1(_, c, _)) - | (Let2, Let2(_, _, c)) - | (Module1, Module1(_, c, _)) - | (Module2, Module2(_, _, c)) - | (Dot1, Dot1(c, _)) - | (Dot2, Dot2(_, c)) - | (Fun, Fun(_, _, c, _)) - | (FixF, FixF(_, _, c)) - | (TypAp, TypAp(c, _)) - | (Ap1, Ap1(c, _)) - | (Ap2, Ap2(_, c)) - | (BinBoolOp1, BinBoolOp1(_, c, _)) - | (BinBoolOp2, BinBoolOp2(_, _, c)) - | (BinIntOp1, BinIntOp1(_, c, _)) - | (BinIntOp2, BinIntOp2(_, _, c)) - | (BinFloatOp1, BinFloatOp1(_, c, _)) - | (BinFloatOp2, BinFloatOp2(_, _, c)) - | (BinStringOp1, BinStringOp1(_, c, _)) - | (BinStringOp2, BinStringOp2(_, _, c)) - | (IfThenElse1, IfThenElse1(_, c, _, _)) - | (IfThenElse2, IfThenElse2(_, _, c, _)) - | (IfThenElse3, IfThenElse3(_, _, _, c)) - | (Cons1, Cons1(c, _)) - | (Cons2, Cons2(_, c)) - | (ListConcat1, ListConcat1(c, _)) - | (ListConcat2, ListConcat2(_, c)) - | (Test, Test(_, c)) - | (Prj, Prj(c, _)) => Some(c) - | (ListLit(n), ListLit(_, _, _, c, (ld, _))) - | (Tuple(n), Tuple(c, (ld, _))) => - if (List.length(ld) == n) { - Some(c); - } else { - None; - } - | (ConsistentCaseRule(n), ConsistentCaseRule(_, _, c, (ld, _), _)) - | ( - InconsistentBranchesRule(n), - InconsistentBranchesRule(_, _, _, _, c, (ld, _), _), - ) => - if (List.length(ld) == n) { - Some(c); - } else { - None; - } - | (InconsistentBranches, InconsistentBranches(_, _, Case(scrut, _, _))) => - Some(scrut) - | (ConsistentCase, ConsistentCase(Case(scrut, _, _))) => Some(scrut) - | (Cast, Cast(c, _, _)) - | (FailedCastCast, FailedCast(Cast(c, _, _), _, _)) - | (FailedCast, FailedCast(c, _, _)) => Some(c) - | (Ap1, Ap2(_, _)) - | (Ap2, Ap1(_, _)) - | (IfThenElse1, IfThenElse2(_)) - | (IfThenElse1, IfThenElse3(_)) - | (IfThenElse2, IfThenElse1(_)) - | (IfThenElse2, IfThenElse3(_)) - | (IfThenElse3, IfThenElse1(_)) - | (IfThenElse3, IfThenElse2(_)) - | (Let1, Let2(_)) - | (Let2, Let1(_)) - | (Module1, Module2(_)) - | (Module2, Module1(_)) - | (Dot1, Dot2(_, _)) - | (Dot2, Dot1(_, _)) - | (BinBoolOp1, BinBoolOp2(_)) - | (BinBoolOp2, BinBoolOp1(_)) - | (BinIntOp1, BinIntOp2(_)) - | (BinIntOp2, BinIntOp1(_)) - | (BinFloatOp1, BinFloatOp2(_)) - | (BinFloatOp2, BinFloatOp1(_)) - | (BinStringOp1, BinStringOp2(_)) - | (BinStringOp2, BinStringOp1(_)) - | (Cons1, Cons2(_)) - | (Cons2, Cons1(_)) - | (Sequence1, Sequence2(_)) - | (Sequence2, Sequence1(_)) - | (ListConcat1, ListConcat2(_)) - | (ListConcat2, ListConcat1(_)) => None - | (FilterPattern, _) => None - | (Filter, _) => Some(ctx) - | (tag, Filter(_, c)) => unwrap(c, tag) - | (Closure, _) => Some(ctx) - | (tag, Closure(_, c)) => unwrap(c, tag) - | (Cast, _) => Some(ctx) - | (tag, Cast(c, _, _)) => unwrap(c, tag) - | (_, Mark) => None - | (_, _) => - // print_endline( - // Sexplib.Sexp.to_string_hum(sexp_of_cls(tag)) - // ++ " does not match with " - // ++ Sexplib.Sexp.to_string_hum(sexp_of_t(ctx)), - // ); - None - // raise(EvaluatorError.Exception(StepDoesNotMatch)); }; }; diff --git a/src/haz3lcore/dynamics/Evaluator.re b/src/haz3lcore/dynamics/Evaluator.re index 5395627ff3..fb877accd7 100644 --- a/src/haz3lcore/dynamics/Evaluator.re +++ b/src/haz3lcore/dynamics/Evaluator.re @@ -1,17 +1,43 @@ -open EvaluatorResult; open Transition; -module EvaluatorEVMode: { - type result_unfinished = +module Result = { + [@deriving (show({with_path: false}), sexp, yojson)] + type t = | BoxedValue(DHExp.t) - | Indet(DHExp.t) - | Uneval(DHExp.t); - let unbox: result_unfinished => DHExp.t; + | Indet(DHExp.t); + + let unbox = + fun + | BoxedValue(d) + | Indet(d) => d; + + let fast_equal = (r1, r2) => + switch (r1, r2) { + | (BoxedValue(d1), BoxedValue(d2)) + | (Indet(d1), Indet(d2)) => DHExp.fast_equal(d1, d2) + | _ => false + }; +}; + +open Result; + +module EvaluatorEVMode: { + type status = + | BoxedValue + | Indet + | Uneval; include EV_MODE with - type state = ref(EvaluatorState.t) and type result = result_unfinished; + type state = ref(EvaluatorState.t) and type result = (status, DHExp.t); } = { + type status = + | BoxedValue + | Indet + | Uneval; + + type result = (status, DHExp.t); + type reqstate = | BoxedReady | IndetReady @@ -34,24 +60,11 @@ module EvaluatorEVMode: { let update_test = (state, id, v) => state := EvaluatorState.add_test(state^, id, v); - type result_unfinished = - | BoxedValue(DHExp.t) - | Indet(DHExp.t) - | Uneval(DHExp.t); - - type result = result_unfinished; - - let unbox = - fun - | BoxedValue(x) - | Indet(x) - | Uneval(x) => x; - let req_value = (f, _, x) => switch (f(x)) { - | BoxedValue(x) => (BoxedReady, x) - | Indet(x) => (IndetBlocked, x) - | Uneval(_) => failwith("Unexpected Uneval") + | (BoxedValue, x) => (BoxedReady, x) + | (Indet, x) => (IndetBlocked, x) + | (Uneval, _) => failwith("Unexpected Uneval") }; let rec req_all_value = (f, i) => @@ -65,9 +78,9 @@ module EvaluatorEVMode: { let req_final = (f, _, x) => switch (f(x)) { - | BoxedValue(x) => (BoxedReady, x) - | Indet(x) => (IndetReady, x) - | Uneval(_) => failwith("Unexpected Uneval") + | (BoxedValue, x) => (BoxedReady, x) + | (Indet, x) => (IndetReady, x) + | (Uneval, _) => failwith("Unexpected Uneval") }; let rec req_all_final = (f, i) => @@ -79,20 +92,33 @@ module EvaluatorEVMode: { (r1 && r2, [x', ...xs']); }; + let req_final_or_value = (f, _, x) => + switch (f(x)) { + | (BoxedValue, x) => (BoxedReady, (x, true)) + | (Indet, x) => (IndetReady, (x, false)) + | (Uneval, _) => failwith("Unexpected Uneval") + }; + let otherwise = (_, c) => (BoxedReady, (), c); let (and.) = ((r1, x1, c1), (r2, x2)) => (r1 && r2, (x1, x2), c1(x2)); let (let.) = ((r, x, c), s) => switch (r, s(x)) { - | (BoxedReady, Step({apply, value: true, _})) => BoxedValue(apply()) - | (IndetReady, Step({apply, value: true, _})) => Indet(apply()) - | (BoxedReady, Step({apply, value: false, _})) - | (IndetReady, Step({apply, value: false, _})) => Uneval(apply()) - | (BoxedReady, Constructor) => BoxedValue(c) - | (IndetReady, Constructor) => Indet(c) - | (IndetBlocked, _) => Indet(c) - | (_, Indet) => Indet(c) + | (BoxedReady, Step({expr, state_update, is_value: true, _})) => + state_update(); + (BoxedValue, expr); + | (IndetReady, Step({expr, state_update, is_value: true, _})) => + state_update(); + (Indet, expr); + | (BoxedReady, Step({expr, state_update, is_value: false, _})) + | (IndetReady, Step({expr, state_update, is_value: false, _})) => + state_update(); + (Uneval, expr); + | (BoxedReady, Constructor) => (BoxedValue, c) + | (IndetReady, Constructor) => (Indet, c) + | (IndetBlocked, _) => (Indet, c) + | (_, Indet) => (Indet, c) }; }; module Eval = Transition(EvaluatorEVMode); @@ -100,21 +126,21 @@ module Eval = Transition(EvaluatorEVMode); let rec evaluate = (state, env, d) => { let u = Eval.transition(evaluate, state, env, d); switch (u) { - | BoxedValue(x) => BoxedValue(x) - | Indet(x) => Indet(x) - | Uneval(x) => evaluate(state, env, x) + | (BoxedValue, x) => (BoxedValue, x) + | (Indet, x) => (Indet, x) + | (Uneval, x) => evaluate(state, env, x) }; }; -let evaluate = (env, d): (EvaluatorState.t, EvaluatorResult.t) => { +let evaluate = (env, {d}: Elaborator.Elaboration.t) => { let state = ref(EvaluatorState.init); let env = ClosureEnvironment.of_environment(env); let result = evaluate(state, env, d); let result = switch (result) { - | BoxedValue(x) => BoxedValue(x) - | Indet(x) => Indet(x) - | Uneval(x) => Indet(x) + | (BoxedValue, x) => BoxedValue(x |> DHExp.repair_ids) + | (Indet, x) => Indet(x |> DHExp.repair_ids) + | (Uneval, x) => Indet(x |> DHExp.repair_ids) }; (state^, result); }; diff --git a/src/haz3lcore/dynamics/Evaluator.rei b/src/haz3lcore/dynamics/Evaluator.rei deleted file mode 100644 index 0589b7fe3f..0000000000 --- a/src/haz3lcore/dynamics/Evaluator.rei +++ /dev/null @@ -1,34 +0,0 @@ -/** - // TODO[Matt]: find where this comment belongs - [evaluate builtins env d] is [(es, r)], where [r] is the result of evaluating [d] and - [es] is the accumulated state. - */ -open Transition; - -let evaluate: - (Environment.t, DHExp.t) => (EvaluatorState.t, EvaluatorResult.t); - -module EvaluatorEVMode: { - type result_unfinished = - | BoxedValue(DHExp.t) - | Indet(DHExp.t) - | Uneval(DHExp.t); - - let unbox: result_unfinished => DHExp.t; - - include - EV_MODE with - type state = ref(EvaluatorState.t) and type result = result_unfinished; -}; - -module Eval: { - let transition: - ( - (EvaluatorEVMode.state, ClosureEnvironment.t, DHExp.t) => - EvaluatorEVMode.result_unfinished, - EvaluatorEVMode.state, - ClosureEnvironment.t, - DHExp.t - ) => - EvaluatorEVMode.result_unfinished; -}; diff --git a/src/haz3lcore/dynamics/EvaluatorError.re b/src/haz3lcore/dynamics/EvaluatorError.re index 86c1e53eaa..5724d69b77 100644 --- a/src/haz3lcore/dynamics/EvaluatorError.re +++ b/src/haz3lcore/dynamics/EvaluatorError.re @@ -1,10 +1,9 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type t = | OutOfFuel | StepDoesNotMatch - | FreeInvalidVar(Var.t) | BadPatternMatch | CastBVHoleGround(DHExp.t) | InvalidBoxedTypFun(DHExp.t) @@ -15,6 +14,7 @@ type t = | InvalidBoxedFloatLit(DHExp.t) | InvalidBoxedListLit(DHExp.t) | InvalidBoxedStringLit(DHExp.t) + | InvalidBoxedSumConstructor(DHExp.t) | InvalidBoxedTuple(DHExp.t) | InvalidBuiltin(string) | BadBuiltinAp(string, list(DHExp.t)) diff --git a/src/haz3lcore/dynamics/EvaluatorError.rei b/src/haz3lcore/dynamics/EvaluatorError.rei deleted file mode 100644 index 7c4a8b8a53..0000000000 --- a/src/haz3lcore/dynamics/EvaluatorError.rei +++ /dev/null @@ -1,22 +0,0 @@ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = - | OutOfFuel - | StepDoesNotMatch - | FreeInvalidVar(Var.t) - | BadPatternMatch - | CastBVHoleGround(DHExp.t) - | InvalidBoxedTypFun(DHExp.t) - | InvalidBoxedFun(DHExp.t) - | InvalidBoxedModule(DHExp.t) - | InvalidBoxedBoolLit(DHExp.t) - | InvalidBoxedIntLit(DHExp.t) - | InvalidBoxedFloatLit(DHExp.t) - | InvalidBoxedListLit(DHExp.t) - | InvalidBoxedStringLit(DHExp.t) - | InvalidBoxedTuple(DHExp.t) - | InvalidBuiltin(string) - | BadBuiltinAp(string, list(DHExp.t)) - | InvalidProjection(int); - -[@deriving (show({with_path: false}), sexp, yojson)] -exception Exception(t); diff --git a/src/haz3lcore/dynamics/EvaluatorPost.re b/src/haz3lcore/dynamics/EvaluatorPost.re deleted file mode 100644 index 25dceb28d5..0000000000 --- a/src/haz3lcore/dynamics/EvaluatorPost.re +++ /dev/null @@ -1,646 +0,0 @@ -module PpMonad = { - include Util.StateMonad.Make({ - [@deriving sexp] - type t = (EnvironmentIdMap.t(ClosureEnvironment.t), HoleInstanceInfo_.t); - }); - - open Syntax; - - let get_pe = get >>| (((pe, _)) => pe); - let pe_add = (ei, env) => - modify(((pe, hii)) => (pe |> EnvironmentIdMap.add(ei, env), hii)); - - let hii_add_instance = (u, env) => - modify'(((pe, hii)) => { - let (hii, i) = HoleInstanceInfo_.add_instance(hii, u, env); - (i, (pe, hii)); - }); -}; - -open PpMonad; -open PpMonad.Syntax; -open DHExp; - -type m('a) = PpMonad.t('a); - -[@deriving (show({with_path: false}), sexp, yojson)] -type error = - | ClosureInsideClosure - | FixFOutsideClosureEnv - | UnevalOutsideClosure - | InvalidClosureBody - | PostprocessedNonHoleInClosure - | PostprocessedHoleOutsideClosure; - -[@deriving (show({with_path: false}), sexp, yojson)] -exception Exception(error); - -/** - Postprocess inside evaluation boundary. - */ -let rec pp_eval = (d: DHExp.t): m(DHExp.t) => - switch (d) { - /* Non-hole expressions: recurse through subexpressions */ - | Test(_) - | BoolLit(_) - | IntLit(_) - | FloatLit(_) - | StringLit(_) - | ModuleVal(_) - | Constructor(_) => d |> return - - | Sequence(d1, d2) => - let* d1' = pp_eval(d1); - let+ d2' = pp_eval(d2); - Sequence(d1', d2'); - - | Filter(f, dbody) => - let+ dbody' = pp_eval(dbody); - Filter(f, dbody'); - - | Ap(d1, d2) => - let* d1' = pp_eval(d1); - let* d2' = pp_eval(d2); - Ap(d1', d2') |> return; - - | Dot(d1, d2) => - let* d1' = pp_eval(d1); - let* d2' = pp_eval(d2); - Dot(d1', d2') |> return; - | TypAp(d1, ty) => - let* d1' = pp_eval(d1); - TypAp(d1', ty) |> return; - - | ApBuiltin(f, d1) => - let* d1' = pp_eval(d1); - ApBuiltin(f, d1') |> return; - - | BinBoolOp(op, d1, d2) => - let* d1' = pp_eval(d1); - let* d2' = pp_eval(d2); - BinBoolOp(op, d1', d2') |> return; - - | BuiltinFun(f) => BuiltinFun(f) |> return - - | BinIntOp(op, d1, d2) => - let* d1' = pp_eval(d1); - let* d2' = pp_eval(d2); - BinIntOp(op, d1', d2') |> return; - - | BinFloatOp(op, d1, d2) => - let* d1' = pp_eval(d1); - let* d2' = pp_eval(d2); - BinFloatOp(op, d1', d2') |> return; - - | BinStringOp(op, d1, d2) => - let* d1' = pp_eval(d1); - let* d2' = pp_eval(d2); - BinStringOp(op, d1', d2') |> return; - - | Cons(d1, d2) => - let* d1' = pp_eval(d1); - let* d2' = pp_eval(d2); - Cons(d1', d2') |> return; - - | ListConcat(d1, d2) => - let* d1' = pp_eval(d1); - let* d2' = pp_eval(d2); - ListConcat(d1', d2') |> return; - - | ListLit(a, b, c, ds) => - let+ ds = - ds - |> List.fold_left( - (ds, d) => { - let* ds = ds; - let+ d = pp_eval(d); - ds @ [d]; - }, - return([]), - ); - ListLit(a, b, c, ds); - - | Tuple(ds) => - let+ ds = - ds - |> List.fold_left( - (ds, d) => { - let* ds = ds; - let+ d = pp_eval(d); - ds @ [d]; - }, - return([]), - ); - Tuple(ds); - - | Prj(d, n) => - let+ d = pp_eval(d); - Prj(d, n); - - | Cast(d', ty1, ty2) => - let* d'' = pp_eval(d'); - Cast(d'', ty1, ty2) |> return; - - | FailedCast(d', ty1, ty2) => - let* d'' = pp_eval(d'); - FailedCast(d'', ty1, ty2) |> return; - - | InvalidOperation(d', reason) => - let* d'' = pp_eval(d'); - InvalidOperation(d'', reason) |> return; - - | IfThenElse(consistent, c, d1, d2) => - let* c' = pp_eval(c); - let* d1' = pp_eval(d1); - let* d2' = pp_eval(d2); - IfThenElse(consistent, c', d1', d2') |> return; - - /* These expression forms should not exist outside closure in evaluated result */ - | BoundVar(_) - | Let(_) - | Module(_) - | ConsistentCase(_) - | Fun(_) - | TypFun(_) - | EmptyHole(_) - | NonEmptyHole(_) - | FreeVar(_) - | InvalidText(_) - | InconsistentBranches(_) => raise(Exception(UnevalOutsideClosure)) - - | FixF(_) => raise(Exception(FixFOutsideClosureEnv)) - - /* Closure: postprocess environment, then postprocess `d'`. - - Some parts of `d'` may lie inside and outside the evaluation boundary, - use `pp_eval` and `pp_uneval` as necessary. - */ - | Closure(env, d) => - let* env = - Util.TimeUtil.measure_time("pp_eval_env/Closure", true, () => - pp_eval_env(env) - ); - switch (d) { - /* Non-hole constructs inside closures. */ - | Fun(dp, ty, d, s) => - let* d = pp_uneval(env, d); - Fun(dp, ty, d, s) |> return; - - | TypFun(tpat, d1, s) => - let* d1' = pp_uneval(env, d1); - TypFun(tpat, d1', s) |> return; - - | Let(dp, d1, d2) => - /* d1 should already be evaluated, d2 is not */ - let* d1 = pp_eval(d1); - let* d2 = pp_uneval(env, d2); - Let(dp, d1, d2) |> return; - - | Module(dp, d1, d2) => - /* d1 should already be evaluated, d2 is not */ - let* d1 = pp_eval(d1); - let* d2 = pp_uneval(env, d2); - Let(dp, d1, d2) |> return; - - | ConsistentCase(Case(scrut, rules, i)) => - /* scrut should already be evaluated, rule bodies are not */ - let* scrut = - Util.TimeUtil.measure_time("pp_eval(scrut)", true, () => - pp_eval(scrut) - ); - let* rules = - Util.TimeUtil.measure_time("pp_uneval_rules", true, () => - pp_uneval_rules(env, rules) - ); - ConsistentCase(Case(scrut, rules, i)) |> return; - - /* Hole constructs inside closures. - - `NonEmptyHole` and `InconsistentBranches` have subexpressions that - lie inside the evaluation boundary, and need to be handled differently - than in `pp_uneval`. The other hole types don't have any evaluated - subexpressions and we can use `pp_uneval`. - */ - | NonEmptyHole(reason, u, _, d) => - let* d = pp_eval(d); - let* i = hii_add_instance(u, env); - Closure(env, NonEmptyHole(reason, u, i, d)) |> return; - - | InconsistentBranches(u, _, Case(scrut, rules, case_i)) => - let* scrut = pp_eval(scrut); - let* i = hii_add_instance(u, env); - Closure(env, InconsistentBranches(u, i, Case(scrut, rules, case_i))) - |> return; - - | EmptyHole(_) - | FreeVar(_) - | InvalidText(_) => pp_uneval(env, d) - - /* Other expression forms cannot be directly in a closure. */ - | _ => raise(Exception(InvalidClosureBody)) - }; - } - -/* Recurse through environments, using memoized result if available. */ -and pp_eval_env = (env: ClosureEnvironment.t): m(ClosureEnvironment.t) => { - let ei = env |> ClosureEnvironment.id_of; - - let* pe = get_pe; - switch (pe |> EnvironmentIdMap.find_opt(ei)) { - | Some(env) => env |> return - | None => - let* env = - env - |> ClosureEnvironment.fold( - ((x, d), env') => { - let* env' = env'; - let* d' = - switch (d) { - | FixF(f, ty, d1) => - let+ d1 = pp_uneval(env', d1); - FixF(f, ty, d1); - | d => pp_eval(d) - }; - ClosureEnvironment.extend(env', (x, d')) |> return; - }, - Environment.empty |> ClosureEnvironment.wrap(ei) |> return, - ); - - let* () = pe_add(ei, env); - env |> return; - }; -} - -/** - Postprocess inside evaluation boundary. Environment should already be - postprocessed. - */ -and pp_uneval = (env: ClosureEnvironment.t, d: DHExp.t): m(DHExp.t) => - switch (d) { - /* Bound variables should be looked up within the closure - environment. If lookup fails, then variable is not bound. */ - | BoundVar(x) => - switch (ClosureEnvironment.lookup(env, x)) { - | Some(d') => d' |> return - | None => d |> return - } - - /* Non-hole expressions: expand recursively */ - | BoolLit(_) - | IntLit(_) - | FloatLit(_) - | StringLit(_) - | ModuleVal(_) - | Constructor(_) => d |> return - - | Test(id, d1) => - let+ d1' = pp_uneval(env, d1); - Test(id, d1'); - - | Sequence(d1, d2) => - let* d1' = pp_uneval(env, d1); - let+ d2' = pp_uneval(env, d2); - Sequence(d1', d2'); - - | Filter(flt, dbody) => - let+ dbody' = pp_uneval(env, dbody); - Filter(flt, dbody'); - | Let(dp, d1, d2) => - let* d1' = pp_uneval(env, d1); - let* d2' = pp_uneval(env, d2); - Let(dp, d1', d2') |> return; - - | Module(dp, d1, d2) => - let* d1' = pp_uneval(env, d1); - let* d2' = pp_uneval(env, d2); - Module(dp, d1', d2') |> return; - - | Dot(d1, d2) => - let* d1' = pp_uneval(env, d1); - let* d2' = pp_uneval(env, d2); - Dot(d1', d2') |> return; - - | FixF(f, ty, d1) => - let* d1' = pp_uneval(env, d1); - FixF(f, ty, d1') |> return; - - | Fun(dp, ty, d', s) => - let* d'' = pp_uneval(env, d'); - Fun(dp, ty, d'', s) |> return; - - | TypFun(tpat, d1, s) => - let* d1' = pp_uneval(env, d1); - TypFun(tpat, d1', s) |> return; - - | Ap(d1, d2) => - let* d1' = pp_uneval(env, d1); - let* d2' = pp_uneval(env, d2); - Ap(d1', d2') |> return; - - | TypAp(d1, ty) => - let* d1' = pp_uneval(env, d1); - TypAp(d1', ty) |> return; - - | ApBuiltin(f, d1) => - let* d1' = pp_uneval(env, d1); - ApBuiltin(f, d1') |> return; - - | BuiltinFun(f) => BuiltinFun(f) |> return - - | BinBoolOp(op, d1, d2) => - let* d1' = pp_uneval(env, d1); - let* d2' = pp_uneval(env, d2); - BinBoolOp(op, d1', d2') |> return; - | BinIntOp(op, d1, d2) => - let* d1' = pp_uneval(env, d1); - let* d2' = pp_uneval(env, d2); - BinIntOp(op, d1', d2') |> return; - - | BinFloatOp(op, d1, d2) => - let* d1' = pp_uneval(env, d1); - let* d2' = pp_uneval(env, d2); - BinFloatOp(op, d1', d2') |> return; - - | BinStringOp(op, d1, d2) => - let* d1' = pp_uneval(env, d1); - let* d2' = pp_uneval(env, d2); - BinStringOp(op, d1', d2') |> return; - - | IfThenElse(consistent, c, d1, d2) => - let* c' = pp_uneval(env, c); - let* d1' = pp_uneval(env, d1); - let* d2' = pp_uneval(env, d2); - IfThenElse(consistent, c', d1', d2') |> return; - - | Cons(d1, d2) => - let* d1' = pp_uneval(env, d1); - let* d2' = pp_uneval(env, d2); - Cons(d1', d2') |> return; - - | ListConcat(d1, d2) => - let* d1' = pp_uneval(env, d1); - let* d2' = pp_uneval(env, d2); - ListConcat(d1', d2') |> return; - - | ListLit(a, b, c, ds) => - let+ ds = - ds - |> List.fold_left( - (ds, d) => { - let* ds = ds; - let+ d = pp_uneval(env, d); - ds @ [d]; - }, - return([]), - ); - ListLit(a, b, c, ds); - - | Tuple(ds) => - let+ ds = - ds - |> List.fold_left( - (ds, d) => { - let* ds = ds; - let+ d = pp_uneval(env, d); - ds @ [d]; - }, - return([]), - ); - Tuple(ds); - - | Prj(d, n) => - let+ d = pp_uneval(env, d); - Prj(d, n); - - | Cast(d', ty1, ty2) => - let* d'' = pp_uneval(env, d'); - Cast(d'', ty1, ty2) |> return; - - | FailedCast(d', ty1, ty2) => - let* d'' = pp_uneval(env, d'); - FailedCast(d'', ty1, ty2) |> return; - - | InvalidOperation(d', reason) => - let* d'' = pp_uneval(env, d'); - InvalidOperation(d'', reason) |> return; - - | ConsistentCase(Case(scrut, rules, i)) => - let* scrut' = pp_uneval(env, scrut); - let* rules' = pp_uneval_rules(env, rules); - ConsistentCase(Case(scrut', rules', i)) |> return; - - /* Closures shouldn't exist inside other closures */ - | Closure(_) => raise(Exception(ClosureInsideClosure)) - - /* Hole expressions: - - Use the closure environment as the hole environment. - - Number the hole instance appropriately. - - Recurse through inner expression (if any). - */ - | EmptyHole(u, _) => - let* i = hii_add_instance(u, env); - Closure(env, EmptyHole(u, i)) |> return; - - | NonEmptyHole(reason, u, _, d') => - let* d' = pp_uneval(env, d'); - let* i = hii_add_instance(u, env); - Closure(env, NonEmptyHole(reason, u, i, d')) |> return; - - | FreeVar(u, _, x) => - let* i = hii_add_instance(u, env); - Closure(env, FreeVar(u, i, x)) |> return; - - | InvalidText(u, _, text) => - let* i = hii_add_instance(u, env); - Closure(env, InvalidText(u, i, text)) |> return; - - | InconsistentBranches(u, _, Case(scrut, rules, case_i)) => - let* scrut = pp_uneval(env, scrut); - let* rules = pp_uneval_rules(env, rules); - let* i = hii_add_instance(u, env); - Closure(env, InconsistentBranches(u, i, Case(scrut, rules, case_i))) - |> return; - } - -and pp_uneval_rules = - (env: ClosureEnvironment.t, rules: list(DHExp.rule)) - : m(list(DHExp.rule)) => { - rules - |> List.map((Rule(dp, d)) => { - let* d' = pp_uneval(env, d); - Rule(dp, d') |> return; - }) - |> sequence; -}; - -/** - Tracking children of hole instances. A hole instance is a child of another hole - instance if it exists in the hole environment of the parent. - - This is the second stage of postprocessing, separate from hole numbering and - substitution, since memoization becomes much more convoluted if these two - stages are combined. - - This works by simply iterating over all the (postprocessed) hole instance - environments in the HoleInstanceInfo_.t and looking for "child" holes. - */ -let rec track_children_of_hole = - (hii: HoleInstanceInfo.t, parent: HoleInstanceParents.t_, d: DHExp.t) - : HoleInstanceInfo.t => - switch (d) { - | Constructor(_) - | BoolLit(_) - | IntLit(_) - | FloatLit(_) - | StringLit(_) - | ModuleVal(_) - | BuiltinFun(_) - | BoundVar(_) => hii - | Test(_, d) - | FixF(_, _, d) - | Fun(_, _, d, _) - | TypFun(_, d, _) - | TypAp(d, _) - | Prj(d, _) - | Cast(d, _, _) - | FailedCast(d, _, _) - | InvalidOperation(d, _) => track_children_of_hole(hii, parent, d) - | Sequence(d1, d2) - | Let(_, d1, d2) - | Module(_, d1, d2) - | Ap(d1, d2) - | BinBoolOp(_, d1, d2) - | BinIntOp(_, d1, d2) - | BinFloatOp(_, d1, d2) - | BinStringOp(_, d1, d2) - | Dot(d1, d2) - | Cons(d1, d2) => - let hii = track_children_of_hole(hii, parent, d1); - track_children_of_hole(hii, parent, d2); - | ListConcat(d1, d2) => - let hii = track_children_of_hole(hii, parent, d1); - track_children_of_hole(hii, parent, d2); - - | ListLit(_, _, _, ds) => - List.fold_right( - (d, hii) => track_children_of_hole(hii, parent, d), - ds, - hii, - ) - - | Tuple(ds) => - List.fold_right( - (d, hii) => track_children_of_hole(hii, parent, d), - ds, - hii, - ) - | IfThenElse(_, c, d1, d2) => - let hii = track_children_of_hole(hii, parent, c); - let hii = track_children_of_hole(hii, parent, d1); - track_children_of_hole(hii, parent, d2); - - | ConsistentCase(Case(scrut, rules, _)) => - let hii = - Util.TimeUtil.measure_time("track_children_of_hole(scrut)", true, () => - track_children_of_hole(hii, parent, scrut) - ); - Util.TimeUtil.measure_time("track_children_of_hole_rules", true, () => - track_children_of_hole_rules(hii, parent, rules) - ); - - | ApBuiltin(_, d) => track_children_of_hole(hii, parent, d) - - /* Hole types */ - | NonEmptyHole(_, u, i, d) => - let hii = track_children_of_hole(hii, parent, d); - hii |> HoleInstanceInfo.add_parent((u, i), parent); - | InconsistentBranches(u, i, Case(scrut, rules, _)) => - let hii = track_children_of_hole(hii, parent, scrut); - let hii = track_children_of_hole_rules(hii, parent, rules); - hii |> HoleInstanceInfo.add_parent((u, i), parent); - | EmptyHole(u, i) - | FreeVar(u, i, _) - | InvalidText(u, i, _) => - hii |> HoleInstanceInfo.add_parent((u, i), parent) - - /* The only thing that should exist in closures at this point - are holes. Ignore the hole environment, not necessary for - parent tracking. */ - | Filter(_, d) - | Closure(_, d) => track_children_of_hole(hii, parent, d) - } - -and track_children_of_hole_rules = - ( - hii: HoleInstanceInfo.t, - parent: HoleInstanceParents.t_, - rules: list(DHExp.rule), - ) - : HoleInstanceInfo.t => - List.fold_right( - (DHExp.Rule(_, d), hii) => track_children_of_hole(hii, parent, d), - rules, - hii, - ); - -/** - Driver for hole parent tracking; iterate through all hole instances in the - [HoleInstanceInfo.t], and call [track_children_of_hole] on them. - */ -let track_children = (hii: HoleInstanceInfo.t): HoleInstanceInfo.t => - MetaVarMap.fold( - (u, his, hii) => - List.fold_right( - ((i, (env, _)), hii) => - Environment.foldo( - ((x, d), hii) => track_children_of_hole(hii, (x, (u, i)), d), - hii, - env |> ClosureEnvironment.map_of, - ), - his |> List.mapi((i, hc) => (i, hc)), - hii, - ), - hii, - hii, - ); - -let postprocess = (d: DHExp.t): (HoleInstanceInfo.t, DHExp.t) => { - /* Substitution and hole numbering postprocessing */ - let ((_, hii), d) = - Util.TimeUtil.measure_time("pp_eval", true, () => - pp_eval(d, (EnvironmentIdMap.empty, HoleInstanceInfo_.empty)) - ); - - /* Build hole instance info. */ - let hii = - Util.TimeUtil.measure_time("to_hii", true, () => - hii |> HoleInstanceInfo_.to_hole_instance_info - ); - - /* Add special hole acting as top-level expression (to act as parent - for holes directly in the result) */ - /* FIXME: Better way to do this? */ - let (u_result, _) = HoleInstance.result; - let hii = - MetaVarMap.add( - u_result, - [ - ( - ClosureEnvironment.wrap( - EnvironmentId.invalid, - Environment.singleton(("", d)), - ), - [], - ), - ], - hii, - ); - - let hii = - Util.TimeUtil.measure_time("track_children", true, () => - hii |> track_children - ); - - /* Perform hole parent tracking. */ - (hii, d); -}; diff --git a/src/haz3lcore/dynamics/EvaluatorPost.rei b/src/haz3lcore/dynamics/EvaluatorPost.rei deleted file mode 100644 index 67cd0438a9..0000000000 --- a/src/haz3lcore/dynamics/EvaluatorPost.rei +++ /dev/null @@ -1,71 +0,0 @@ -/** - Postprocessing of the evaluation result. - - NOTE: Currently disabled due to exponential blow-up in certain situations, but - leaving here for now until we can fully investigate. - - This has two functions: - - Match the evaluation result generated by evaluation with substitution. - This means to continue evaluation within expressions for which evaluation - has not reached (e.g., lambda expression bodies, unmatched case and let - expression bodies), by looking up bound variables and assigning hole - environments. - - Number holes and generate a HoleInstanceInfo.t that holds information - about all unique hole instances in the result. - - The postprocessing steps are partially memoized by environments. (Only - memoized among hole instances which share the same environment.) - - Algorithmically, this algorithm begins in the evaluated region of the - evaluation result inside the "evaluation boundary" (pp_eval), and continues - to the region outside the evaluation boundary (pp_uneval). - */ - -/** - Errors related to EvalPostprocess.postprocess - - Postprocessing invalid cases: Evaluation boundary is abbreviated as "EB". "In - closure" and "outside closure" correspond to "outside the EB" and "inside the - EB," respectively. - - The following errors are used to indicate an invalid case DURING - postprocessing: - - - ClosureInsideClosure: an evaluated expression outside the EB - - BoundVarOutsideClosure: an un-looked-up (unevaluated) variable inside the EB - - UnevalOutsideClosure: non-variable unevaluated expression inside the EB - - InvalidClosureBody: closures currently only make sense storing the - following expression types: - - Hole expressions - - Lambda abstractions - - Let/case with a pattern match failure - - The following errors are used to indicate an invalid case AFTER postprocessing. - After postprocessing, closures around lambda abstractions, let expressions, and - case expressions should be removed, and all hole expressions should be wrapped - in a closure. - - - PostprocessedNoneHoleInClosure - - PostprocessedHoleOutsideClosure - */ -[@deriving (show({with_path: false}), sexp, yojson)] -type error = - | ClosureInsideClosure - | FixFOutsideClosureEnv - | UnevalOutsideClosure - | InvalidClosureBody - | PostprocessedNonHoleInClosure - | PostprocessedHoleOutsideClosure; - -[@deriving (show({with_path: false}), sexp, yojson)] -exception Exception(error); - -/** - Postprocessing driver. - - Note: The top-level expression is wrapped in a non-empty hole, this is a - clean way of noting holes that lie directly in the result. - - See also HoleInstanceInfo.rei/HoleInstanceInfo_.rei. - */ -let postprocess: DHExp.t => (HoleInstanceInfo.t, DHExp.t); diff --git a/src/haz3lcore/dynamics/EvaluatorResult.re b/src/haz3lcore/dynamics/EvaluatorResult.re deleted file mode 100644 index 73628a7c89..0000000000 --- a/src/haz3lcore/dynamics/EvaluatorResult.re +++ /dev/null @@ -1,16 +0,0 @@ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = - | BoxedValue(DHExp.t) - | Indet(DHExp.t); - -let unbox = - fun - | BoxedValue(d) - | Indet(d) => d; - -let fast_equal = (r1, r2) => - switch (r1, r2) { - | (BoxedValue(d1), BoxedValue(d2)) - | (Indet(d1), Indet(d2)) => DHExp.fast_equal(d1, d2) - | _ => false - }; diff --git a/src/haz3lcore/dynamics/EvaluatorResult.rei b/src/haz3lcore/dynamics/EvaluatorResult.rei deleted file mode 100644 index 350c3cec62..0000000000 --- a/src/haz3lcore/dynamics/EvaluatorResult.rei +++ /dev/null @@ -1,22 +0,0 @@ -/** - The output from {!val:Evaluator.evaluate}. - */ - -/** - The type for the evaluation result, a {!type:DHExp.t} wrapped in its {v final - v} judgment (boxed value or indeterminate). - */ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = - | BoxedValue(DHExp.t) - | Indet(DHExp.t); - -/** - [unbox r] is the inner expression. - */ -let unbox: t => DHExp.t; - -/** - See {!val:DHExp.fast_equal}. - */ -let fast_equal: (t, t) => bool; diff --git a/src/haz3lcore/dynamics/EvaluatorState.rei b/src/haz3lcore/dynamics/EvaluatorState.rei index e699190314..916ac0586b 100644 --- a/src/haz3lcore/dynamics/EvaluatorState.rei +++ b/src/haz3lcore/dynamics/EvaluatorState.rei @@ -28,7 +28,7 @@ let get_step: t => int; let put_step: (int, t) => t; -let add_test: (t, KeywordID.t, TestMap.instance_report) => t; +let add_test: (t, Id.t, TestMap.instance_report) => t; let get_tests: t => TestMap.t; diff --git a/src/haz3lcore/dynamics/EvaluatorStats.re b/src/haz3lcore/dynamics/EvaluatorStats.re index 6047b799ed..89917ceba7 100644 --- a/src/haz3lcore/dynamics/EvaluatorStats.re +++ b/src/haz3lcore/dynamics/EvaluatorStats.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type t = {step: int}; diff --git a/src/haz3lcore/dynamics/EvaluatorStep.re b/src/haz3lcore/dynamics/EvaluatorStep.re index 6956ed7eef..5b9e32b10f 100644 --- a/src/haz3lcore/dynamics/EvaluatorStep.re +++ b/src/haz3lcore/dynamics/EvaluatorStep.re @@ -5,17 +5,11 @@ type step = { d: DHExp.t, // technically can be calculated from d_loc and ctx state: EvaluatorState.t, d_loc: DHExp.t, // the expression at the location given by ctx + d_loc': DHExp.t, ctx: EvalCtx.t, knd: step_kind, }; -let unwrap = (step, sel: EvalCtx.cls) => - EvalCtx.unwrap(step.ctx, sel) |> Option.map(ctx => {...step, ctx}); - -let unwrap_unsafe = (step, sel: EvalCtx.cls) => - // TODO[Matt]: bring back "safe" version - EvalCtx.unwrap(step.ctx, sel) |> Option.map(ctx => {...step, ctx}); - module EvalObj = { [@deriving (show({with_path: false}), sexp, yojson)] type t = { @@ -59,7 +53,7 @@ module Decompose = { EV_MODE with type result = Result.t and type state = ref(EvaluatorState.t); } = { - type state = ref(EvaluatorState.t); // TODO[Matt]: Make sure this gets passed around correctly + type state = ref(EvaluatorState.t); type requirement('a) = (Result.t, 'a); type requirements('a, 'b) = ('b, Result.t, ClosureEnvironment.t, 'a); type result = Result.t; @@ -111,6 +105,17 @@ module Decompose = { ); }; + let req_final_or_value = (cont, wr, d) => { + switch (cont(d)) { + | Result.Indet => (Result.BoxedValue, (d, false)) + | Result.BoxedValue => (Result.BoxedValue, (d, true)) + | Result.Step(objs) => ( + Result.Step(List.map(EvalObj.wrap(wr), objs)), + (d, false), + ) + }; + }; + let rec req_all_final' = (cont, wr, ds') => fun | [] => (Result.BoxedValue, []) @@ -133,6 +138,8 @@ module Decompose = { | Constructor => Result.BoxedValue | Indet => Result.Indet | Step(s) => Result.Step([EvalObj.mk(Mark, env, undo, s.kind)]) + // TODO: Actually show these exceptions to the user! + | exception (EvaluatorError.Exception(_)) => Result.Indet } | (_, Result.Step(_) as r, _, _) => r }; @@ -172,9 +179,13 @@ module TakeStep = { let req_final = (_, _, d) => d; let req_all_final = (_, _, ds) => ds; + let req_final_or_value = (_, _, d) => (d, true); + let (let.) = (rq: requirements('a, DHExp.t), rl: 'a => rule) => switch (rl(rq)) { - | Step({apply, _}) => Some(apply()) + | Step({expr, state_update, _}) => + state_update(); + Some(expr); | Constructor | Indet => None }; @@ -195,159 +206,7 @@ module TakeStep = { let take_step = TakeStep.take_step; -let rec rev_concat: (list('a), list('a)) => list('a) = - (ls, rs) => { - switch (ls) { - | [] => rs - | [hd, ...tl] => rev_concat(tl, [hd, ...rs]) - }; - }; - -let rec compose = (ctx: EvalCtx.t, d: DHExp.t): DHExp.t => { - DHExp.( - switch (ctx) { - | Mark => d - | Closure(env, ctx) => - let d = compose(ctx, d); - Closure(env, d); - | Filter(flt, ctx) => - let d = compose(ctx, d); - Filter(flt, d); - | Sequence1(ctx, d2) => - let d1 = compose(ctx, d); - Sequence(d1, d2); - | Sequence2(d1, ctx) => - let d2 = compose(ctx, d); - Sequence(d1, d2); - | TypAp(ctx, typ) => - let d1 = compose(ctx, d); - TypAp(d1, typ); - | Ap1(ctx, d2) => - let d1 = compose(ctx, d); - Ap(d1, d2); - | Ap2(d1, ctx) => - let d2 = compose(ctx, d); - Ap(d1, d2); - | ApBuiltin(s, ctx) => - let d' = compose(ctx, d); - ApBuiltin(s, d'); - | IfThenElse1(c, ctx, d2, d3) => - let d' = compose(ctx, d); - IfThenElse(c, d', d2, d3); - | IfThenElse2(c, d1, ctx, d3) => - let d' = compose(ctx, d); - IfThenElse(c, d1, d', d3); - | IfThenElse3(c, d1, d2, ctx) => - let d' = compose(ctx, d); - IfThenElse(c, d1, d2, d'); - | Test(lit, ctx) => - let d1 = compose(ctx, d); - Test(lit, d1); - | BinBoolOp1(op, ctx, d2) => - let d1 = compose(ctx, d); - BinBoolOp(op, d1, d2); - | BinBoolOp2(op, d1, ctx) => - let d2 = compose(ctx, d); - BinBoolOp(op, d1, d2); - | BinIntOp1(op, ctx, d2) => - let d1 = compose(ctx, d); - BinIntOp(op, d1, d2); - | BinIntOp2(op, d1, ctx) => - let d2 = compose(ctx, d); - BinIntOp(op, d1, d2); - | BinFloatOp1(op, ctx, d2) => - let d1 = compose(ctx, d); - BinFloatOp(op, d1, d2); - | BinFloatOp2(op, d1, ctx) => - let d2 = compose(ctx, d); - BinFloatOp(op, d1, d2); - | BinStringOp1(op, ctx, d2) => - let d1 = compose(ctx, d); - BinStringOp(op, d1, d2); - | BinStringOp2(op, d1, ctx) => - let d2 = compose(ctx, d); - BinStringOp(op, d1, d2); - | Cons1(ctx, d2) => - let d1 = compose(ctx, d); - Cons(d1, d2); - | Cons2(d1, ctx) => - let d2 = compose(ctx, d); - Cons(d1, d2); - | ListConcat1(ctx, d2) => - let d1 = compose(ctx, d); - ListConcat(d1, d2); - | ListConcat2(d1, ctx) => - let d2 = compose(ctx, d); - ListConcat(d1, d2); - | Tuple(ctx, (ld, rd)) => - let d = compose(ctx, d); - Tuple(rev_concat(ld, [d, ...rd])); - | ListLit(m, i, t, ctx, (ld, rd)) => - let d = compose(ctx, d); - ListLit(m, i, t, rev_concat(ld, [d, ...rd])); - | Let1(dp, ctx, d2) => - let d = compose(ctx, d); - Let(dp, d, d2); - | Let2(dp, d1, ctx) => - let d = compose(ctx, d); - Let(dp, d1, d); - | Module1(dp, ctx, d2) => - let d = compose(ctx, d); - Module(dp, d, d2); - | Module2(dp, d1, ctx) => - let d = compose(ctx, d); - Module(dp, d1, d); - | Dot1(ctx, d2) => - let d1 = compose(ctx, d); - Dot(d1, d2); - | Dot2(d1, ctx) => - let d2 = compose(ctx, d); - Dot(d1, d2); - | Fun(dp, t, ctx, v) => - let d = compose(ctx, d); - Fun(dp, t, d, v); - | FixF(v, t, ctx) => - let d = compose(ctx, d); - FixF(v, t, d); - | Prj(ctx, n) => - let d = compose(ctx, d); - Prj(d, n); - | Cast(ctx, ty1, ty2) => - let d = compose(ctx, d); - Cast(d, ty1, ty2); - | FailedCast(ctx, ty1, ty2) => - let d = compose(ctx, d); - FailedCast(d, ty1, ty2); - | InvalidOperation(ctx, err) => - let d = compose(ctx, d); - InvalidOperation(d, err); - | NonEmptyHole(reason, u, i, ctx) => - let d = compose(ctx, d); - NonEmptyHole(reason, u, i, d); - | ConsistentCase(Case(ctx, rule, n)) => - let d = compose(ctx, d); - ConsistentCase(Case(d, rule, n)); - | ConsistentCaseRule(scr, p, ctx, (lr, rr), n) => - let d = compose(ctx, d); - ConsistentCase( - Case(scr, rev_concat(lr, [(Rule(p, d): DHExp.rule), ...rr]), n), - ); - | InconsistentBranches(u, i, Case(ctx, rule, n)) => - let d = compose(ctx, d); - InconsistentBranches(u, i, Case(d, rule, n)); - | InconsistentBranchesRule(scr, mv, hi, p, ctx, (lr, rr), n) => - let d = compose(ctx, d); - InconsistentBranches( - mv, - hi, - Case(scr, rev_concat(lr, [(Rule(p, d): DHExp.rule), ...rr]), n), - ); - } - ); -}; - -let decompose = (d: DHExp.t) => { - let es = EvaluatorState.init; +let decompose = (d: DHExp.t, es: EvaluatorState.t) => { let env = ClosureEnvironment.of_environment(Builtins.env_init); let rs = Decompose.decompose(ref(es), env, d); Decompose.Result.unbox(rs); @@ -363,170 +222,177 @@ let rec matches = idx: int, ) : (FilterAction.t, int, EvalCtx.t) => { - let composed = compose(ctx, exp); + let composed = EvalCtx.compose(ctx, exp); let (pact, pidx) = (act, idx); let (mact, midx) = FilterMatcher.matches(~env, ~exp=composed, ~act, flt); let (act, idx) = switch (ctx) { - | Filter(_, _) => (pact, pidx) + | Term({term: Filter(_, _), _}) => (pact, pidx) | _ => midx > pidx ? (mact, midx) : (pact, pidx) }; let map = ((a, i, c), f: EvalCtx.t => EvalCtx.t) => { (a, i, f(c)); }; let (let+) = map; - let (ract, ridx, rctx) = + let (ract, ridx, rctx) = { + let wrap_ids = (ids, ctx) => EvalCtx.Term({term: ctx, ids}); switch (ctx) { | Mark => (act, idx, EvalCtx.Mark) - | Closure(env, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Closure(env, ctx); - | Filter(Filter(flt'), ctx) => - let flt = flt |> FilterEnvironment.extends(flt'); - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Filter(Filter(flt'), ctx); - | Filter(Residue(idx', act'), ctx) => - let (ract, ridx, rctx) = - if (idx > idx') { - matches(env, flt, ctx, exp, act, idx); + | Term({term, ids}) => + switch (term) { + | Closure(env, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Closure(env, ctx) |> wrap_ids(ids); + | Filter(Filter(flt'), ctx) => + let flt = flt |> FilterEnvironment.extends(flt'); + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Filter(Filter(flt'), ctx) |> wrap_ids(ids); + | Filter(Residue(idx', act'), ctx) => + let (ract, ridx, rctx) = + if (idx > idx') { + matches(env, flt, ctx, exp, act, idx); + } else { + matches(env, flt, ctx, exp, act', idx'); + }; + if (act' |> snd == All) { + ( + ract, + ridx, + Term({ + term: Filter(Residue(idx', act'), rctx), + ids: [Id.mk()], + }), + ); } else { - matches(env, flt, ctx, exp, act', idx'); + (ract, ridx, rctx); }; - if (act' |> snd == All) { - (ract, ridx, Filter(Residue(idx', act'), rctx)); - } else { - (ract, ridx, rctx); - }; - | Sequence1(ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Sequence1(ctx, d2); - | Sequence2(d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Sequence2(d1, ctx); - | Let1(d1, ctx, d3) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Let1(d1, ctx, d3); - | Let2(d1, d2, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Let2(d1, d2, ctx); - | Module1(d1, ctx, d3) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Module1(d1, ctx, d3); - | Module2(d1, d2, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Module2(d1, d2, ctx); - | Dot1(ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Dot1(ctx, d2); - | Dot2(d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Dot2(d1, ctx); - | Fun(dp, ty, ctx, name) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Fun(dp, ty, ctx, name); - | FixF(name, ty, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - FixF(name, ty, ctx); - | Ap1(ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Ap1(ctx, d2); - | Ap2(d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Ap2(d1, ctx); - | IfThenElse1(c, ctx, d2, d3) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - IfThenElse1(c, ctx, d2, d3); - | IfThenElse2(c, d1, ctx, d3) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - IfThenElse2(c, d1, ctx, d3); - | IfThenElse3(c, d1, d2, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - IfThenElse3(c, d1, d2, ctx); - | BinBoolOp1(op, ctx, d1) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinBoolOp1(op, ctx, d1); - | BinBoolOp2(op, d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinBoolOp2(op, d1, ctx); - | BinIntOp1(op, ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinIntOp1(op, ctx, d2); - | BinIntOp2(op, d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinIntOp2(op, d1, ctx); - | BinFloatOp1(op, ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinFloatOp1(op, ctx, d2); - | BinFloatOp2(op, d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinFloatOp2(op, d1, ctx); - | BinStringOp1(op, ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinStringOp1(op, ctx, d2); - | BinStringOp2(op, d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinStringOp2(op, d1, ctx); - | Tuple(ctx, ds) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Tuple(ctx, ds); - | ApBuiltin(name, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - ApBuiltin(name, ctx); - | Test(id, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Test(id, ctx); - | ListLit(u, i, ty, ctx, ds) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - ListLit(u, i, ty, ctx, ds); - | Cons1(ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Cons1(ctx, d2); - | Cons2(d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Cons2(d1, ctx); - | ListConcat1(ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - ListConcat1(ctx, d2); - | ListConcat2(d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - ListConcat2(d1, ctx); - | Prj(ctx, n) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Prj(ctx, n); - | NonEmptyHole(e, u, i, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - NonEmptyHole(e, u, i, ctx); - | Cast(ctx, ty, ty') => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Cast(ctx, ty, ty'); - | FailedCast(ctx, ty, ty') => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - FailedCast(ctx, ty, ty'); - | InvalidOperation(ctx, error) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - InvalidOperation(ctx, error); - | ConsistentCase(Case(ctx, rs, i)) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - ConsistentCase(Case(ctx, rs, i)); - | ConsistentCaseRule(dexp, dpat, ctx, rs, i) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - ConsistentCaseRule(dexp, dpat, ctx, rs, i); - | InconsistentBranches(u, i, Case(ctx, rs, ri)) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - InconsistentBranches(u, i, Case(ctx, rs, ri)); - | InconsistentBranchesRule(dexp, u, i, dpat, ctx, rs, ri) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - InconsistentBranchesRule(dexp, u, i, dpat, ctx, rs, ri); - | TypAp(ctx, ty) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - TypAp(ctx, ty); + | Seq1(ctx, d2) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Seq1(ctx, d2) |> wrap_ids(ids); + | Seq2(d1, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Seq2(d1, ctx) |> wrap_ids(ids); + | Let1(d1, ctx, d3) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Let1(d1, ctx, d3) |> wrap_ids(ids); + | Let2(d1, d2, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Let2(d1, d2, ctx) |> wrap_ids(ids); + | Module1(d1, ctx, d3) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Module1(d1, ctx, d3) |> wrap_ids(ids); + | Module2(d1, d2, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Module2(d1, d2, ctx) |> wrap_ids(ids); + | Dot1(ctx, d2) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Dot1(ctx, d2) |> wrap_ids(ids); + | Dot2(d1, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Dot2(d1, ctx) |> wrap_ids(ids); + | Fun(dp, ctx, env', name) => + let+ ctx = + matches( + env' |> Option.value(~default=env), + flt, + ctx, + exp, + act, + idx, + ); + Fun(dp, ctx, env', name) |> wrap_ids(ids); + | FixF(name, ctx, env') => + let+ ctx = + matches( + env' |> Option.value(~default=env), + flt, + ctx, + exp, + act, + idx, + ); + FixF(name, ctx, env') |> wrap_ids(ids); + | Ap1(dir, ctx, d2) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Ap1(dir, ctx, d2) |> wrap_ids(ids); + | Ap2(dir, d1, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Ap2(dir, d1, ctx) |> wrap_ids(ids); + | If1(ctx, d2, d3) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + If1(ctx, d2, d3) |> wrap_ids(ids); + | If2(d1, ctx, d3) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + If2(d1, ctx, d3) |> wrap_ids(ids); + | If3(d1, d2, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + If3(d1, d2, ctx) |> wrap_ids(ids); + | BinOp1(op, ctx, d1) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + BinOp1(op, ctx, d1) |> wrap_ids(ids); + | BinOp2(op, d1, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + BinOp2(op, d1, ctx) |> wrap_ids(ids); + | Test(ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Test(ctx) |> wrap_ids(ids); + | ListLit(ctx, ds) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + ListLit(ctx, ds) |> wrap_ids(ids); + | Tuple(ctx, ds) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Tuple(ctx, ds) |> wrap_ids(ids); + | MultiHole(ctx, ds) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + MultiHole(ctx, ds) |> wrap_ids(ids); + | Cons1(ctx, d2) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Cons1(ctx, d2) |> wrap_ids(ids); + | Cons2(d1, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Cons2(d1, ctx) |> wrap_ids(ids); + | ListConcat1(ctx, d2) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + ListConcat1(ctx, d2) |> wrap_ids(ids); + | ListConcat2(d1, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + ListConcat2(d1, ctx) |> wrap_ids(ids); + | Cast(ctx, ty, ty') => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Cast(ctx, ty, ty') |> wrap_ids(ids); + | FailedCast(ctx, ty, ty') => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + FailedCast(ctx, ty, ty') |> wrap_ids(ids); + | DynamicErrorHole(ctx, error) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + DynamicErrorHole(ctx, error) |> wrap_ids(ids); + | MatchScrut(ctx, rs) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + MatchScrut(ctx, rs) |> wrap_ids(ids); + | MatchRule(dexp, dpat, ctx, rs) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + MatchRule(dexp, dpat, ctx, rs) |> wrap_ids(ids); + | TypAp(ctx, ty) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + TypAp(ctx, ty) |> wrap_ids(ids); + | DeferredAp1(ctx, ds) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + DeferredAp1(ctx, ds) |> wrap_ids(ids); + | DeferredAp2(d1, ctx, ds) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + DeferredAp2(d1, ctx, ds) |> wrap_ids(ids); + | UnOp(op, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + UnOp(op, ctx) |> wrap_ids(ids); + } }; + }; switch (ctx) { - | Filter(_) => (ract, ridx, rctx) + | Term({term: Filter(_), _}) => (ract, ridx, rctx) | _ when midx > pidx && mact |> snd == All => ( ract, ridx, - Filter(Residue(midx, mact), rctx), + Term({term: Filter(Residue(midx, mact), rctx), ids: [Id.mk()]}), ) | _ => (ract, ridx, rctx) }; @@ -557,19 +423,19 @@ let should_hide_step = (~settings, x: step): (FilterAction.action, step) => }; }; -let decompose = (~settings, d) => - d |> decompose |> List.map(should_hide_eval_obj(~settings)); +let decompose = (~settings, d, st) => + decompose(d, st) |> List.map(should_hide_eval_obj(~settings)); let evaluate_with_history = (~settings, d) => { let state = ref(EvaluatorState.init); let rec go = d => - switch (decompose(~settings, d)) { + switch (decompose(~settings, d, state^)) { | [] => [] | [(_, x), ..._] => switch (take_step(state, x.env, x.d_loc)) { | None => [] | Some(d) => - let next = compose(x.ctx, d); + let next = EvalCtx.compose(x.ctx, d); [next, ...go(next)]; } }; diff --git a/src/haz3lcore/dynamics/ExpandingKeyword.re b/src/haz3lcore/dynamics/ExpandingKeyword.re deleted file mode 100644 index 58ecbe7553..0000000000 --- a/src/haz3lcore/dynamics/ExpandingKeyword.re +++ /dev/null @@ -1,31 +0,0 @@ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = - | Let - | Case - | Fun - | Test; - -let is_Let = String.equal("let"); -let is_Case = String.equal("case"); -let is_Fun = String.equal("fun"); -let is_Test = String.equal("test"); - -let mk = (text: string): option(t) => - if (text |> is_Let) { - Some(Let); - } else if (text |> is_Case) { - Some(Case); - } else if (text |> is_Fun) { - Some(Fun); - } else if (text |> is_Test) { - Some(Test); - } else { - None; - }; - -let to_string = - fun - | Let => "let" - | Case => "case" - | Fun => "fun" - | Test => "test"; diff --git a/src/haz3lcore/dynamics/Filter.re b/src/haz3lcore/dynamics/Filter.re deleted file mode 100644 index d6de2b524a..0000000000 --- a/src/haz3lcore/dynamics/Filter.re +++ /dev/null @@ -1 +0,0 @@ -include DH.Filter; diff --git a/src/haz3lcore/dynamics/FilterEnvironment.re b/src/haz3lcore/dynamics/FilterEnvironment.re index ce2f324f4c..284e7353d3 100644 --- a/src/haz3lcore/dynamics/FilterEnvironment.re +++ b/src/haz3lcore/dynamics/FilterEnvironment.re @@ -1 +1,2 @@ -include DH.FilterEnvironment; +type t = list(TermBase.StepperFilterKind.filter); +let extends = (flt, env) => [flt, ...env]; diff --git a/src/haz3lcore/dynamics/FilterMatcher.re b/src/haz3lcore/dynamics/FilterMatcher.re index 39153acee1..25d160af8f 100644 --- a/src/haz3lcore/dynamics/FilterMatcher.re +++ b/src/haz3lcore/dynamics/FilterMatcher.re @@ -1,3 +1,95 @@ +let evaluate_extend_env = + (new_bindings: Environment.t, to_extend: ClosureEnvironment.t) + : ClosureEnvironment.t => { + to_extend + |> ClosureEnvironment.map_of + |> Environment.union(new_bindings) + |> ClosureEnvironment.of_environment; +}; + +let evaluate_extend_env_with_pat = + ( + ids: list(Uuidm.t), + copied: bool, + pat: DHPat.t, + exp: DHExp.t, + to_extend: ClosureEnvironment.t, + ) + : ClosureEnvironment.t => { + switch (DHPat.get_var(pat)) { + | Some(fname) => + evaluate_extend_env( + Environment.singleton(( + fname, + { + ids, + copied, + IdTagged.term: TermBase.Exp.FixF(pat, exp, Some(to_extend)), + }, + )), + to_extend, + ) + | None => + let bindings = DHPat.bound_vars(pat); + let substitutions = + List.map( + binding => + ( + binding, + TermBase.Exp.Let( + pat, + { + ids, + copied, + term: TermBase.Exp.FixF(pat, exp, Some(to_extend)), + }, + TermBase.Exp.Var(binding) |> IdTagged.fresh, + ) + |> IdTagged.fresh, + ), + bindings, + ); + evaluate_extend_env(Environment.of_list(substitutions), to_extend); + }; +}; + +let alpha_magic = "__alpha_id__"; + +let tangle = + ( + dp: DHPat.t, + denv: ClosureEnvironment.t, + fp: DHPat.t, + fenv: ClosureEnvironment.t, + ) + : option((ClosureEnvironment.t, ClosureEnvironment.t)) => { + let dvars = DHPat.bound_vars(dp); + let fvars = DHPat.bound_vars(fp); + if (List.length(dvars) != List.length(fvars)) { + None; + } else { + let ids = + Array.init(List.length(dvars), _ => { + alpha_magic ++ Uuidm.to_string(Uuidm.v(`V4)) + }); + let denv_subst: list((string, 'a)) = + List.mapi( + (i, binding) => + (binding, TermBase.Exp.Var(ids[i]) |> IdTagged.fresh), + dvars, + ); + let fenv_subst: list((string, 'a)) = + List.mapi( + (i, binding) => + (binding, TermBase.Exp.Var(ids[i]) |> IdTagged.fresh), + fvars, + ); + let denv = evaluate_extend_env(Environment.of_list(denv_subst), denv); + let fenv = evaluate_extend_env(Environment.of_list(fenv_subst), fenv); + Some((denv, fenv)); + }; +}; + let rec matches_exp = ( ~denv: ClosureEnvironment.t, @@ -11,34 +103,56 @@ let rec matches_exp = if (d == f) { true; } else { - switch (d, f) { - | (Constructor("$e"), _) => failwith("$e in matched expression") - | (Constructor("$v"), _) => failwith("$v in matched expression") + switch (d |> DHExp.term_of, f |> DHExp.term_of) { + | (Parens(d), _) => matches_exp(d, f) + | (_, Parens(f)) => matches_exp(d, f) - // HACK[Matt]: ignore fixpoints in comparison, to allow pausing on fixpoint steps - | (FixF(dp, dt, dc), FixF(fp, ft, fc)) => - dp == fp - && dt == ft - && matches_exp( - ~denv=denv |> ClosureEnvironment.without_keys([dp]), - dc, - ~fenv=fenv |> ClosureEnvironment.without_keys([fp]), - fc, - ) - | (FixF(dp, _, dc), f) => - matches_exp(~denv=denv |> ClosureEnvironment.without_keys([dp]), dc, f) - | (d, FixF(fp, _, fc)) => - matches_exp(d, ~fenv=fenv |> ClosureEnvironment.without_keys([fp]), fc) + | (Constructor("$e", _), _) => failwith("$e in matched expression") + | (Constructor("$v", _), _) => failwith("$v in matched expression") - | (_, Constructor("$v")) => - switch (ValueChecker.check_value(denv, d)) { + // HACK[Matt]: ignore fixpoints in comparison, to allow pausing on fixpoint steps + | (FixF(dp, dc, None), FixF(fp, fc, None)) => + switch (tangle(dp, denv, fp, fenv)) { + | None => false + | Some((denv, fenv)) => matches_exp(~denv, dc, ~fenv, fc) + } + | (FixF(dp, dc, None), FixF(fp, fc, Some(fenv))) => + switch (tangle(dp, denv, fp, fenv)) { + | None => false + | Some((denv, fenv)) => matches_exp(~denv, dc, ~fenv, fc) + } + | (FixF(dp, dc, Some(denv)), FixF(fp, fc, None)) => + switch (tangle(dp, denv, fp, fenv)) { + | None => false + | Some((denv, fenv)) => matches_exp(~denv, dc, ~fenv, fc) + } + | (FixF(dp, dc, Some(denv)), FixF(fp, fc, Some(fenv))) => + switch (tangle(dp, denv, fp, fenv)) { + | None => false + | Some((denv, fenv)) => matches_exp(~denv, dc, ~fenv, fc) + } + | (FixF(dp, dc, None), _) => + let denv = evaluate_extend_env_with_pat(d.ids, d.copied, dp, dc, denv); + matches_exp(~denv, dc, ~fenv, f); + | (FixF(dp, dc, Some(denv)), _) => + let denv = evaluate_extend_env_with_pat(d.ids, d.copied, dp, dc, denv); + matches_exp(~denv, dc, ~fenv, f); + | (_, FixF(fp, fc, None)) => + let fenv = evaluate_extend_env_with_pat(f.ids, f.copied, fp, fc, fenv); + matches_exp(~denv, d, ~fenv, fc); + | (_, FixF(fp, fc, Some(fenv))) => + let fenv = evaluate_extend_env_with_pat(f.ids, f.copied, fp, fc, fenv); + matches_exp(~denv, d, ~fenv, fc); + + | (_, Constructor("$v", _)) => + switch (ValueChecker.check_value((), denv, d)) { | Indet | Value => true | Expr => false } - | (_, EmptyHole(_)) - | (_, Constructor("$e")) => true + | (_, EmptyHole) + | (_, Constructor("$e", _)) => true | (Cast(d, _, _), Cast(f, _, _)) => matches_exp(d, f) | (Closure(denv, d), Closure(fenv, f)) => @@ -53,102 +167,59 @@ let rec matches_exp = | (FailedCast(d, _, _), _) => matches_exp(d, f) | (Filter(Residue(_), d), _) => matches_exp(d, f) - | (BoundVar(dx), BoundVar(fx)) - when String.starts_with(dx, ~prefix="__mutual__") => - String.starts_with(fx, ~prefix="__mutual__") && dx == fx - | (BoundVar(dx), BoundVar(fx)) => - switch ( - ClosureEnvironment.lookup(denv, dx), - ClosureEnvironment.lookup(fenv, fx), - ) { - | ( - Some(Fun(_, _, Closure(denv, _), Some(dname)) as d), - Some(Fun(_, _, Closure(fenv, _), Some(fname)) as f), - ) - when - ClosureEnvironment.lookup(denv, dname) == Some(d) - && ClosureEnvironment.lookup(fenv, fname) == Some(f) => - matches_exp( - ~denv=ClosureEnvironment.without_keys([dname], denv), - d, - ~fenv=ClosureEnvironment.without_keys([fname], fenv), - f, - ) - | ( - Some(Fun(_, _, Closure(denv, _), Some(dname)) as d), - Some(Fun(_, _, _, Some(fname)) as f), - ) - when - ClosureEnvironment.lookup(denv, dname) == Some(d) - && ClosureEnvironment.lookup(fenv, fname) == Some(f) => - matches_exp( - ~denv=ClosureEnvironment.without_keys([dname], denv), - d, - ~fenv=ClosureEnvironment.without_keys([fname], fenv), - f, - ) - | ( - Some(Fun(_, _, _, Some(dname)) as d), - Some(Fun(_, _, _, Some(fname)) as f), - ) - when - ClosureEnvironment.lookup(denv, dname) == Some(d) - && ClosureEnvironment.lookup(fenv, fname) == Some(f) => - matches_exp( - ~denv=ClosureEnvironment.without_keys([dname], denv), - d, - ~fenv=ClosureEnvironment.without_keys([fname], fenv), - f, - ) - | ( - Some(Fun(_, _, _, Some(dname)) as d), - Some(Fun(_, _, _, Some(fname)) as f), - ) - when - ClosureEnvironment.lookup(denv, dname) == Some(d) - && ClosureEnvironment.lookup(fenv, fname) == Some(f) => - matches_exp( - ~denv=ClosureEnvironment.without_keys([dname], denv), - d, - ~fenv=ClosureEnvironment.without_keys([fname], denv), - f, - ) - | (Some(d), Some(f)) => matches_exp(d, f) - | (Some(_), None) => false - | (None, Some(_)) => false - | (None, None) => true + | (Var(dx), Var(fx)) => + if (String.starts_with(~prefix=alpha_magic, dx) + && String.starts_with(~prefix=alpha_magic, fx)) { + String.equal(dx, fx); + } else { + switch ( + ClosureEnvironment.lookup(denv, dx), + ClosureEnvironment.lookup(fenv, fx), + ) { + | (Some(d), Some(f)) => matches_exp(d, f) + | (Some(_), None) => false + | (None, Some(_)) => false + | (None, None) => true + }; } - | (BoundVar(dx), _) => + | (Var(dx), _) => switch (ClosureEnvironment.lookup(denv, dx)) { | Some(d) => matches_exp(d, f) | None => false } - | (_, BoundVar(fx)) => + | (_, Var(fx)) => switch (ClosureEnvironment.lookup(fenv, fx)) { | Some(f) => matches_exp(d, f) | None => false } - | (EmptyHole(_), _) => false + | (EmptyHole, _) => false + + | (Deferral(x), Deferral(y)) => x == y + | (Deferral(_), _) => false | (Filter(df, dd), Filter(ff, fd)) => - DH.DHFilter.fast_equal(df, ff) && matches_exp(dd, fd) + TermBase.StepperFilterKind.fast_equal(df, ff) && matches_exp(dd, fd) | (Filter(_), _) => false - | (BoolLit(dv), BoolLit(fv)) => dv == fv - | (BoolLit(_), _) => false + | (Bool(dv), Bool(fv)) => dv == fv + | (Bool(_), _) => false - | (IntLit(dv), IntLit(fv)) => dv == fv - | (IntLit(_), _) => false + | (Int(dv), Int(fv)) => dv == fv + | (Int(_), _) => false - | (FloatLit(dv), FloatLit(fv)) => dv == fv - | (FloatLit(_), _) => false + | (Float(dv), Float(fv)) => dv == fv + | (Float(_), _) => false - | (StringLit(dv), StringLit(fv)) => dv == fv - | (StringLit(_), _) => false + | (String(dv), String(fv)) => dv == fv + | (String(_), _) => false - | (Constructor(_), Ap(Constructor("~MVal"), Tuple([]))) => true - | (Constructor(dt), Constructor(ft)) => dt == ft + | ( + Constructor(_), + Ap(_, {term: Constructor("~MVal", _), _}, {term: Tuple([]), _}), + ) => + true + | (Constructor(dt, _), Constructor(ft, _)) => dt == ft | (Constructor(_), _) => false | (BuiltinFun(dn), BuiltinFun(fn)) => dn == fn @@ -158,25 +229,22 @@ let rec matches_exp = s1 == s2 && matches_utpat(pat1, pat2) && matches_exp(d1, d2) | (TypFun(_), _) => false - | ( - Fun(dp1, _, Closure(denv, d1), _), - Fun(fp1, _, Closure(fenv, f1), _), - ) => + | (Fun(dp1, d1, Some(denv), _), Fun(fp1, f1, Some(fenv), _)) => matches_fun(~denv, dp1, d1, ~fenv, fp1, f1) - | (Fun(dp1, _, Closure(denv, d1), _), Fun(fp1, _, f1, _)) => + | (Fun(dp1, d1, Some(denv), _), Fun(fp1, f1, None, _)) => matches_fun(~denv, dp1, d1, ~fenv, fp1, f1) - | (Fun(dp1, _, d1, _), Fun(fp1, _, Closure(fenv, f1), _)) => + | (Fun(dp1, d1, None, _), Fun(fp1, f1, Some(fenv), _)) => matches_fun(~denv, dp1, d1, ~fenv, fp1, f1) - | (Fun(dp1, _, d1, _), Fun(fp1, _, f1, _)) => + | (Fun(dp1, d1, None, _), Fun(fp1, f1, None, _)) => matches_fun(~denv, dp1, d1, ~fenv, fp1, f1) | (Fun(_), _) => false - | (FreeVar(du, di, dx), FreeVar(fu, fi, fx)) => - du == fu && di == fi && dx == fx - | (FreeVar(_), _) => false - | (Let(dp, d1, d2), Let(fp, f1, f2)) => - matches_pat(dp, fp) && matches_exp(d1, f1) && matches_exp(d2, f2) + switch (tangle(dp, denv, fp, fenv)) { + | None => false + | Some((denv, fenv)) => + matches_exp(d1, f1) && matches_exp(~denv, d2, ~fenv, f2) + } | (Let(_), _) => false | (Module(dp, d1, d2), Module(fp, f1, f2)) => matches_pat(dp, fp) && matches_exp(d1, f1) && matches_exp(d2, f2) @@ -191,76 +259,67 @@ let rec matches_exp = matches_exp(d1, d2) && matches_typ(t1, t2) | (TypAp(_), _) => false - | (Ap(d1, d2), Ap(f1, f2)) => + // TODO: do we want f(x) to match x |> f ??? + | (Ap(_, d1, d2), Ap(_, f1, f2)) => matches_exp(d1, f1) && matches_exp(d2, f2) | (Ap(_), _) => false - | (IfThenElse(dc, d1, d2, d3), IfThenElse(fc, f1, f2, f3)) => - dc == fc - && matches_exp(d1, f1) - && matches_exp(d2, f2) - && matches_exp(d3, f3) - | (IfThenElse(_), _) => false + | (DeferredAp(d1, d2), DeferredAp(f1, f2)) => + matches_exp(d1, f1) + && List.fold_left2( + (acc, d, f) => acc && matches_exp(d, f), + true, + d2, + f2, + ) + | (DeferredAp(_), _) => false + + | (If(d1, d2, d3), If(f1, f2, f3)) => + matches_exp(d1, f1) && matches_exp(d2, f2) && matches_exp(d3, f3) + | (If(_), _) => false - | (Sequence(d1, d2), Sequence(f1, f2)) => + | (Seq(d1, d2), Seq(f1, f2)) => matches_exp(d1, f1) && matches_exp(d2, f2) - | (Sequence(_), _) => false + | (Seq(_), _) => false - | (Test(id1, d2), Test(id2, f2)) => id1 == id2 && matches_exp(d2, f2) + | (Test(d2), Test(f2)) => matches_exp(d2, f2) | (Test(_), _) => false | (Cons(d1, d2), Cons(f1, f2)) => matches_exp(d1, f1) && matches_exp(d2, f2) | (Cons(_), _) => false - | (ListLit(_, _, dt, dv), ListLit(_, _, ft, fv)) => - dt == ft - && List.fold_left2( - (acc, d, f) => acc && matches_exp(d, f), - true, - dv, - fv, - ) + | (ListLit(dv), ListLit(fv)) => + List.fold_left2((acc, d, f) => acc && matches_exp(d, f), true, dv, fv) | (ListLit(_), _) => false | (Tuple(dv), Tuple(fv)) => List.fold_left2((acc, d, f) => acc && matches_exp(d, f), true, dv, fv) | (Tuple(_), _) => false - | (BinBoolOp(d_op_bin, d1, d2), BinBoolOp(f_op_bin, f1, f2)) => - d_op_bin == f_op_bin && matches_exp(d1, f1) && matches_exp(d2, f2) + | (UnOp(d_op, d1), UnOp(f_op, f1)) => + d_op == f_op && matches_exp(d1, f1) + | (UnOp(_), _) => false - | (BinBoolOp(_), _) => false - - | (BinIntOp(d_op_bin, d1, d2), BinIntOp(f_op_bin, f1, f2)) => - d_op_bin == f_op_bin && matches_exp(d1, f1) && matches_exp(d2, f2) - | (BinIntOp(_), _) => false - - | (BinFloatOp(d_op_bin, d1, d2), BinFloatOp(f_op_bin, f1, f2)) => - d_op_bin == f_op_bin && matches_exp(d1, f1) && matches_exp(d2, f2) - | (BinFloatOp(_), _) => false - - | (BinStringOp(d_op_bin, d1, d2), BinStringOp(f_op_bin, f1, f2)) => - d_op_bin == f_op_bin && matches_exp(d1, f1) && matches_exp(d2, f2) - | (BinStringOp(_), _) => false + | (BinOp(d_op, d1, d2), BinOp(f_op, f1, f2)) => + d_op == f_op && matches_exp(d1, f1) && matches_exp(d2, f2) + | (BinOp(_), _) => false + | (ListConcat(d1, d2), ListConcat(f1, f2)) => + matches_exp(d1, f1) && matches_exp(d2, f2) | (ListConcat(_), _) => false - | ( - ConsistentCase(Case(dscrut, drule, _)), - ConsistentCase(Case(fscrut, frule, _)), - ) - | ( - InconsistentBranches(_, _, Case(dscrut, drule, _)), - InconsistentBranches(_, _, Case(fscrut, frule, _)), - ) => + | (Match(dscrut, drule), Match(fscrut, frule)) => matches_exp(dscrut, fscrut) && ( switch ( - List.fold_left2( - (res, drule, frule) => - res && matches_rul(~denv, drule, ~fenv, frule), - true, + List.for_all2( + ((dk, dv), (fk, fv)) => { + switch (tangle(dk, denv, fk, fenv)) { + | None => false + | Some((denv, fenv)) => matches_exp(~denv, dv, ~fenv, fv) + } + }, drule, frule, ) @@ -269,22 +328,21 @@ let rec matches_exp = | res => res } ) - | (ConsistentCase(_), _) - | (InconsistentBranches(_), _) => false - - | (NonEmptyHole(_), _) => false - | (InvalidText(_), _) => false - | (InvalidOperation(_), _) => false + | (Match(_), _) => false + // TODO: should these not default to false? + | (MultiHole(_), _) => false + | (Invalid(_), _) => false + | (DynamicErrorHole(_), _) => false - | (ApBuiltin(dname, darg), ApBuiltin(fname, farg)) => - dname == fname && matches_exp(darg, farg) - | (ApBuiltin(_), _) => false + | (Undefined, _) => false - | (Prj(dv, di), Prj(fv, fi)) => matches_exp(dv, fv) && di == fi - | (Prj(_), _) => false + | (TyAlias(dtp, dut, dd), TyAlias(ftp, fut, fd)) => + dtp == ftp && dut == fut && matches_exp(dd, fd) + | (TyAlias(_), _) => false }; }; } + and matches_fun = ( ~denv: ClosureEnvironment.t, @@ -294,69 +352,38 @@ and matches_fun = fp: DHPat.t, f: DHExp.t, ) => { - matches_pat(dp, fp) - && matches_exp( - ~denv=ClosureEnvironment.without_keys(DHPat.bound_vars(dp), denv), - d, - ~fenv=ClosureEnvironment.without_keys(DHPat.bound_vars(fp), fenv), - f, - ); -} -and matches_pat = (d: DHPat.t, f: DHPat.t): bool => { - switch (d, f) { - | (_, EmptyHole(_)) => true - | (Wild, Wild) => true - | (Wild, _) => false - | (IntLit(dv), IntLit(fv)) => dv == fv - | (IntLit(_), _) => false - | (FloatLit(dv), FloatLit(fv)) => dv == fv - | (FloatLit(_), _) => false - | (BoolLit(dv), BoolLit(fv)) => dv == fv - | (BoolLit(_), _) => false - | (StringLit(dv), StringLit(fv)) => dv == fv - | (StringLit(_), _) => false - | (ListLit(dty1, dl), ListLit(fty1, fl)) => - switch ( - List.fold_left2((res, d, f) => res && matches_pat(d, f), true, dl, fl) - ) { - | exception (Invalid_argument(_)) => false - | res => matches_typ(dty1, fty1) && res - } - | (ListLit(_), _) => false - | (Constructor(dt), Constructor(ft)) => dt == ft - | (Constructor(_), _) => false - | (Var(_), Var(_)) => true - | (Var(_), _) => false - | (Tuple(dl), Tuple(fl)) => - switch ( - List.fold_left2((res, d, f) => res && matches_pat(d, f), true, dl, fl) - ) { - | exception (Invalid_argument(_)) => false - | res => res - } - | (Tuple(_), _) => false - | (Ap(d1, d2), Ap(f1, f2)) => matches_pat(d1, f1) && matches_pat(d2, f2) - | (Ap(_), _) => false - | (BadConstructor(_, _, dt), BadConstructor(_, _, ft)) => dt == ft - | (BadConstructor(_), _) => false - | (Cons(d1, d2), Cons(f1, f2)) => - matches_pat(d1, f1) && matches_pat(d2, f2) - | (Cons(_), _) => false - | (EmptyHole(_), _) => false - | (NonEmptyHole(_), _) => false - | (InvalidText(_), _) => false + let dvars = DHPat.bound_vars(dp); + let fvars = DHPat.bound_vars(fp); + if (List.length(dvars) != List.length(fvars)) { + false; + } else { + let ids = + Array.init(List.length(dvars), _ => { + alpha_magic ++ Uuidm.to_string(Uuidm.v(`V4)) + }); + let denv_subst: list((string, 'a)) = + List.mapi( + (i, binding) => + (binding, TermBase.Exp.Var(ids[i]) |> IdTagged.fresh), + dvars, + ); + let fenv_subst: list((string, 'a)) = + List.mapi( + (i, binding) => + (binding, TermBase.Exp.Var(ids[i]) |> IdTagged.fresh), + fvars, + ); + let denv = evaluate_extend_env(Environment.of_list(denv_subst), denv); + let fenv = evaluate_extend_env(Environment.of_list(fenv_subst), fenv); + matches_exp(~denv, d, ~fenv, f); }; } + and matches_typ = (d: Typ.t, f: Typ.t) => { Typ.eq(d, f); } -and matches_rul = (~denv, d: DHExp.rule, ~fenv, f: DHExp.rule) => { - switch (d, f) { - | (Rule(dp, d), Rule(fp, f)) => - matches_pat(dp, fp) && matches_exp(~denv, d, ~fenv, f) - }; -} -and matches_utpat = (d: Term.UTPat.t, f: Term.UTPat.t): bool => { + +and matches_utpat = (d: TPat.t, f: TPat.t): bool => { switch (d.term, f.term) { | (Invalid(_), _) => false | (_, Invalid(_)) => false @@ -368,7 +395,11 @@ and matches_utpat = (d: Term.UTPat.t, f: Term.UTPat.t): bool => { }; let matches = - (~env: ClosureEnvironment.t, ~exp: DHExp.t, ~flt: Filter.t) + ( + ~env: ClosureEnvironment.t, + ~exp: DHExp.t, + ~flt: TermBase.StepperFilterKind.filter, + ) : option(FilterAction.t) => if (matches_exp(~denv=env, exp, ~fenv=env, flt.pat)) { Some(flt.act); diff --git a/src/haz3lcore/dynamics/HoleInstance.re b/src/haz3lcore/dynamics/HoleInstance.re deleted file mode 100644 index 5925bf6ae8..0000000000 --- a/src/haz3lcore/dynamics/HoleInstance.re +++ /dev/null @@ -1,7 +0,0 @@ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = (MetaVar.t, HoleInstanceId.t); - -let u_of = ((u, _): t): MetaVar.t => u; -let i_of = ((_, i): t): HoleInstanceId.t => i; - -let result: t = (Id.invalid, 0); diff --git a/src/haz3lcore/dynamics/HoleInstance.rei b/src/haz3lcore/dynamics/HoleInstance.rei deleted file mode 100644 index 1e1c40bbd6..0000000000 --- a/src/haz3lcore/dynamics/HoleInstance.rei +++ /dev/null @@ -1,23 +0,0 @@ -/** - Representation of a unique hole instantiation (the set of hole instances with - the same hole number and environment). - */ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = (MetaVar.t, HoleInstanceId.t); - -/** - [u_of (u, i)] is [u], where [u] is the hole metavariable. - */ -let u_of: t => MetaVar.t; - -/** - [i_of (u, i)] is [i], where [i] is the hole instance id. - */ -let i_of: t => HoleInstanceId.t; - -/** - [result] is the special instance used to represent the parent "hole instance" - of the result; that is to say, if a hole instance has this value as its - parent, then it is directly in the result. - */ -let result: t; diff --git a/src/haz3lcore/dynamics/HoleInstanceId.re b/src/haz3lcore/dynamics/HoleInstanceId.re deleted file mode 100644 index 6db122bfcf..0000000000 --- a/src/haz3lcore/dynamics/HoleInstanceId.re +++ /dev/null @@ -1,4 +0,0 @@ -open Sexplib.Std; - -[@deriving (show({with_path: false}), sexp, yojson)] -type t = int; diff --git a/src/haz3lcore/dynamics/HoleInstanceId.rei b/src/haz3lcore/dynamics/HoleInstanceId.rei deleted file mode 100644 index 2093b1dcd5..0000000000 --- a/src/haz3lcore/dynamics/HoleInstanceId.rei +++ /dev/null @@ -1,6 +0,0 @@ -/** - Identifier for a unique hole closure/instantiation (unique among hole - closures for a given hole number). - */ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = int; diff --git a/src/haz3lcore/dynamics/HoleInstanceInfo.re b/src/haz3lcore/dynamics/HoleInstanceInfo.re deleted file mode 100644 index f63e70a762..0000000000 --- a/src/haz3lcore/dynamics/HoleInstanceInfo.re +++ /dev/null @@ -1,38 +0,0 @@ -open Sexplib.Std; - -[@deriving (show({with_path: false}), sexp, yojson)] -type t = MetaVarMap.t(list((ClosureEnvironment.t, HoleInstanceParents.t))); - -let empty: t = MetaVarMap.empty; - -let num_instances = (hii: t, u: MetaVar.t): int => - hii - |> MetaVarMap.find_opt(u) - |> Option.map(his => List.length(his)) - |> Option.value(~default=0); - -let find_instance = - (hii: t, u: MetaVar.t, i: HoleInstanceId.t) - : option((ClosureEnvironment.t, HoleInstanceParents.t)) => { - switch (hii |> MetaVarMap.find_opt(u)) { - | Some(his) => List.nth_opt(his, i) - | None => None - }; -}; - -let add_parent = - ((u, i): HoleInstance.t, parent: HoleInstanceParents.t_, hii: t): t => { - let u_instances = hii |> MetaVarMap.find(u); - hii - |> MetaVarMap.add( - u, - u_instances - |> List.mapi((i', (env, parents)) => - if (i' == i) { - (env, parent |> HoleInstanceParents.add_parent(parents)); - } else { - (env, parents); - } - ), - ); -}; diff --git a/src/haz3lcore/dynamics/HoleInstanceInfo.rei b/src/haz3lcore/dynamics/HoleInstanceInfo.rei deleted file mode 100644 index e7477ff995..0000000000 --- a/src/haz3lcore/dynamics/HoleInstanceInfo.rei +++ /dev/null @@ -1,33 +0,0 @@ -/** - Stores information about all hole instances reachable by a program's - evaluation result. Used in the context inspector. - - Constructed using {!val:HoleInstanceInfo_.to_hole_instance_info}. - */ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = MetaVarMap.t(list((ClosureEnvironment.t, HoleInstanceParents.t))); - -/** - [empty] is the empty info map. - */ -let empty: t; - -/** - [num_unique_his hii u] is the number of unique hole instances for a given - hole (given by the id [u]). - */ -let num_instances: (t, MetaVar.t) => int; - -/** - [find_instance hii u i] is the information for the given hole and hole - instance id, if found. - */ -let find_instance: - (t, MetaVar.t, HoleInstanceId.t) => - option((ClosureEnvironment.t, HoleInstanceParents.t)); - -/** - [add_parent (u, i) hip hii] adds the parent [hip] to the hole given by [(u, - i)]. Assumes both the parent and the hole exist in [hii]. - */ -let add_parent: (HoleInstance.t, HoleInstanceParents.t_, t) => t; diff --git a/src/haz3lcore/dynamics/HoleInstanceInfo_.re b/src/haz3lcore/dynamics/HoleInstanceInfo_.re deleted file mode 100644 index bee03aa10f..0000000000 --- a/src/haz3lcore/dynamics/HoleInstanceInfo_.re +++ /dev/null @@ -1,61 +0,0 @@ -/* - Variable names: - [hii] => "hole instance info" - [his] => "hole instances" - [hip] => "hole instance parents" - - TODO: Clear explanation of namings, probably in overall doc. - */ - -/** - Map associates a hole id to a hole instance id, hole closure environment, and - hole instance parents. - */ -[@deriving sexp] -type t = - MetaVarMap.t( - EnvironmentIdMap.t( - (HoleInstanceId.t, ClosureEnvironment.t, HoleInstanceParents.t), - ), - ); - -let empty: t = MetaVarMap.empty; - -let add_instance = - (hii: t, u: MetaVar.t, env: ClosureEnvironment.t): (t, HoleInstanceId.t) => { - let ei = env |> ClosureEnvironment.id_of; - switch (hii |> MetaVarMap.find_opt(u)) { - /* Hole already exists in the map. */ - | Some(his) => - switch (his |> EnvironmentIdMap.find_opt(ei)) { - /* Hole instance already exists in the map, simply return the hole instance - * id. */ - | Some((i, _, _)) => (hii, i) - /* Hole exists in the info map, but instance doesn't; create a new hole - * instance with next unique instance id. */ - | None => - let i = his |> EnvironmentIdMap.cardinal; - let his = his |> EnvironmentIdMap.add(ei, (i, env, [])); - let hii = hii |> MetaVarMap.add(u, his); - (hii, i); - } - /* Hole doesn't exist in the map. */ - | None => - let i = 0; - let his = EnvironmentIdMap.singleton(ei, (0, env, [])); - let hii = hii |> MetaVarMap.add(u, his); - (hii, i); - }; -}; - -let to_hole_instance_info = (hii: t): HoleInstanceInfo.t => - /* For each hole, arrange instances in order of increasing hole instance id. */ - hii - |> MetaVarMap.map(his => - his - |> EnvironmentIdMap.bindings - |> List.sort(((_, (i1, _, _)), (_, (i2, _, _))) => - compare(i1, i2) - ) - |> List.map(((_, (_, env, hip))) => (env, hip)) - ); diff --git a/src/haz3lcore/dynamics/HoleInstanceInfo_.rei b/src/haz3lcore/dynamics/HoleInstanceInfo_.rei deleted file mode 100644 index 8877f4da71..0000000000 --- a/src/haz3lcore/dynamics/HoleInstanceInfo_.rei +++ /dev/null @@ -1,29 +0,0 @@ -/** - Auxiliary data structure for constructing a {!type:HoleInstanceInfo.t}. - */ - -/* FIXME: Make this abstract. */ -[@deriving sexp] -type t; - -/** - [empty] is the empty info map. - */ -let empty: t; - -/** - [add_instance hii u env] binds a unique hole instance id for the - [(u, env)] pair representing a hole instance, assocating it in [hii] and - returning [(map', i)], where [map'] is the augmented [map] and [i] is the - hole instance id. - - If the pair already exists in [hii], the existing id is returned as [i]; - otherwise, a unique id is assigned and returned as [i]. - */ -let add_instance: - (t, MetaVar.t, ClosureEnvironment.t) => (t, HoleInstanceId.t); - -/** - [to_hole_instance_info hii] converts [hii] into {!type:HoleInstanceInfo.t}. - */ -let to_hole_instance_info: t => HoleInstanceInfo.t; diff --git a/src/haz3lcore/dynamics/HoleInstanceParents.re b/src/haz3lcore/dynamics/HoleInstanceParents.re deleted file mode 100644 index 3935a3b8c8..0000000000 --- a/src/haz3lcore/dynamics/HoleInstanceParents.re +++ /dev/null @@ -1,13 +0,0 @@ -open Sexplib.Std; - -[@deriving (show({with_path: false}), sexp, yojson)] -type t_ = (Var.t, HoleInstance.t) -and t = list(t_); - -let to_list = (hcp: t): list(t_) => hcp; -let singleton = (parent: t_) => [parent]; - -let add_parent = (hcp: t, new_parent: t_) => [ - new_parent, - ...List.filter(p => p != new_parent, hcp), -]; diff --git a/src/haz3lcore/dynamics/HoleInstanceParents.rei b/src/haz3lcore/dynamics/HoleInstanceParents.rei deleted file mode 100644 index 96b43acc95..0000000000 --- a/src/haz3lcore/dynamics/HoleInstanceParents.rei +++ /dev/null @@ -1,13 +0,0 @@ -/** - List of hole instance parents. A single hole instance (set of closures with - the same environment) may have multiple parents. - */ - -[@deriving (show({with_path: false}), sexp, yojson)] -type t_ = (Var.t, HoleInstance.t) -and t = list(t_); - -let to_list: t => list(t_); -let singleton: t_ => t; - -let add_parent: (t, t_) => t; diff --git a/src/haz3lcore/dynamics/InjSide.re b/src/haz3lcore/dynamics/InjSide.re deleted file mode 100644 index 690f23871d..0000000000 --- a/src/haz3lcore/dynamics/InjSide.re +++ /dev/null @@ -1,15 +0,0 @@ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = - | L - | R; - -let to_string = - fun - | L => "L" - | R => "R"; - -let pick = (side, l, r) => - switch (side) { - | L => l - | R => r - }; diff --git a/src/haz3lcore/dynamics/InstancePath.re b/src/haz3lcore/dynamics/InstancePath.re deleted file mode 100644 index 117a03806e..0000000000 --- a/src/haz3lcore/dynamics/InstancePath.re +++ /dev/null @@ -1,4 +0,0 @@ -open Sexplib.Std; - -[@deriving sexp] -type t = list((HoleInstance.t, Var.t)); diff --git a/src/haz3lcore/dynamics/InstancePath.rei b/src/haz3lcore/dynamics/InstancePath.rei deleted file mode 100644 index 8e205a0052..0000000000 --- a/src/haz3lcore/dynamics/InstancePath.rei +++ /dev/null @@ -1,2 +0,0 @@ -[@deriving sexp] -type t = list((HoleInstance.t, Var.t)); diff --git a/src/haz3lcore/dynamics/KeywordID.re b/src/haz3lcore/dynamics/KeywordID.re deleted file mode 100644 index d176549da7..0000000000 --- a/src/haz3lcore/dynamics/KeywordID.re +++ /dev/null @@ -1,2 +0,0 @@ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = Id.t; diff --git a/src/haz3lcore/dynamics/MetaVar.re b/src/haz3lcore/dynamics/MetaVar.re deleted file mode 100644 index d176549da7..0000000000 --- a/src/haz3lcore/dynamics/MetaVar.re +++ /dev/null @@ -1,2 +0,0 @@ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = Id.t; diff --git a/src/haz3lcore/dynamics/MetaVar.rei b/src/haz3lcore/dynamics/MetaVar.rei deleted file mode 100644 index d176549da7..0000000000 --- a/src/haz3lcore/dynamics/MetaVar.rei +++ /dev/null @@ -1,2 +0,0 @@ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = Id.t; diff --git a/src/haz3lcore/dynamics/MetaVarInst.re b/src/haz3lcore/dynamics/MetaVarInst.re deleted file mode 100644 index 9b410f2e61..0000000000 --- a/src/haz3lcore/dynamics/MetaVarInst.re +++ /dev/null @@ -1,7 +0,0 @@ -open Sexplib.Std; - -/** - * Hole instance index in DHPat and DHExp - */ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = int; diff --git a/src/haz3lcore/dynamics/MetaVarInst.rei b/src/haz3lcore/dynamics/MetaVarInst.rei deleted file mode 100644 index 89692b7bed..0000000000 --- a/src/haz3lcore/dynamics/MetaVarInst.rei +++ /dev/null @@ -1,5 +0,0 @@ -/** - * Hole instance index in DHPat and DHExp - */ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = int; diff --git a/src/haz3lcore/dynamics/MetaVarMap.re b/src/haz3lcore/dynamics/MetaVarMap.re deleted file mode 100644 index 932d7b1316..0000000000 --- a/src/haz3lcore/dynamics/MetaVarMap.re +++ /dev/null @@ -1 +0,0 @@ -include Id.Map; diff --git a/src/haz3lcore/dynamics/PatternMatch.re b/src/haz3lcore/dynamics/PatternMatch.re index cc51a785e4..329ca1efd8 100644 --- a/src/haz3lcore/dynamics/PatternMatch.re +++ b/src/haz3lcore/dynamics/PatternMatch.re @@ -1,522 +1,60 @@ -open Util; - -type match_result = - | Matches(Environment.t) - | DoesNotMatch - | IndetMatch; - -let const_unknown: 'a => Typ.t = _ => Unknown(Internal); - -let cast_sum_maps = - (sm1: Typ.sum_map, sm2: Typ.sum_map) - : option(ConstructorMap.t((Typ.t, Typ.t))) => { - let (ctrs1, tys1) = sm1 |> ConstructorMap.bindings |> List.split; - let (ctrs2, tys2) = sm2 |> ConstructorMap.bindings |> List.split; - if (ctrs1 == ctrs2) { - let tys1 = tys1 |> List.filter(Option.is_some) |> List.map(Option.get); - let tys2 = tys2 |> List.filter(Option.is_some) |> List.map(Option.get); - if (List.length(tys1) == List.length(tys2)) { - Some( - List.(combine(tys1, tys2) |> combine(ctrs1)) - |> ConstructorMap.of_list, - ); - } else { - None; - }; - } else { - None; +type match_result = Unboxing.unboxed(Environment.t); +let ( let* ) = Unboxing.( let* ); + +let combine_result = (r1: match_result, r2: match_result): match_result => + switch (r1, r2) { + | (DoesNotMatch, _) + | (_, DoesNotMatch) => DoesNotMatch + | (IndetMatch, _) + | (_, IndetMatch) => IndetMatch + | (Matches(env1), Matches(env2)) => + Matches(Environment.union(env1, env2)) }; -}; - -let rec matches = (dp: DHPat.t, d: DHExp.t): match_result => - switch (dp, d) { - | (_, BoundVar(_)) => DoesNotMatch - | (EmptyHole(_), _) - | (NonEmptyHole(_), _) => IndetMatch - | (Wild, _) => Matches(Environment.empty) - | (InvalidText(_), _) => IndetMatch - | (Var(_), ModuleVal(_)) => DoesNotMatch - | (Constructor(x), ModuleVal(_)) - | (Constructor(x), Cast(_, Module(_), Module(_))) - | (Constructor(x), Cast(_, Module(_), Unknown(_))) - | (Constructor(x), Cast(_, Unknown(_), Module(_))) => - let env = Environment.extend(Environment.empty, (x, d)); - Matches(env); - | (BadConstructor(_), _) => IndetMatch - | (Var(x), _) => - let env = Environment.extend(Environment.empty, (x, d)); - Matches(env); - | (_, EmptyHole(_)) => IndetMatch - | (_, NonEmptyHole(_)) => IndetMatch - | (_, FailedCast(_)) => IndetMatch - | (_, InvalidOperation(_)) => IndetMatch - | (_, FreeVar(_)) => IndetMatch - | (_, InvalidText(_)) => IndetMatch - | (_, Let(_)) => IndetMatch - | (_, FixF(_)) => DoesNotMatch - | (_, Fun(_)) => DoesNotMatch - | (_, BinBoolOp(_)) => IndetMatch - | (_, BinIntOp(_)) => IndetMatch - | (_, BinFloatOp(_)) => IndetMatch - | (_, ConsistentCase(Case(_))) => IndetMatch - - /* Closure should match like underlying expression. */ - | (_, Closure(_, d')) - | (_, Filter(_, d')) => matches(dp, d') - - | (BoolLit(b1), BoolLit(b2)) => - if (b1 == b2) { - Matches(Environment.empty); - } else { - DoesNotMatch; - } - | (BoolLit(_), Cast(d, Bool, Unknown(_))) => matches(dp, d) - | (BoolLit(_), Cast(d, Unknown(_), Bool)) => matches(dp, d) - | (BoolLit(_), _) => DoesNotMatch - | (IntLit(n1), IntLit(n2)) => - if (n1 == n2) { - Matches(Environment.empty); - } else { - DoesNotMatch; - } - | (IntLit(_), Cast(d, Int, Unknown(_))) => matches(dp, d) - | (IntLit(_), Cast(d, Unknown(_), Int)) => matches(dp, d) - | (IntLit(_), _) => DoesNotMatch - | (FloatLit(n1), FloatLit(n2)) => - if (n1 == n2) { - Matches(Environment.empty); - } else { - DoesNotMatch; - } - | (FloatLit(_), Cast(d, Float, Unknown(_))) => matches(dp, d) - | (FloatLit(_), Cast(d, Unknown(_), Float)) => matches(dp, d) - | (FloatLit(_), _) => DoesNotMatch - | (StringLit(s1), StringLit(s2)) => - if (s1 == s2) { - Matches(Environment.empty); - } else { - DoesNotMatch; - } - | (StringLit(_), Cast(d, String, Unknown(_))) => matches(dp, d) - | (StringLit(_), Cast(d, Unknown(_), String)) => matches(dp, d) - | (StringLit(_), _) => DoesNotMatch - - | (Ap(dp1, dp2), Ap(d1, d2)) => - switch (matches(dp1, d1)) { - | DoesNotMatch => DoesNotMatch - | IndetMatch => - switch (matches(dp2, d2)) { - | DoesNotMatch => DoesNotMatch - | IndetMatch - | Matches(_) => IndetMatch - } - | Matches(env1) => - switch (matches(dp2, d2)) { - | DoesNotMatch => DoesNotMatch - | IndetMatch => IndetMatch - | Matches(env2) => Matches(Environment.union(env1, env2)) - } - } - | ( - Ap(Constructor(ctr), dp_opt), - Cast(d, Sum(sm1) | Rec(_, Sum(sm1)), Sum(sm2) | Rec(_, Sum(sm2))), - ) => - switch (cast_sum_maps(sm1, sm2)) { - | Some(castmap) => matches_cast_Sum(ctr, Some(dp_opt), d, [castmap]) - | None => DoesNotMatch - } - - | (Ap(_, _), Cast(d, Sum(_) | Rec(_, Sum(_)), Unknown(_))) - | (Ap(_, _), Cast(d, Unknown(_), Sum(_) | Rec(_, Sum(_)))) => - matches(dp, d) - | (Ap(_, _), _) => DoesNotMatch - | (Constructor(ctr), Constructor(ctr')) => - ctr == ctr' ? Matches(Environment.empty) : DoesNotMatch - | ( - Constructor(ctr), - Cast(d, Sum(sm1) | Rec(_, Sum(sm1)), Sum(sm2) | Rec(_, Sum(sm2))), - ) => - switch (cast_sum_maps(sm1, sm2)) { - | Some(castmap) => matches_cast_Sum(ctr, None, d, [castmap]) - | None => DoesNotMatch - } - | (Constructor(_), Cast(d, Sum(_) | Rec(_, Sum(_)), Unknown(_))) => - matches(dp, d) - | (Constructor(_), Cast(d, Unknown(_), Sum(_) | Rec(_, Sum(_)))) => - matches(dp, d) - | (Constructor(_), _) => DoesNotMatch - - | (Tuple(dps), Tuple(ds)) => - if (List.length(dps) != List.length(ds)) { - DoesNotMatch; - } else { - List.fold_left2( - (result, dp, d) => - switch (result) { - | DoesNotMatch => DoesNotMatch - | IndetMatch => IndetMatch - | Matches(env) => - switch (matches(dp, d)) { - | DoesNotMatch => DoesNotMatch - | IndetMatch => IndetMatch - | Matches(env') => Matches(Environment.union(env, env')) - } - }, - Matches(Environment.empty), - dps, - ds, - ); - } - | (Tuple(dps), Cast(d, Prod(tys), Prod(tys'))) => - assert(List.length(tys) == List.length(tys')); - matches_cast_Tuple( - dps, - d, - List.map(p => [p], List.combine(tys, tys')), - ); - | (Tuple(dps), Cast(d, Prod(tys), Unknown(_))) => - matches_cast_Tuple( - dps, - d, - List.map( - p => [p], - List.combine(tys, List.init(List.length(tys), const_unknown)), - ), - ) - | (Tuple(dps), Cast(d, Unknown(_), Prod(tys'))) => - matches_cast_Tuple( - dps, - d, - List.map( - p => [p], - List.combine(List.init(List.length(tys'), const_unknown), tys'), - ), - ) - | (Tuple(_), Cast(_)) => DoesNotMatch - | (Tuple(_), _) => DoesNotMatch - | (Cons(_) | ListLit(_), Cast(d, List(ty1), List(ty2))) => - matches_cast_Cons(dp, d, [(ty1, ty2)]) - | (Cons(_) | ListLit(_), Cast(d, Unknown(_), List(ty2))) => - matches_cast_Cons(dp, d, [(Unknown(Internal), ty2)]) - | (Cons(_) | ListLit(_), Cast(d, List(ty1), Unknown(_))) => - matches_cast_Cons(dp, d, [(ty1, Unknown(Internal))]) - | (Cons(_, _), Cons(_, _)) - | (ListLit(_, _), Cons(_, _)) - | (Cons(_, _), ListLit(_)) - | (ListLit(_), ListLit(_)) => matches_cast_Cons(dp, d, []) - | (Cons(_) | ListLit(_), _) => DoesNotMatch - } -and matches_cast_Sum = - ( - ctr: string, - dp: option(DHPat.t), - d: DHExp.t, - castmaps: list(ConstructorMap.t((Typ.t, Typ.t))), - ) - : match_result => - switch (d) { - | Constructor(ctr') => - switch ( - dp, - castmaps |> List.map(ConstructorMap.find_opt(ctr')) |> OptUtil.sequence, - ) { - | (None, Some(_)) => - ctr == ctr' ? Matches(Environment.empty) : DoesNotMatch - | _ => DoesNotMatch - } - | Ap(Constructor(ctr'), d') => - switch ( - dp, - castmaps |> List.map(ConstructorMap.find_opt(ctr')) |> OptUtil.sequence, - ) { - | (Some(dp), Some(side_casts)) => - matches(dp, DHExp.apply_casts(d', side_casts)) - | _ => DoesNotMatch - } - | Cast(d', Sum(sm1) | Rec(_, Sum(sm1)), Sum(sm2) | Rec(_, Sum(sm2))) => - switch (cast_sum_maps(sm1, sm2)) { - | Some(castmap) => matches_cast_Sum(ctr, dp, d', [castmap, ...castmaps]) - | None => DoesNotMatch - } - | Cast(d', Sum(_) | Rec(_, Sum(_)), Unknown(_)) - | Cast(d', Unknown(_), Sum(_) | Rec(_, Sum(_))) => - matches_cast_Sum(ctr, dp, d', castmaps) - | FreeVar(_) - | InvalidText(_) - | Let(_) - | Module(_) - | TypAp(_) - | Ap(_) - | ApBuiltin(_) - | BinBoolOp(_) - | BinIntOp(_) - | BinFloatOp(_) - | BinStringOp(_) - | InconsistentBranches(_) - | EmptyHole(_) - | NonEmptyHole(_) - | FailedCast(_, _, _) - | Test(_) - | InvalidOperation(_) - | ConsistentCase(_) - | Prj(_) - | IfThenElse(_) - | BuiltinFun(_) => IndetMatch - | Cast(_) - | BoundVar(_) - | Dot(_) - | ModuleVal(_) - | FixF(_) - | TypFun(_) - | Fun(_) - | BoolLit(_) - | IntLit(_) - | FloatLit(_) - | StringLit(_) - | ListLit(_) - | Tuple(_) - | Sequence(_, _) - | Closure(_) - | Filter(_) - | Cons(_) - | ListConcat(_) => DoesNotMatch - } -and matches_cast_Tuple = - ( - dps: list(DHPat.t), - d: DHExp.t, - elt_casts: list(list((Typ.t, Typ.t))), - ) - : match_result => - switch (d) { - | Tuple(ds) => - if (List.length(dps) != List.length(ds)) { - DoesNotMatch; +let rec matches = (dp: Pat.t, d: DHExp.t): match_result => + switch (DHPat.term_of(dp)) { + | Invalid(_) + | EmptyHole + | MultiHole(_) + | Wild => Matches(Environment.empty) + | Int(n) => + let* n' = Unboxing.unbox(Int, d); + n == n' ? Matches(Environment.empty) : DoesNotMatch; + | Float(n) => + let* n' = Unboxing.unbox(Float, d); + n == n' ? Matches(Environment.empty) : DoesNotMatch; + | Bool(b) => + let* b' = Unboxing.unbox(Bool, d); + b == b' ? Matches(Environment.empty) : DoesNotMatch; + | String(s) => + let* s' = Unboxing.unbox(String, d); + s == s' ? Matches(Environment.empty) : DoesNotMatch; + | ListLit(xs) => + let* s' = Unboxing.unbox(List, d); + if (List.length(xs) == List.length(s')) { + List.map2(matches, xs, s') + |> List.fold_left(combine_result, Matches(Environment.empty)); } else { - assert(List.length(List.combine(dps, ds)) == List.length(elt_casts)); - List.fold_right( - (((dp, d), casts), result) => { - switch (result) { - | DoesNotMatch - | IndetMatch => result - | Matches(env) => - switch (matches(dp, DHExp.apply_casts(d, casts))) { - | DoesNotMatch => DoesNotMatch - | IndetMatch => IndetMatch - | Matches(env') => Matches(Environment.union(env, env')) - } - } - }, - List.combine(List.combine(dps, ds), elt_casts), - Matches(Environment.empty), - ); - } - | Cast(d', Prod(tys), Prod(tys')) => - if (List.length(dps) != List.length(tys)) { DoesNotMatch; - } else { - assert(List.length(tys) == List.length(tys')); - matches_cast_Tuple( - dps, - d', - List.map2(List.cons, List.combine(tys, tys'), elt_casts), - ); - } - | Cast(d', Prod(tys), Unknown(_)) => - let tys' = List.init(List.length(tys), const_unknown); - matches_cast_Tuple( - dps, - d', - List.map2(List.cons, List.combine(tys, tys'), elt_casts), - ); - | Cast(d', Unknown(_), Prod(tys')) => - let tys = List.init(List.length(tys'), const_unknown); - matches_cast_Tuple( - dps, - d', - List.map2(List.cons, List.combine(tys, tys'), elt_casts), - ); - | Cast(_, _, _) => DoesNotMatch - | BoundVar(_) => DoesNotMatch - | FreeVar(_) => IndetMatch - | InvalidText(_) => IndetMatch - | Let(_, _, _) => IndetMatch - | Module(_, _, _) => IndetMatch - | Dot(_, _) => IndetMatch - | FixF(_, _, _) => DoesNotMatch - | TypFun(_, _, _) => DoesNotMatch - | Fun(_, _, _, _) => DoesNotMatch - | Closure(_, Fun(_)) => DoesNotMatch - | Closure(_, _) => IndetMatch - | TypAp(_, _) => IndetMatch - | Filter(_, _) => IndetMatch - | Ap(_, _) => IndetMatch - | ApBuiltin(_, _) => IndetMatch - | BinBoolOp(_, _, _) - | BinIntOp(_, _, _) - | BinFloatOp(_, _, _) - | BinStringOp(_) - | BoolLit(_) => DoesNotMatch - | IntLit(_) => DoesNotMatch - | ModuleVal(_) => DoesNotMatch - | Sequence(_) - | BuiltinFun(_) - | Test(_) => DoesNotMatch - | FloatLit(_) => DoesNotMatch - | StringLit(_) => DoesNotMatch - | ListLit(_) => DoesNotMatch - | Cons(_, _) => DoesNotMatch - | ListConcat(_) => DoesNotMatch - | Prj(_) => IndetMatch - | Constructor(_) => DoesNotMatch - | ConsistentCase(_) - | InconsistentBranches(_) => IndetMatch - | EmptyHole(_) => IndetMatch - | NonEmptyHole(_) => IndetMatch - | FailedCast(_, _, _) => IndetMatch - | InvalidOperation(_) => IndetMatch - | IfThenElse(_) => IndetMatch - } -and matches_cast_Cons = - (dp: DHPat.t, d: DHExp.t, elt_casts: list((Typ.t, Typ.t))): match_result => - switch (d) { - | ListLit(_, _, _, []) => - switch (dp) { - | ListLit(_, []) => Matches(Environment.empty) - | _ => DoesNotMatch - } - | ListLit(u, i, ty, [dhd, ...dtl] as ds) => - switch (dp) { - | Cons(dp1, dp2) => - switch (matches(dp1, DHExp.apply_casts(dhd, elt_casts))) { - | DoesNotMatch => DoesNotMatch - | IndetMatch => IndetMatch - | Matches(env1) => - let list_casts = - List.map( - (c: (Typ.t, Typ.t)) => { - let (ty1, ty2) = c; - (Typ.List(ty1), Typ.List(ty2)); - }, - elt_casts, - ); - let d2 = DHExp.ListLit(u, i, ty, dtl); - switch (matches(dp2, DHExp.apply_casts(d2, list_casts))) { - | DoesNotMatch => DoesNotMatch - | IndetMatch => IndetMatch - | Matches(env2) => Matches(Environment.union(env1, env2)) - }; - } - | ListLit(_, dps) => - switch (ListUtil.opt_zip(dps, ds)) { - | None => DoesNotMatch - | Some(lst) => - lst - |> List.map(((dp, d)) => - matches(dp, DHExp.apply_casts(d, elt_casts)) - ) - |> List.fold_left( - (match1, match2) => - switch (match1, match2) { - | (DoesNotMatch, _) - | (_, DoesNotMatch) => DoesNotMatch - | (IndetMatch, _) - | (_, IndetMatch) => IndetMatch - | (Matches(env1), Matches(env2)) => - Matches(Environment.union(env1, env2)) - }, - Matches(Environment.empty), - ) - } - | _ => failwith("called matches_cast_Cons with non-list pattern") - } - | Cons(d1, d2) => - switch (dp) { - | Cons(dp1, dp2) => - switch (matches(dp1, DHExp.apply_casts(d1, elt_casts))) { - | DoesNotMatch => DoesNotMatch - | IndetMatch => IndetMatch - | Matches(env1) => - let list_casts = - List.map( - (c: (Typ.t, Typ.t)) => { - let (ty1, ty2) = c; - (Typ.List(ty1), Typ.List(ty2)); - }, - elt_casts, - ); - switch (matches(dp2, DHExp.apply_casts(d2, list_casts))) { - | DoesNotMatch => DoesNotMatch - | IndetMatch => IndetMatch - | Matches(env2) => Matches(Environment.union(env1, env2)) - }; - } - | ListLit(_, []) => DoesNotMatch - | ListLit(ty, [dphd, ...dptl]) => - switch (matches(dphd, DHExp.apply_casts(d1, elt_casts))) { - | DoesNotMatch => DoesNotMatch - | IndetMatch => IndetMatch - | Matches(env1) => - let list_casts = - List.map( - (c: (Typ.t, Typ.t)) => { - let (ty1, ty2) = c; - (Typ.List(ty1), Typ.List(ty2)); - }, - elt_casts, - ); - let dp2 = DHPat.ListLit(ty, dptl); - switch (matches(dp2, DHExp.apply_casts(d2, list_casts))) { - | DoesNotMatch => DoesNotMatch - | IndetMatch => IndetMatch - | Matches(env2) => Matches(Environment.union(env1, env2)) - }; - } - | _ => failwith("called matches_cast_Cons with non-list pattern") - } - | Cast(d', List(ty1), List(ty2)) => - matches_cast_Cons(dp, d', [(ty1, ty2), ...elt_casts]) - | Cast(d', List(ty1), Unknown(_)) => - matches_cast_Cons(dp, d', [(ty1, Unknown(Internal)), ...elt_casts]) - | Cast(d', Unknown(_), List(ty2)) => - matches_cast_Cons(dp, d', [(Unknown(Internal), ty2), ...elt_casts]) - | Cast(_, _, _) => DoesNotMatch - | BoundVar(_) => DoesNotMatch - | FreeVar(_) => IndetMatch - | InvalidText(_) => IndetMatch - | Let(_, _, _) => IndetMatch - | Module(_, _, _) => IndetMatch - | Dot(_, _) => IndetMatch - | FixF(_, _, _) => DoesNotMatch - | TypFun(_, _, _) => DoesNotMatch - | Fun(_, _, _, _) => DoesNotMatch - | Closure(_, d') => matches_cast_Cons(dp, d', elt_casts) - | TypAp(_, _) => IndetMatch - | Filter(_, d') => matches_cast_Cons(dp, d', elt_casts) - | Ap(_, _) => IndetMatch - | ApBuiltin(_, _) => IndetMatch - | BinBoolOp(_, _, _) - | BinIntOp(_, _, _) - | BinFloatOp(_, _, _) - | BinStringOp(_) - | ListConcat(_) - | BuiltinFun(_) => DoesNotMatch - | BoolLit(_) => DoesNotMatch - | IntLit(_) => DoesNotMatch - | ModuleVal(_) => DoesNotMatch - | Sequence(_) - | Test(_) => DoesNotMatch - | FloatLit(_) => DoesNotMatch - | StringLit(_) => DoesNotMatch - | Tuple(_) => DoesNotMatch - | Prj(_) => IndetMatch - | Constructor(_) => DoesNotMatch - | ConsistentCase(_) - | InconsistentBranches(_) => IndetMatch - | EmptyHole(_) => IndetMatch - | NonEmptyHole(_) => IndetMatch - | FailedCast(_, _, _) => IndetMatch - | InvalidOperation(_) => IndetMatch - | IfThenElse(_) => IndetMatch + }; + | Cons(x, xs) => + let* (x', xs') = Unboxing.unbox(Cons, d); + let* m_x = matches(x, x'); + let* m_xs = matches(xs, xs'); + Matches(Environment.union(m_x, m_xs)); + | Constructor(ctr, _) => + let* () = Unboxing.unbox(SumNoArg(ctr), d); + Matches(Environment.empty); + | Ap({term: Constructor(ctr, _), _}, p2) => + let* d2 = Unboxing.unbox(SumWithArg(ctr), d); + matches(p2, d2); + | Ap(_, _) => IndetMatch // TODO: should this fail? + | Var(x) => Matches(Environment.singleton((x, d))) + | Tuple(ps) => + let* ds = Unboxing.unbox(Tuple(List.length(ps)), d); + List.map2(matches, ps, ds) + |> List.fold_left(combine_result, Matches(Environment.empty)); + | Parens(p) => matches(p, d) + | Cast(p, t1, t2) => + matches(p, Cast(d, t2, t1) |> DHExp.fresh |> Casts.transition_multiple) }; diff --git a/src/haz3lcore/dynamics/PatternMatch.rei b/src/haz3lcore/dynamics/PatternMatch.rei deleted file mode 100644 index 96cf6019fa..0000000000 --- a/src/haz3lcore/dynamics/PatternMatch.rei +++ /dev/null @@ -1,6 +0,0 @@ -type match_result = - | Matches(Environment.t) - | DoesNotMatch - | IndetMatch; - -let matches: (DHPat.t, DHExp.t) => match_result; diff --git a/src/haz3lcore/dynamics/Stepper.re b/src/haz3lcore/dynamics/Stepper.re index 9e528af222..b23d3d9a4b 100644 --- a/src/haz3lcore/dynamics/Stepper.re +++ b/src/haz3lcore/dynamics/Stepper.re @@ -1,29 +1,24 @@ -open Sexplib.Std; open EvaluatorStep; open Transition; +open Util; exception Exception; -type step_with_previous = { - step, - previous: option(step), - hidden: list(step), -}; +[@deriving (show({with_path: false}), sexp, yojson)] +type stepper_state = + | StepPending(int) + | StepperReady + | StepperDone + | StepTimeout(EvalObj.t); [@deriving (show({with_path: false}), sexp, yojson)] -type current = - | StepperOK(DHExp.t, EvaluatorState.t) - | StepTimeout // Must have at least one in previous - | StepPending(DHExp.t, EvaluatorState.t, option(EvalObj.t)); // StepPending(_,Some(_)) cannot be saved +type history = Aba.t((DHExp.t, EvaluatorState.t), step); [@deriving (show({with_path: false}), sexp, yojson)] type t = { - /* Might be different to first expression in previous because - steps are taken automatically (this may no longer be true - Matt) */ - elab: DHExp.t, - previous: list(step), - current, - next: list((FilterAction.action, EvalObj.t)), + history, + next_options: list((FilterAction.action, EvalObj.t)), + stepper_state, }; let rec matches = @@ -36,170 +31,155 @@ let rec matches = idx: int, ) : (FilterAction.t, int, EvalCtx.t) => { - let composed = compose(ctx, exp); + let composed = EvalCtx.compose(ctx, exp); let (pact, pidx) = (act, idx); let (mact, midx) = FilterMatcher.matches(~env, ~exp=composed, ~act, flt); let (act, idx) = switch (ctx) { - | Filter(_, _) => (pact, pidx) + | Term({term: Filter(_, _), _}) => (pact, pidx) | _ => midx > pidx ? (mact, midx) : (pact, pidx) }; - let map = ((a, i, c), f: EvalCtx.t => EvalCtx.t) => { + let map = ((a, i, c), f) => { (a, i, f(c)); }; let (let+) = map; let (ract, ridx, rctx) = switch (ctx) { | Mark => (act, idx, EvalCtx.Mark) - | Closure(env, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Closure(env, ctx); - | Filter(Filter(flt'), ctx) => - let flt = flt |> FilterEnvironment.extends(flt'); - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Filter(Filter(flt'), ctx); - | Filter(Residue(idx', act'), ctx) => - let (ract, ridx, rctx) = - if (idx > idx') { - matches(env, flt, ctx, exp, act, idx); + | Term({term, ids}) => + let rewrap = term => EvalCtx.Term({term, ids}); + switch ((term: EvalCtx.term)) { + | Closure(env, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Closure(env, ctx) |> rewrap; + | Filter(Filter(flt'), ctx) => + let flt = flt |> FilterEnvironment.extends(flt'); + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Filter(Filter(flt'), ctx) |> rewrap; + | Filter(Residue(idx', act'), ctx) => + let (ract, ridx, rctx) = + if (idx > idx') { + matches(env, flt, ctx, exp, act, idx); + } else { + matches(env, flt, ctx, exp, act', idx'); + }; + if (act' |> snd == All) { + (ract, ridx, Filter(Residue(idx', act'), rctx) |> rewrap); } else { - matches(env, flt, ctx, exp, act', idx'); + (ract, ridx, rctx); }; - if (act' |> snd == All) { - (ract, ridx, Filter(Residue(idx', act'), rctx)); - } else { - (ract, ridx, rctx); + | Seq1(ctx, d2) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Seq1(ctx, d2) |> rewrap; + | Seq2(d1, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Seq2(d1, ctx) |> rewrap; + | Let1(d1, ctx, d3) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Let1(d1, ctx, d3) |> rewrap; + | Let2(d1, d2, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Let2(d1, d2, ctx) |> rewrap; + | Module1(d1, ctx, d3) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Module1(d1, ctx, d3) |> rewrap; + | Module2(d1, d2, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Module2(d1, d2, ctx) |> rewrap; + | Dot1(ctx, d2) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Dot1(ctx, d2) |> rewrap; + | Dot2(d1, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Dot2(d1, ctx) |> rewrap; + | Fun(dp, ctx, env', name) => + let+ ctx = + matches(Option.value(~default=env, env'), flt, ctx, exp, act, idx); + Fun(dp, ctx, env', name) |> rewrap; + | FixF(name, ctx, env') => + let+ ctx = + matches(Option.value(~default=env, env'), flt, ctx, exp, act, idx); + FixF(name, ctx, env') |> rewrap; + | Ap1(dir, ctx, d2) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Ap1(dir, ctx, d2) |> rewrap; + | Ap2(dir, d1, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Ap2(dir, d1, ctx) |> rewrap; + | TypAp(ctx, ty) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + TypAp(ctx, ty) |> rewrap; + | DeferredAp1(ctx, d2) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + DeferredAp1(ctx, d2) |> rewrap; + | DeferredAp2(d1, ctx, ds) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + DeferredAp2(d1, ctx, ds) |> rewrap; + | If1(ctx, d2, d3) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + If1(ctx, d2, d3) |> rewrap; + | If2(d1, ctx, d3) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + If2(d1, ctx, d3) |> rewrap; + | If3(d1, d2, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + If3(d1, d2, ctx) |> rewrap; + | UnOp(op, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + UnOp(op, ctx) |> rewrap; + | BinOp1(op, ctx, d1) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + BinOp1(op, ctx, d1) |> rewrap; + | BinOp2(op, d1, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + BinOp2(op, d1, ctx) |> rewrap; + | Tuple(ctx, ds) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Tuple(ctx, ds) |> rewrap; + | Test(ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Test(ctx) |> rewrap; + | ListLit(ctx, ds) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + ListLit(ctx, ds) |> rewrap; + | Cons1(ctx, d2) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Cons1(ctx, d2) |> rewrap; + | Cons2(d1, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Cons2(d1, ctx) |> rewrap; + | ListConcat1(ctx, d2) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + ListConcat1(ctx, d2) |> rewrap; + | ListConcat2(d1, ctx) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + ListConcat2(d1, ctx) |> rewrap; + | MultiHole(ctx, (dl, dr)) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + MultiHole(ctx, (dl, dr)) |> rewrap; + | Cast(ctx, ty, ty') => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + Cast(ctx, ty, ty') |> rewrap; + | FailedCast(ctx, ty, ty') => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + FailedCast(ctx, ty, ty') |> rewrap; + | DynamicErrorHole(ctx, error) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + DynamicErrorHole(ctx, error) |> rewrap; + | MatchScrut(ctx, rs) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + MatchScrut(ctx, rs) |> rewrap; + | MatchRule(scr, p, ctx, rs) => + let+ ctx = matches(env, flt, ctx, exp, act, idx); + MatchRule(scr, p, ctx, rs) |> rewrap; }; - | Sequence1(ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Sequence1(ctx, d2); - | Sequence2(d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Sequence2(d1, ctx); - | Let1(d1, ctx, d3) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Let1(d1, ctx, d3); - | Let2(d1, d2, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Let2(d1, d2, ctx); - | Module1(d1, ctx, d3) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Module1(d1, ctx, d3); - | Module2(d1, d2, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Module2(d1, d2, ctx); - | Dot1(ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Dot1(ctx, d2); - | Dot2(d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Dot2(d1, ctx); - | Fun(dp, ty, ctx, name) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Fun(dp, ty, ctx, name); - | FixF(name, ty, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - FixF(name, ty, ctx); - | TypAp(ctx, ty) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - TypAp(ctx, ty); - | Ap1(ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Ap1(ctx, d2); - | Ap2(d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Ap2(d1, ctx); - | IfThenElse1(c, ctx, d2, d3) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - IfThenElse1(c, ctx, d2, d3); - | IfThenElse2(c, d1, ctx, d3) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - IfThenElse2(c, d1, ctx, d3); - | IfThenElse3(c, d1, d2, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - IfThenElse3(c, d1, d2, ctx); - | BinBoolOp1(op, ctx, d1) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinBoolOp1(op, ctx, d1); - | BinBoolOp2(op, d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinBoolOp2(op, d1, ctx); - | BinIntOp1(op, ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinIntOp1(op, ctx, d2); - | BinIntOp2(op, d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinIntOp2(op, d1, ctx); - | BinFloatOp1(op, ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinFloatOp1(op, ctx, d2); - | BinFloatOp2(op, d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinFloatOp2(op, d1, ctx); - | BinStringOp1(op, ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinStringOp1(op, ctx, d2); - | BinStringOp2(op, d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - BinStringOp2(op, d1, ctx); - | Tuple(ctx, ds) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Tuple(ctx, ds); - | ApBuiltin(name, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - ApBuiltin(name, ctx); - | Test(id, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Test(id, ctx); - | ListLit(u, i, ty, ctx, ds) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - ListLit(u, i, ty, ctx, ds); - | Cons1(ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Cons1(ctx, d2); - | Cons2(d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Cons2(d1, ctx); - | ListConcat1(ctx, d2) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - ListConcat1(ctx, d2); - | ListConcat2(d1, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - ListConcat2(d1, ctx); - | Prj(ctx, n) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Prj(ctx, n); - | NonEmptyHole(e, u, i, ctx) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - NonEmptyHole(e, u, i, ctx); - | Cast(ctx, ty, ty') => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - Cast(ctx, ty, ty'); - | FailedCast(ctx, ty, ty') => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - FailedCast(ctx, ty, ty'); - | InvalidOperation(ctx, error) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - InvalidOperation(ctx, error); - | ConsistentCase(Case(ctx, rs, i)) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - ConsistentCase(Case(ctx, rs, i)); - | ConsistentCaseRule(dexp, dpat, ctx, rs, i) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - ConsistentCaseRule(dexp, dpat, ctx, rs, i); - | InconsistentBranches(u, i, Case(ctx, rs, ri)) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - InconsistentBranches(u, i, Case(ctx, rs, ri)); - | InconsistentBranchesRule(dexp, u, i, dpat, ctx, rs, ri) => - let+ ctx = matches(env, flt, ctx, exp, act, idx); - InconsistentBranchesRule(dexp, u, i, dpat, ctx, rs, ri); }; switch (ctx) { - | Filter(_) => (ract, ridx, rctx) + | Term({term: Filter(_), _}) => (ract, ridx, rctx) | _ when midx > pidx && mact |> snd == All => ( ract, ridx, - Filter(Residue(midx, mact), rctx), + Term({term: Filter(Residue(midx, mact), rctx), ids: [Id.mk()]}), ) | _ => (ract, ridx, rctx) }; @@ -230,104 +210,80 @@ let should_hide_step = (~settings, x: step): (FilterAction.action, step) => }; }; -let get_elab = ({elab, _}: t) => elab; +let get_elab = ({history, _}: t): Elaborator.Elaboration.t => { + let (d, _) = Aba.last_a(history); + {d: d}; +}; -let get_next_steps = s => s.next; +let get_next_steps = s => s.next_options |> List.map(snd); -let current_expr = (s: t) => - switch (s.current, s.previous) { - | (StepperOK(d, _), _) - | (StepPending(d, _, _), _) => d - | (StepTimeout, [x, ..._]) => x.d - | (StepTimeout, []) => s.elab - }; +let current_expr = ({history, _}: t) => Aba.hd(history) |> fst; -let step_pending = (idx: int, {elab, previous, current, next}: t) => { - // TODO[Matt]: change to nth_opt after refactor - let eo = List.nth(next, idx) |> snd; - switch (current) { - | StepperOK(d, s) => { - elab, - previous, - current: StepPending(d, s, Some(eo)), - next, - } - | StepTimeout => { - elab, - previous: List.tl(previous), - current: - StepPending( - List.hd(previous).d, - List.hd(previous).state, - Some(eo), - ), - next, - } - | StepPending(d, s, _) => { - elab, - previous, - current: StepPending(d, s, Some(eo)), - next, - } - }; +let current_state = ({history, _}: t) => Aba.hd(history) |> snd; + +let step_pending = (idx: int, stepper: t) => { + {...stepper, stepper_state: StepPending(idx)}; }; -let init = (~settings, elab: DHExp.t) => { +let init = (~settings, {d}: Elaborator.Elaboration.t) => { + let state = EvaluatorState.init; { - elab, - previous: [], - current: StepPending(elab, EvaluatorState.init, None), - next: decompose(~settings, elab), + history: Aba.singleton((d, state)), + next_options: decompose(~settings, d, state), + stepper_state: StepperReady, }; }; let rec evaluate_pending = (~settings, s: t) => { - switch (s.current) { - | StepperOK(_) - | StepTimeout => s - | StepPending(d, state, Some(eo)) => + switch (s.stepper_state) { + | StepperDone + | StepTimeout(_) => s + | StepperReady => + let next' = List.mapi((i, x) => (i, x), s.next_options); + switch ( + List.find_opt(((_, (act, _))) => act == FilterAction.Eval, next') + ) { + | Some((i, (_, _))) => + {...s, stepper_state: StepPending(i)} |> evaluate_pending(~settings) + | None => {...s, stepper_state: StepperDone} + }; + | StepPending(i) => + let (_, eo) = List.nth(s.next_options, i); + let (d, state) = Aba.hd(s.history); let state_ref = ref(state); let d_loc' = - switch (take_step(state_ref, eo.env, eo.d_loc)) { - | Some(d) => d - | None => raise(Exception) - }; - let d' = compose(eo.ctx, d_loc'); + ( + switch (take_step(state_ref, eo.env, eo.d_loc)) { + | Some(d) => d |> DHExp.repair_ids + | None => raise(Exception) + } + ) + |> DHExp.repair_ids; + let d' = EvalCtx.compose(eo.ctx, d_loc'); + let new_step = { + d, + d_loc: eo.d_loc, + d_loc', + ctx: eo.ctx, + knd: eo.knd, + state, + }; + let new_state = state_ref^; { - elab: s.elab, - previous: [ - {d, d_loc: eo.d_loc, ctx: eo.ctx, knd: eo.knd, state}, - ...s.previous, - ], - current: StepPending(d', state_ref^, None), - next: decompose(~settings, d'), + history: s.history |> Aba.cons((d', new_state), new_step), + stepper_state: StepperReady, + next_options: decompose(~settings, d', new_state), } |> evaluate_pending(~settings); - | StepPending(d, state, None) => - switch (List.find_opt(((act, _)) => act == FilterAction.Eval, s.next)) { - | Some((_, eo)) => - { - elab: s.elab, - previous: s.previous, - current: StepPending(d, state, Some(eo)), - next: s.next, - } - |> evaluate_pending(~settings) - | None => { - elab: s.elab, - previous: s.previous, - current: StepperOK(d, state), - next: s.next, - } - } }; }; let rec evaluate_full = (~settings, s: t) => { - switch (s.current) { - | StepTimeout => s - | StepperOK(_) when s.next == [] => s - | StepperOK(_) => s |> step_pending(0) |> evaluate_full(~settings) + switch (s.stepper_state) { + | StepTimeout(_) => s + | StepperDone when s.next_options == [] => s + | StepperDone => s |> step_pending(0) |> evaluate_full(~settings) + | StepperReady | StepPending(_) => evaluate_pending(~settings, s) |> evaluate_full(~settings) }; @@ -335,70 +291,49 @@ let rec evaluate_full = (~settings, s: t) => { let timeout = fun - | {elab, previous, current: StepPending(d, state, Some(eo)), next} => { - elab, - previous: [ - {d, d_loc: eo.d_loc, ctx: eo.ctx, knd: eo.knd, state}, - ...previous, - ], - current: StepTimeout, - next, + | {stepper_state: StepPending(idx), _} as s => { + ...s, + stepper_state: StepTimeout(List.nth(s.next_options, idx) |> snd), } - | {current: StepTimeout | StepperOK(_) | StepPending(_, _, None), _} as s => s; - -// let rec step_forward = (~settings, e: EvalObj.t, s: t) => { -// let current = compose(e.ctx, e.apply()); -// skip_steps( -// ~settings, -// { -// current, -// previous: [{d: s.current, step: e}, ...s.previous], -// next: decompose(current), -// }, -// ); -// } -// and skip_steps = (~settings, s) => { -// switch ( -// List.find_opt( -// (x: EvalObj.t) => should_hide_step(~settings, x.knd), -// s.next, -// ) -// ) { -// | None => s -// | Some(e) => step_forward(~settings, e, s) -// }; -// }; + | {stepper_state: StepTimeout(_) | StepperReady | StepperDone, _} as s => s; -let rec undo_point = - (~settings): (list(step) => option((step, list(step)))) => +let rec truncate_history = (~settings) => fun - | [] => None - | [x, ...xs] when should_hide_step(~settings, x) |> fst == Eval => - undo_point(~settings, xs) - | [x, ...xs] => Some((x, xs)); + | ([_, ...as_], [b, ...bs]) + when should_hide_step(~settings, b) |> fst == Eval => + truncate_history(~settings, (as_, bs)) + | ([_, ...as_], [_, ...bs]) => Some((as_, bs)) + | _ => None; -let step_backward = (~settings, s: t) => - switch (undo_point(~settings, s.previous)) { - | None => failwith("cannot step backwards") - | Some((x, xs)) => { - current: StepperOK(x.d, x.state), - next: decompose(~settings, x.d), - previous: xs, - elab: s.elab, - } +let step_backward = (~settings, s: t) => { + let h' = + truncate_history(~settings, s.history) + |> Option.value(~default=s.history); + { + history: h', + next_options: + decompose(~settings, Aba.hd(h') |> fst, Aba.hd(h') |> snd), + stepper_state: StepperDone, }; +}; + +let can_undo = (~settings, s: t) => { + truncate_history(~settings, s.history) |> Option.is_some; +}; let get_justification: step_kind => string = fun | LetBind => "substitution" | ModuleBind => "module substitution" - | Sequence => "sequence" + | Seq => "sequence" | FixUnwrap => "unroll fixpoint" | UpdateTest => "update test" | TypFunAp => "apply type function" | FunAp => "apply function" + | DeferredAp => "deferred application" | BuiltinWrap => "wrap builtin" | BuiltinAp(s) => "evaluate " ++ s + | UnOp(Int(Minus)) | BinIntOp(Plus | Minus | Times | Power | Divide) | BinFloatOp(Plus | Minus | Times | Power | Divide) => "arithmetic" | BinIntOp(LessThan | LessThanOrEqual | GreaterThan | GreaterThanOrEqual) @@ -407,12 +342,12 @@ let get_justification: step_kind => string = | BinFloatOp(Equals | NotEquals) | BinStringOp(Equals) => "check equality" | BinStringOp(Concat) => "string manipulation" + | UnOp(Bool(Not)) | BinBoolOp(_) => "boolean logic" | Conditional(_) => "conditional" | ListCons => "list manipulation" | ListConcat => "list manipulation" | CaseApply => "case selection" - | CaseNext => "case discarding" | Projection => "projection" // TODO(Matt): We don't want to show projection to the user | InvalidStep => "error" | VarLookup => "variable lookup" @@ -425,44 +360,84 @@ let get_justification: step_kind => string = | CompleteFilter => "complete filter" | CompleteClosure => "complete closure" | FunClosure => "function closure" - | Skip => "skipped steps"; + | RemoveTypeAlias => "define type" + | RemoveParens => "remove parentheses" + | UnOp(Meta(Unquote)) => failwith("INVALID STEP"); + +type step_info = { + d: DHExp.t, + chosen_step: option(step), // The step that was taken next + hidden_steps: list((step, Id.t)), // The hidden steps between previous_step and the current one (an Id in included because it may have changed since the step was taken) + previous_step: option((step, Id.t)) // The step that will be displayed above this one (an Id in included because it may have changed since the step was taken) +}; let get_history = (~settings, stepper) => { - let rec get_history': - list(step) => (list(step), list(step_with_previous)) = - fun - | [] => ([], []) - | [step, ...steps] => { - let (hidden, ss) = get_history'(steps); - switch (step |> should_hide_step(~settings) |> fst) { - | Eval => ([step, ...hidden], ss) - | Step => ( - [], - [ - { - step, - previous: - Option.map( - (x: step_with_previous) => x.step, - List.nth_opt(ss, 0), - ), - hidden, - }, - ...ss, - ], - ) - }; - }; - stepper.previous |> get_history'; + let should_skip_step = step => + step |> should_hide_step(~settings) |> fst == Eval; + let grouped_steps = + stepper.history + |> Aba.fold_right( + ((d, _), step, result) => + if (should_skip_step(step)) { + Aba.map_hd(((_, hs)) => (d, [step, ...hs]), result); + } else { + Aba.cons((d, []), step, result); + }, + ((d, _)) => Aba.singleton((d, [])), + ); + let replace_id = (x, y, (s, z)) => (s, x == z ? y : z); + let track_ids = + ( + ( + chosen_step: option(step), + (d: DHExp.t, hidden_steps: list(step)), + previous_step: option(step), + ), + ) => { + let (previous_step, hidden_steps) = + List.fold_left( + ((ps, hs), h: step) => { + let replacement = + replace_id(h.d_loc |> DHExp.rep_id, h.d_loc' |> DHExp.rep_id); + ( + Option.map(replacement, ps), + [(h, h.d_loc' |> DHExp.rep_id), ...List.map(replacement, hs)], + ); + }, + (Option.map(x => (x, x.d_loc' |> DHExp.rep_id), previous_step), []), + hidden_steps, + ); + {d, previous_step, hidden_steps, chosen_step}; + }; + let padded = grouped_steps |> Aba.bab_triples; + let result = padded |> List.map(track_ids); + result; + //grouped_steps |> Aba.bab_triples |> List.map(track_ids); }; -[@deriving (show({with_path: false}), sexp, yojson)] -type persistent = { - elab: DHExp.t, - previous: list(step), - current, +let hidden_steps_of_info = (info: step_info): list(step_info) => { + // note the previous_step field is fudged because it is currently usused.next_options + List.map( + ((hs: step, _)) => + { + d: hs.d, + chosen_step: Some(hs), + hidden_steps: [], + previous_step: None, + }, + info.hidden_steps, + ); }; +[@deriving (show({with_path: false}), sexp, yojson)] +type persistent = {history}; + +let (sexp_of_persistent, persistent_of_sexp) = + StructureShareSexp.structure_share_in( + sexp_of_persistent, + persistent_of_sexp, + ); + let (sexp_of_persistent, persistent_of_sexp) = StructureShareSexp.structure_share_in( sexp_of_persistent, @@ -470,16 +445,13 @@ let (sexp_of_persistent, persistent_of_sexp) = ); // Remove EvalObj.t objects from stepper to prevent problems when loading -let to_persistent: t => persistent = - fun - | {elab, previous, current: StepPending(d, state, Some(_)), _} => { - elab, - previous, - current: StepPending(d, state, None), - } - | {elab, previous, current, _} => {elab, previous, current}; +let to_persistent: t => persistent = ({history, _}) => {history: history}; -let from_persistent = (~settings, {elab, previous, current}) => { - let s = {elab, previous, current, next: []}; - {elab, previous, current, next: decompose(~settings, current_expr(s))}; +let from_persistent = (~settings, {history}) => { + { + history, + next_options: + decompose(~settings, Aba.hd(history) |> fst, Aba.hd(history) |> snd), + stepper_state: StepperDone, + }; }; diff --git a/src/haz3lcore/dynamics/Substitution.re b/src/haz3lcore/dynamics/Substitution.re index 521ec5dc49..3bcc910e3a 100644 --- a/src/haz3lcore/dynamics/Substitution.re +++ b/src/haz3lcore/dynamics/Substitution.re @@ -1,31 +1,32 @@ /* closed substitution [d1/x]d2 */ -let rec subst_var = (d1: DHExp.t, x: Var.t, d2: DHExp.t): DHExp.t => - switch (d2) { - | BoundVar(y) => +let rec subst_var = (m, d1: DHExp.t, x: Var.t, d2: DHExp.t): DHExp.t => { + let (term, rewrap) = DHExp.unwrap(d2); + switch (term) { + | Var(y) => if (Var.eq(x, y)) { d1; } else { d2; } - | FreeVar(_) => d2 - | InvalidText(_) => d2 - | Sequence(d3, d4) => - let d3 = subst_var(d1, x, d3); - let d4 = subst_var(d1, x, d4); - Sequence(d3, d4); + | Invalid(_) => d2 + | Undefined => d2 + | Seq(d3, d4) => + let d3 = subst_var(m, d1, x, d3); + let d4 = subst_var(m, d1, x, d4); + Seq(d3, d4) |> rewrap; | Filter(filter, dbody) => - let dbody = subst_var(d1, x, dbody); - let filter = subst_var_filter(d1, x, filter); - Filter(filter, dbody); + let dbody = subst_var(m, d1, x, dbody); + let filter = subst_var_filter(m, d1, x, filter); + Filter(filter, dbody) |> rewrap; | Let(dp, d3, d4) => - let d3 = subst_var(d1, x, d3); + let d3 = subst_var(m, d1, x, d3); let d4 = - if (DHPat.binds_var(x, dp)) { + if (DHPat.binds_var(m, x, dp)) { d4; } else { - subst_var(d1, x, d4); + subst_var(m, d1, x, d4); }; - Let(dp, d3, d4); + Let(dp, d3, d4) |> rewrap; | Module(dp, d3, d4) => let d3 = subst_var(d1, x, d3); let d4 = @@ -34,119 +35,116 @@ let rec subst_var = (d1: DHExp.t, x: Var.t, d2: DHExp.t): DHExp.t => } else { subst_var(d1, x, d4); }; - Module(dp, d3, d4); + Module(dp, d3, d4) |> rewrap; | Dot(d3, d4) => let d3 = subst_var(d1, x, d3); let d4 = subst_var(d1, x, d4); - Dot(d3, d4); + Dot(d3, d4) |> rewrap; | FixF(y, ty, d3) => + let env' = Option.map(subst_var_env(m, d1, x), env); let d3 = - if (Var.eq(x, y)) { + if (DHPat.binds_var(m, x, y)) { d3; } else { - subst_var(d1, x, d3); + subst_var(m, d1, x, d3); }; - FixF(y, ty, d3); - | Fun(dp, ty, d3, s) => - if (DHPat.binds_var(x, dp)) { - Fun(dp, ty, d3, s); + FixF(y, d3, env') |> rewrap; + | Fun(dp, d3, env, s) => + /* Function closure shouldn't appear during substitution + (which only is called from elaboration currently) */ + let env' = Option.map(subst_var_env(m, d1, x), env); + if (DHPat.binds_var(m, x, dp)) { + Fun(dp, d3, env', s) |> rewrap; } else { - let d3 = subst_var(d1, x, d3); - Fun(dp, ty, d3, s); - } - | TypFun(tpat, d3, s) => TypFun(tpat, subst_var(d1, x, d3), s) + let d3 = subst_var(m, d1, x, d3); + Fun(dp, d3, env', s) |> rewrap; + }; + | TypFun(tpat, d3, s) => + TypFun(tpat, subst_var(m, d1, x, d3), s) |> rewrap | Closure(env, d3) => /* Closure shouldn't appear during substitution (which only is called from elaboration currently) */ - let env' = subst_var_env(d1, x, env); - let d3' = subst_var(d1, x, d3); - Closure(env', d3'); - | Ap(d3, d4) => - let d3 = subst_var(d1, x, d3); - let d4 = subst_var(d1, x, d4); - Ap(d3, d4); - | TypAp(d3, ty) => TypAp(subst_var(d1, x, d3), ty) - | ApBuiltin(ident, args) => ApBuiltin(ident, subst_var(d1, x, args)) - | BuiltinFun(ident) => BuiltinFun(ident) - | Test(id, d3) => Test(id, subst_var(d1, x, d3)) - | BoolLit(_) - | IntLit(_) - | FloatLit(_) - | StringLit(_) - | ModuleVal(_) + let env' = subst_var_env(m, d1, x, env); + let d3' = subst_var(m, d1, x, d3); + Closure(env', d3') |> rewrap; + | Ap(dir, d3, d4) => + let d3 = subst_var(m, d1, x, d3); + let d4 = subst_var(m, d1, x, d4); + Ap(dir, d3, d4) |> rewrap; + | BuiltinFun(_) => d2 + | Test(d3) => Test(subst_var(m, d1, x, d3)) |> rewrap + | Bool(_) + | Int(_) + | Float(_) + | String(_) | Constructor(_) => d2 - | ListLit(a, b, c, ds) => - ListLit(a, b, c, List.map(subst_var(d1, x), ds)) + | ListLit(ds) => ListLit(List.map(subst_var(m, d1, x), ds)) |> rewrap | Cons(d3, d4) => - let d3 = subst_var(d1, x, d3); - let d4 = subst_var(d1, x, d4); - Cons(d3, d4); + let d3 = subst_var(m, d1, x, d3); + let d4 = subst_var(m, d1, x, d4); + Cons(d3, d4) |> rewrap; | ListConcat(d3, d4) => - let d3 = subst_var(d1, x, d3); - let d4 = subst_var(d1, x, d4); - ListConcat(d3, d4); - | Tuple(ds) => Tuple(List.map(subst_var(d1, x), ds)) - | Prj(d, n) => Prj(subst_var(d1, x, d), n) - | BinBoolOp(op, d3, d4) => - let d3 = subst_var(d1, x, d3); - let d4 = subst_var(d1, x, d4); - BinBoolOp(op, d3, d4); - | BinIntOp(op, d3, d4) => - let d3 = subst_var(d1, x, d3); - let d4 = subst_var(d1, x, d4); - BinIntOp(op, d3, d4); - | BinFloatOp(op, d3, d4) => - let d3 = subst_var(d1, x, d3); - let d4 = subst_var(d1, x, d4); - BinFloatOp(op, d3, d4); - | BinStringOp(op, d3, d4) => - let d3 = subst_var(d1, x, d3); - let d4 = subst_var(d1, x, d4); - BinStringOp(op, d3, d4); - | ConsistentCase(Case(d3, rules, n)) => - let d3 = subst_var(d1, x, d3); - let rules = subst_var_rules(d1, x, rules); - ConsistentCase(Case(d3, rules, n)); - | InconsistentBranches(u, i, Case(d3, rules, n)) => - let d3 = subst_var(d1, x, d3); - let rules = subst_var_rules(d1, x, rules); - InconsistentBranches(u, i, Case(d3, rules, n)); - | EmptyHole(u, i) => EmptyHole(u, i) - | NonEmptyHole(reason, u, i, d3) => - let d3' = subst_var(d1, x, d3); - NonEmptyHole(reason, u, i, d3'); + let d3 = subst_var(m, d1, x, d3); + let d4 = subst_var(m, d1, x, d4); + ListConcat(d3, d4) |> rewrap; + | Tuple(ds) => Tuple(List.map(subst_var(m, d1, x), ds)) |> rewrap + | UnOp(op, d3) => + let d3 = subst_var(m, d1, x, d3); + UnOp(op, d3) |> rewrap; + | BinOp(op, d3, d4) => + let d3 = subst_var(m, d1, x, d3); + let d4 = subst_var(m, d1, x, d4); + BinOp(op, d3, d4) |> rewrap; + | Match(ds, rules) => + let ds = subst_var(m, d1, x, ds); + let rules = + List.map( + ((p, v)) => + if (DHPat.binds_var(m, x, p)) { + (p, v); + } else { + (p, subst_var(m, d1, x, v)); + }, + rules, + ); + Match(ds, rules) |> rewrap; + | EmptyHole => EmptyHole |> rewrap + // TODO: handle multihole + | MultiHole(_d2) => d2 //MultiHole(List.map(subst_var(m, d1, x), ds)) |> rewrap | Cast(d, ty1, ty2) => - let d' = subst_var(d1, x, d); - Cast(d', ty1, ty2); + let d' = subst_var(m, d1, x, d); + Cast(d', ty1, ty2) |> rewrap; | FailedCast(d, ty1, ty2) => - let d' = subst_var(d1, x, d); - FailedCast(d', ty1, ty2); - | InvalidOperation(d, err) => - let d' = subst_var(d1, x, d); - InvalidOperation(d', err); - | IfThenElse(d3, d4, d5, d6) => - let d4' = subst_var(d1, x, d4); - let d5' = subst_var(d1, x, d5); - let d6' = subst_var(d1, x, d6); - IfThenElse(d3, d4', d5', d6'); - } - -and subst_var_rules = - (d1: DHExp.t, x: Var.t, rules: list(DHExp.rule)): list(DHExp.rule) => - rules - |> List.map((r: DHExp.rule) => - switch (r) { - | Rule(dp, d2) => - if (DHPat.binds_var(x, dp)) { - r; - } else { - Rule(dp, subst_var(d1, x, d2)); - } - } - ) + let d' = subst_var(m, d1, x, d); + FailedCast(d', ty1, ty2) |> rewrap; + | DynamicErrorHole(d, err) => + let d' = subst_var(m, d1, x, d); + DynamicErrorHole(d', err) |> rewrap; + | If(d4, d5, d6) => + let d4' = subst_var(m, d1, x, d4); + let d5' = subst_var(m, d1, x, d5); + let d6' = subst_var(m, d1, x, d6); + If(d4', d5', d6') |> rewrap; + | TyAlias(tp, ut, d4) => + let d4' = subst_var(m, d1, x, d4); + TyAlias(tp, ut, d4') |> rewrap; + | Parens(d4) => + let d4' = subst_var(m, d1, x, d4); + Parens(d4') |> rewrap; + | Deferral(_) => d2 + | DeferredAp(d3, d4s) => + let d3 = subst_var(m, d1, x, d3); + let d4s = List.map(subst_var(m, d1, x), d4s); + DeferredAp(d3, d4s) |> rewrap; + | TypAp(d3, ut) => + let d3 = subst_var(m, d1, x, d3); + TypAp(d3, ut) |> rewrap; + }; +} and subst_var_env = - (d1: DHExp.t, x: Var.t, env: ClosureEnvironment.t): ClosureEnvironment.t => { + (m, d1: DHExp.t, x: Var.t, env: ClosureEnvironment.t) + : ClosureEnvironment.t => { let id = env |> ClosureEnvironment.id_of; let map = env @@ -154,20 +152,20 @@ and subst_var_env = |> Environment.foldo( ((x', d': DHExp.t), map) => { let d' = - switch (d') { + switch (DHExp.term_of(d')) { /* Substitute each previously substituted binding into the * fixpoint. */ - | FixF(_) as d => + | FixF(_) => map |> Environment.foldo( - ((x'', d''), d) => subst_var(d'', x'', d), - d, + ((x'', d''), d) => subst_var(m, d'', x'', d), + d', ) - | d => d + | _ => d' }; /* Substitute. */ - let d' = subst_var(d1, x, d'); + let d' = subst_var(m, d1, x, d'); Environment.extend(map, (x', d')); }, Environment.empty, @@ -177,16 +175,17 @@ and subst_var_env = } and subst_var_filter = - (d1: DHExp.t, x: Var.t, flt: DH.DHFilter.t): DH.DHFilter.t => { - flt |> DH.DHFilter.map(subst_var(d1, x)); + (m, d1: DHExp.t, x: Var.t, flt: TermBase.StepperFilterKind.t) + : TermBase.StepperFilterKind.t => { + flt |> TermBase.StepperFilterKind.map(subst_var(m, d1, x)); }; -let subst = (env: Environment.t, d: DHExp.t): DHExp.t => +let subst = (m, env: Environment.t, d: DHExp.t): DHExp.t => env |> Environment.foldo( (xd: (Var.t, DHExp.t), d2) => { let (x, d1) = xd; - subst_var(d1, x, d2); + subst_var(m, d1, x, d2); }, d, ); diff --git a/src/haz3lcore/dynamics/Substitution.rei b/src/haz3lcore/dynamics/Substitution.rei index d413bf23c9..49b1e2e92f 100644 --- a/src/haz3lcore/dynamics/Substitution.rei +++ b/src/haz3lcore/dynamics/Substitution.rei @@ -1,3 +1,3 @@ /* closed substitution [d1/x]d2 */ -let subst_var: (DHExp.t, Var.t, DHExp.t) => DHExp.t; -let subst: (Environment.t, DHExp.t) => DHExp.t; +let subst_var: (Statics.Map.t, DHExp.t, Var.t, DHExp.t) => DHExp.t; +let subst: (Statics.Map.t, Environment.t, DHExp.t) => DHExp.t; diff --git a/src/haz3lcore/dynamics/TestMap.re b/src/haz3lcore/dynamics/TestMap.re index 0a77e62d21..74a5f8f550 100644 --- a/src/haz3lcore/dynamics/TestMap.re +++ b/src/haz3lcore/dynamics/TestMap.re @@ -1,14 +1,14 @@ -open Sexplib.Std; +open Util; /* FIXME: Make more obvious names. */ [@deriving (show({with_path: false}), sexp, yojson)] type instance_report = (DHExp.t, TestStatus.t); let joint_status: list(instance_report) => TestStatus.t = - reports => TestStatus.join_all(List.map(snd, reports)); + reports => TestStatus.join_all(List.map(((_, x)) => x, reports)); [@deriving (show({with_path: false}), sexp, yojson)] -type report = (KeywordID.t, list(instance_report)); +type report = (Id.t, list(instance_report)); [@deriving (show({with_path: false}), sexp, yojson)] type t = list(report); diff --git a/src/haz3lcore/dynamics/TestResults.re b/src/haz3lcore/dynamics/TestResults.re index d716d1ac05..bc0cdefe0a 100644 --- a/src/haz3lcore/dynamics/TestResults.re +++ b/src/haz3lcore/dynamics/TestResults.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type t = { diff --git a/src/haz3lcore/dynamics/Transition.re b/src/haz3lcore/dynamics/Transition.re index 1a3fdeed1a..9dcc89352e 100644 --- a/src/haz3lcore/dynamics/Transition.re +++ b/src/haz3lcore/dynamics/Transition.re @@ -1,19 +1,17 @@ -open Sexplib.Std; open Util; open PatternMatch; -open DH; /* Transition.re This module defines the evaluation semantics of Hazel in terms of small step evaluation. These small steps are wrapped up into a big step in Evaluator.re. - I'll use the Sequence case as an example: + I'll use the Seq case as an example: - | Sequence(d1, d2) => - let. _ = otherwise(d1 => Sequence(d1, d2)) + | Seq(d1, d2) => + let. _ = otherwise(d1 => Seq(d1, d2)) and. _ = req_final(req(state, env), 0, d1); - Step({apply: () => d2, kind: Sequence, final: false}); + Step({expr: d2, state, kind: Seq, final: false}); Each step semantics starts with a `let. () = otherwise(...)` that defines how @@ -34,9 +32,9 @@ open DH; secondly a `kind`, that describes the step (which will be used in the stepper) Lastly, the `value` field allows for some speeding up of the evaluator. If you - are unsure, it is always safe to put `value: false`. + are unsure, it is always safe to put `is_value: false`. - `value: true` guarantees: + `is_value: true` guarantees: - if all requirements are values, then the output will be a value - if some requirements are indet, then the output will be indet @@ -49,7 +47,7 @@ type step_kind = | InvalidStep | VarLookup | ModuleLookup - | Sequence + | Seq | LetBind | ModuleBind | DotAccess @@ -59,117 +57,26 @@ type step_kind = | UpdateTest | TypFunAp | FunAp + | DeferredAp | CastTypAp | CastAp | BuiltinWrap | BuiltinAp(string) - | BinBoolOp(TermBase.UExp.op_bin_bool) - | BinIntOp(TermBase.UExp.op_bin_int) - | BinFloatOp(TermBase.UExp.op_bin_float) - | BinStringOp(TermBase.UExp.op_bin_string) + | UnOp(Operators.op_un) + | BinBoolOp(Operators.op_bin_bool) + | BinIntOp(Operators.op_bin_int) + | BinFloatOp(Operators.op_bin_float) + | BinStringOp(Operators.op_bin_string) | Conditional(bool) | Projection | ListCons | ListConcat | CaseApply - | CaseNext | CompleteClosure | CompleteFilter | Cast - | Skip; - -module CastHelpers = { - [@deriving sexp] - type ground_cases = - | Hole - | Ground - | NotGroundOrHole(Typ.t) /* the argument is the corresponding ground type */; - - let const_unknown: 'a => Typ.t = _ => Unknown(Internal); - - let grounded_Arrow = - NotGroundOrHole(Arrow(Unknown(Internal), Unknown(Internal))); - // TODO: Maybe the Forall should allow a hole in the variable position? - let grounded_Forall = - NotGroundOrHole(Forall("grounded_forall", Unknown(Internal))); - let grounded_Prod = length => - NotGroundOrHole( - Prod(ListUtil.replicate(length, Typ.Unknown(Internal))), - ); - let grounded_Sum = (sm: Typ.sum_map): ground_cases => { - let sm' = sm |> ConstructorMap.map(Option.map(const_unknown)); - NotGroundOrHole(Sum(sm')); - }; - let grounded_List = NotGroundOrHole(List(Unknown(Internal))); - let grounded_Module = (ctx: Ctx.t) => - NotGroundOrHole( - Typ.Module({ - inner_ctx: - List.map( - fun - | Ctx.VarEntry(var_entry) => - Ctx.VarEntry({...var_entry, typ: Unknown(Internal)}) - | Ctx.ConstructorEntry(var_entry) => - Ctx.ConstructorEntry({...var_entry, typ: Unknown(Internal)}) - | Ctx.TVarEntry(tvar_entry) => Ctx.TVarEntry(tvar_entry), - ctx, - ), - incomplete: false, - }), - ); - - let rec ground_cases_of = (ty: Typ.t): ground_cases => { - let is_ground_arg: option(Typ.t) => bool = - fun - | None - | Some(Typ.Unknown(_)) => true - | Some(ty) => ground_cases_of(ty) == Ground; - switch (ty) { - | Unknown(_) => Hole - | Bool - | Int - | Float - | String - | Var(_) - | Rec(_) - | Forall(_, Unknown(_)) - | Arrow(Unknown(_), Unknown(_)) - | List(Unknown(_)) => Ground - | Prod(tys) => - if (List.for_all( - fun - | Typ.Unknown(_) => true - | _ => false, - tys, - )) { - Ground; - } else { - tys |> List.length |> grounded_Prod; - } - | Module({inner_ctx: [], incomplete: true}) => Ground - | Module(_) => NotGroundOrHole(Module({inner_ctx: [], incomplete: true})) - | Sum(sm) => - sm |> ConstructorMap.is_ground(is_ground_arg) - ? Ground : grounded_Sum(sm) - | Arrow(_, _) => grounded_Arrow - | Forall(_) => grounded_Forall - | List(_) => grounded_List - | Member(_, ty) => ground_cases_of(ty) - }; - }; -}; - -let rec unbox_list = (d: DHExp.t): DHExp.t => - switch (d) { - | Cast(d, List(t1), List(t2)) => - switch (unbox_list(d)) { - | ListLit(u, i, _, xs) => - ListLit(u, i, t2, List.map(x => DHExp.Cast(x, t1, t2), xs)) - | d => d - } - | d => d - }; - + | RemoveTypeAlias + | RemoveParens; let evaluate_extend_env = (new_bindings: Environment.t, to_extend: ClosureEnvironment.t) : ClosureEnvironment.t => { @@ -181,13 +88,21 @@ let evaluate_extend_env = type rule = | Step({ - apply: unit => DHExp.t, + expr: DHExp.t, + state_update: unit => unit, kind: step_kind, - value: bool, + is_value: bool, }) | Constructor | Indet; +let (let-unbox) = ((request, v), f) => + switch (Unboxing.unbox(request, v)) { + | IndetMatch + | DoesNotMatch => Indet + | Matches(n) => f(n) + }; + module type EV_MODE = { type state; type result; @@ -214,6 +129,9 @@ module type EV_MODE = { list(DHExp.t) ) => requirement(list(DHExp.t)); + let req_final_or_value: + (DHExp.t => result, EvalCtx.t => EvalCtx.t, DHExp.t) => + requirement((DHExp.t, bool)); let (let.): (requirements('a, DHExp.t), 'a => rule) => result; let (and.): @@ -221,14 +139,17 @@ module type EV_MODE = { requirements(('a, 'c), 'b); let otherwise: (ClosureEnvironment.t, 'a) => requirements(unit, 'a); - let update_test: (state, KeywordID.t, TestMap.instance_report) => unit; + let update_test: (state, Id.t, TestMap.instance_report) => unit; }; module Transition = (EV: EV_MODE) => { open EV; open DHExp; - let (let.match) = ((env, match_result), r) => + // Default state update + let state_update = () => (); + + let (let.match) = ((env, match_result: PatternMatch.match_result), r) => switch (match_result) { | IndetMatch | DoesNotMatch => Indet @@ -251,45 +172,71 @@ module Transition = (EV: EV_MODE) => { }; }; - let transition = (req, state, env, d): 'a => - switch (d) { - | BoundVar(x) => - let. _ = otherwise(env, BoundVar(x)); - let d = - ClosureEnvironment.lookup(env, x) - |> OptUtil.get(() => { - raise(EvaluatorError.Exception(FreeInvalidVar(x))) - }); - Step({apply: () => d, kind: VarLookup, value: false}); - | Sequence(d1, d2) => - let. _ = otherwise(env, d1 => Sequence(d1, d2)) - and. _ = req_final(req(state, env), d1 => Sequence1(d1, d2), d1); - Step({apply: () => d2, kind: Sequence, value: false}); + /* Note[Matt]: For IDs, I'm currently using a fresh id + if anything about the current node changes, if only its + children change, we use rewrap */ + + let transition = (req, state, env, d): 'a => { + // Split DHExp into term and id information + let (term, rewrap) = DHExp.unwrap(d); + let wrap_ctx = (term): EvalCtx.t => Term({term, ids: [rep_id(d)]}); + + // Transition rules + switch (term) { + | Var(x) => + let. _ = otherwise(env, Var(x) |> rewrap); + switch (ClosureEnvironment.lookup(env, x)) { + | Some(d) => + Step({ + expr: d |> fast_copy(Id.mk()), + state_update, + kind: VarLookup, + is_value: false, + }) + | None => Indet + }; + | Seq(d1, d2) => + let. _ = otherwise(env, d1 => Seq(d1, d2) |> rewrap) + and. _ = + req_final(req(state, env), d1 => Seq1(d1, d2) |> wrap_ctx, d1); + Step({expr: d2, state_update, kind: Seq, is_value: false}); | Let(dp, d1, d2) => - let. _ = otherwise(env, d1 => Let(dp, d1, d2)) - and. d1' = req_final(req(state, env), d1 => Let1(dp, d1, d2), d1); + let. _ = otherwise(env, d1 => Let(dp, d1, d2) |> rewrap) + and. d1' = + req_final(req(state, env), d1 => Let1(dp, d1, d2) |> wrap_ctx, d1); let result = matches(dp, d1'); let d2' = extend_module(d2, result); let.match env' = (env, result); - Step({apply: () => Closure(env', d2'), kind: LetBind, value: false}); + Step({ + expr: Closure(env', d2) |> fresh, + state_update, + kind: LetBind, + is_value: false, + }); | Module(dp, d1, d2) => - let. _ = otherwise(env, d1 => Module(dp, d1, d2)) - and. d1' = req_final(req(state, env), d1 => Module1(dp, d1, d2), d1); + let. _ = otherwise(env, d1 => Module(dp, d1, d2) |> rewrap) + and. d1' = + req_final( + req(state, env), + d1 => Module1(dp, d1, d2) |> wrap_ctx, + d1, + ); let result = matches(dp, d1'); let d2' = extend_module(d2, result); let.match env' = (env, result); Step({ - apply: () => Closure(env', d2'), + apply: () => Closure(env', d2') |> fresh, kind: ModuleBind, value: false, }); | Dot(d1, d2) => - let. _ = otherwise(env, d1 => Dot(d1, d2)) - and. d1' = req_value(req(state, env), d1 => Dot1(d1, d2), d1); + let. _ = otherwise(env, d1 => Dot(d1, d2) |> rewrap) + and. d1' = + req_value(req(state, env), d1 => Dot1(d1, d2) |> wrap_ctx, d1); switch (d1', d2) { | (ModuleVal(inner_env, _), _) => Step({ - apply: () => Closure(inner_env, d2), + apply: () => Closure(inner_env, d2) |> fresh, kind: DotAccess, value: false, }) @@ -319,504 +266,589 @@ module Transition = (EV: EV_MODE) => { | _ => Indet }; | TypFun(_) - | Fun(_, _, Closure(_), _) => + | Fun(_, _, Some(_), _) => let. _ = otherwise(env, d); Constructor; - | Fun(p, t, d, v) => - let. _ = otherwise(env, Fun(p, t, d, v)); + | Fun(p, d1, None, v) => + let. _ = otherwise(env, d); Step({ - apply: () => Fun(p, t, Closure(env, d), v), + expr: Fun(p, d1, Some(env), v) |> rewrap, + state_update, kind: FunClosure, - value: true, + is_value: true, }); - | FixF(f, _, Closure(env, d1)) => - let. _ = otherwise(env, d); - let env' = evaluate_extend_env(Environment.singleton((f, d)), env); - Step({apply: () => Closure(env', d1), kind: FixUnwrap, value: false}); - | FixF(f, t, d1) => - let. _ = otherwise(env, FixF(f, t, d1)); + | FixF(dp, d1, None) => + let. _ = otherwise(env, FixF(dp, d1, None) |> rewrap); Step({ - apply: () => FixF(f, t, Closure(env, d1)), + expr: FixF(dp, d1, Some(env)) |> rewrap, + state_update, kind: FixClosure, - value: false, + is_value: false, }); - | Test(id, d) => - let. _ = otherwise(env, d => Test(id, d)) - and. d' = req_final(req(state, env), d => Test(id, d), d); + | FixF(dp, d1, Some(env)) => + switch (DHPat.get_var(dp)) { + // Simple Recursion case + | Some(f) => + let. _ = otherwise(env, d); + let env'' = + evaluate_extend_env( + Environment.singleton((f, FixF(dp, d1, Some(env)) |> rewrap)), + env, + ); + Step({ + expr: Closure(env'', d1) |> fresh, + state_update, + kind: FixUnwrap, + is_value: false, + }); + // Mutual Recursion case + | None => + let. _ = otherwise(env, d); + let bindings = DHPat.bound_vars(dp); + let substitutions = + List.map( + binding => + ( + binding, + Let( + dp, + FixF(dp, d1, Some(env)) |> rewrap, + Var(binding) |> fresh, + ) + |> fresh, + ), + bindings, + ); + let env'' = + evaluate_extend_env(Environment.of_list(substitutions), env); + Step({ + expr: Closure(env'', d1) |> fresh, + state_update, + kind: FixUnwrap, + is_value: false, + }); + } + | Test(d'') => + let. _ = otherwise(env, ((d, _)) => Test(d) |> rewrap) + and. (d', is_value) = + req_final_or_value(req(state, env), d => Test(d) |> wrap_ctx, d''); + let result: TestStatus.t = + if (is_value) { + switch (Unboxing.unbox(Bool, d')) { + | DoesNotMatch + | IndetMatch => Indet + | Matches(b) => b ? Pass : Fail + }; + } else { + Indet; + }; Step({ - apply: () => - switch (d') { - | BoolLit(true) => - update_test(state, id, (d', Pass)); - Tuple([]); - | BoolLit(false) => - update_test(state, id, (d', Fail)); - Tuple([]); - /* Hack: assume if final and not Bool, then Indet; this won't catch errors in statics */ - | _ => - update_test(state, id, (d', Indet)); - Tuple([]); - }, + expr: Tuple([]) |> fresh, + state_update: () => + update_test(state, DHExp.rep_id(d), (d', result)), kind: UpdateTest, - value: true, + is_value: true, }); | TypAp(d, tau) => - let. _ = otherwise(env, d => TypAp(d, tau)) - and. d' = req_value(req(state, env), d => TypAp(d, tau), d); - switch (d') { + let. _ = otherwise(env, d => TypAp(d, tau) |> rewrap) + and. d' = + req_value(req(state, env), d => TypAp(d, tau) |> wrap_ctx, d); + switch (DHExp.term_of(d')) { | TypFun(utpat, tfbody, name) => /* Rule ITTLam */ - switch (Term.UTPat.tyvar_of_utpat(utpat)) { - | Some(tyvar) => - /* Perform substitution */ - Step({ - apply: () => - DHExp.assign_name_if_none( - /* Inherit name for user clarity */ - DHExp.ty_subst(tau, tyvar, tfbody), - Option.map( - x => x ++ "@<" ++ Typ.pretty_print(tau) ++ ">", - name, - ), - ), - kind: TypFunAp, - value: false, - }) - | None => - /* Treat a hole or invalid tyvar name as a unique type variable that doesn't appear anywhere else. Thus instantiating it at anything doesn't produce any substitutions. */ - Step({ - apply: () => - DHExp.assign_name_if_none( - tfbody, - Option.map( - x => x ++ "@<" ++ Typ.pretty_print(tau) ++ ">", - name, - ), + Step({ + expr: + DHExp.assign_name_if_none( + /* Inherit name for user clarity */ + DHExp.ty_subst(tau, utpat, tfbody), + Option.map( + x => x ++ "@<" ++ Typ.pretty_print(tau) ++ ">", + name, ), - kind: TypFunAp, - value: false, - }) - } - | Cast(d'', Forall(x, t), Forall(x', t')) => + ), + state_update, + kind: TypFunAp, + is_value: false, + }) + | Cast( + d'', + {term: Forall(tp1, _), _} as t1, + {term: Forall(tp2, _), _} as t2, + ) => /* Rule ITTApCast */ Step({ - apply: () => + expr: Cast( - TypAp(d'', tau), - Typ.subst(tau, x, t), - Typ.subst(tau, x', t'), - ), + TypAp(d'', tau) |> Exp.fresh, + Typ.subst(tau, tp1, t1), + Typ.subst(tau, tp2, t2), + ) + |> Exp.fresh, + state_update, kind: CastTypAp, - value: false, - }) - | _ => - Step({ - apply: () => { - raise(EvaluatorError.Exception(InvalidBoxedTypFun(d'))); - }, - kind: InvalidStep, - value: true, + is_value: false, }) + | _ => raise(EvaluatorError.Exception(InvalidBoxedTypFun(d'))) }; - | Ap(d1, d2) => - let. _ = otherwise(env, (d1, d2) => Ap(d1, d2)) - and. d1' = req_value(req(state, env), d1 => Ap1(d1, d2), d1) - and. d2' = req_final(req(state, env), d2 => Ap2(d1, d2), d2); - switch (d1') { + | DeferredAp(d1, ds) => + let. _ = otherwise(env, (d1, ds) => DeferredAp(d1, ds) |> rewrap) + and. _ = + req_final( + req(state, env), + d1 => DeferredAp1(d1, ds) |> wrap_ctx, + d1, + ) + and. _ = + req_all_final( + req(state, env), + (d2, ds) => DeferredAp2(d1, d2, ds) |> wrap_ctx, + ds, + ); + Constructor; + | Ap(dir, d1, d2) => + let. _ = otherwise(env, (d1, (d2, _)) => Ap(dir, d1, d2) |> rewrap) + and. d1' = + req_value(req(state, env), d1 => Ap1(dir, d1, d2) |> wrap_ctx, d1) + and. (d2', d2_is_value) = + req_final_or_value( + req(state, env), + d2 => Ap2(dir, d1, d2) |> wrap_ctx, + d2, + ); + switch (DHExp.term_of(d1')) { | Constructor(_) => Constructor - | Fun(dp, _, Closure(env', d3), _) => + | Fun(dp, d3, Some(env'), _) => let.match env'' = (env', matches(dp, d2')); - Step({apply: () => Closure(env'', d3), kind: FunAp, value: false}); - | Cast(d3', Arrow(ty1, ty2), Arrow(ty1', ty2')) => Step({ - apply: () => Cast(Ap(d3', Cast(d2', ty1', ty1)), ty2, ty2'), + expr: Closure(env'', d3) |> fresh, + state_update, + kind: FunAp, + is_value: false, + }); + | Cast( + d3', + {term: Arrow(ty1, ty2), _}, + {term: Arrow(ty1', ty2'), _}, + ) => + Step({ + expr: + Cast( + Ap(dir, d3', Cast(d2', ty1', ty1) |> fresh) |> fresh, + ty2, + ty2', + ) + |> fresh, + state_update, kind: CastAp, - value: false, + is_value: false, }) | BuiltinFun(ident) => + if (d2_is_value) { + Step({ + expr: { + let builtin = + VarMap.lookup(Builtins.forms_init, ident) + |> OptUtil.get(() => { + /* This exception should never be raised because there is + no way for the user to create a BuiltinFun. They are all + inserted into the context before evaluation. */ + raise( + EvaluatorError.Exception(InvalidBuiltin(ident)), + ) + }); + builtin(d2'); + }, + state_update, + kind: BuiltinAp(ident), + is_value: false // Not necessarily a value because of InvalidOperations + }); + } else { + Indet; + } + /* This case isn't currently used because deferrals are elaborated away */ + | DeferredAp(d3, d4s) => + let n_args = + List.length( + List.map( + fun + | {term: Deferral(_), _} => true + | _ => false: Exp.t => bool, + d4s, + ), + ); + let-unbox args = (Tuple(n_args), d2); + let new_args = { + let rec go = (deferred, args) => + switch ((deferred: list(Exp.t))) { + | [] => [] + | [{term: Deferral(_), _}, ...deferred] => + /* I can use List.hd and List.tl here because let-unbox ensure that + there are the correct number of args */ + [List.hd(args), ...go(deferred, List.tl(args))] + | [x, ...deferred] => [x, ...go(deferred, args)] + }; + go(d4s, args); + }; Step({ - apply: () => { - //HACK[Matt]: This step is just so we can check that d2' is not indet - ApBuiltin( - ident, - d2', - ); - }, - kind: BuiltinWrap, - value: false // Not necessarily a value because of InvalidOperations - }) + expr: Ap(Forward, d3, Tuple(new_args) |> fresh) |> fresh, + state_update, + kind: DeferredAp, + is_value: false, + }); + | Cast(_) + | FailedCast(_) => Indet + | FixF(_) => + print_endline(Exp.show(d1)); + print_endline(Exp.show(d1')); + print_endline("FIXF"); + failwith("FixF in Ap"); | _ => Step({ - apply: () => { + expr: { raise(EvaluatorError.Exception(InvalidBoxedFun(d1'))); }, + state_update, kind: InvalidStep, - value: true, + is_value: true, }) }; - | ApBuiltin(ident, arg) => - let. _ = otherwise(env, arg => ApBuiltin(ident, arg)) - and. arg' = - req_value(req(state, env), arg => ApBuiltin(ident, arg), arg); - Step({ - apply: () => { - let builtin = - VarMap.lookup(Builtins.forms_init, ident) - |> OptUtil.get(() => { - raise(EvaluatorError.Exception(InvalidBuiltin(ident))) - }); - builtin(arg'); - }, - kind: BuiltinAp(ident), - value: false // Not necessarily a value because of InvalidOperations - }); - | BoolLit(_) - | IntLit(_) - | FloatLit(_) - | StringLit(_) - | ModuleVal(_) => + | Deferral(_) => let. _ = otherwise(env, d); - Constructor; - | Constructor(x) => - let. _ = otherwise(env, d); - switch (ClosureEnvironment.lookup(env, x)) { - | None => Constructor - | Some(d) => Step({apply: () => d, kind: ModuleLookup, value: false}) - }; - + Indet; + | Bool(_) + | Int(_) + | Float(_) + | String(_) + | ModuleVal(_) + | Constructor(_) | BuiltinFun(_) => let. _ = otherwise(env, d); Constructor; - | IfThenElse(consistent, c, d1, d2) => - let. _ = otherwise(env, c => IfThenElse(consistent, c, d1, d2)) + | If(c, d1, d2) => + let. _ = otherwise(env, c => If(c, d1, d2) |> rewrap) and. c' = + req_value(req(state, env), c => If1(c, d1, d2) |> wrap_ctx, c); + let-unbox b = (Bool, c'); + Step({ + expr: { + b ? d1 : d2; + }, + state_update, + // Attach c' to indicate which branch taken. + kind: Conditional(b), + is_value: false, + }); + | UnOp(Meta(Unquote), _) => + let. _ = otherwise(env, d); + Indet; + | UnOp(Int(Minus), d1) => + let. _ = otherwise(env, d1 => UnOp(Int(Minus), d1) |> rewrap) + and. d1' = req_value( req(state, env), - c => IfThenElse1(consistent, c, d1, d2), - c, + c => UnOp(Int(Minus), c) |> wrap_ctx, + d1, ); - switch (consistent, c') { - | (ConsistentIf, BoolLit(b)) => - Step({ - apply: () => { - b ? d1 : d2; - }, - // Attach c' to indicate which branch taken. - kind: Conditional(b), - value: false, - }) - // Use a seperate case for invalid conditionals. Makes extracting the bool from BoolLit (above) easier. - | (ConsistentIf, _) => - Step({ - apply: () => { - raise(EvaluatorError.Exception(InvalidBoxedBoolLit(c'))); - }, - kind: InvalidStep, - value: true, - }) - // Inconsistent branches should be Indet - | (InconsistentIf, _) => Indet - }; - | BinBoolOp(And, d1, d2) => - let. _ = otherwise(env, d1 => BinBoolOp(And, d1, d2)) + let-unbox n = (Int, d1'); + Step({ + expr: Int(- n) |> fresh, + state_update, + kind: UnOp(Int(Minus)), + is_value: true, + }); + | UnOp(Bool(Not), d1) => + let. _ = otherwise(env, d1 => UnOp(Bool(Not), d1) |> rewrap) and. d1' = - req_value(req(state, env), d1 => BinBoolOp1(And, d1, d2), d1); + req_value( + req(state, env), + c => UnOp(Bool(Not), c) |> wrap_ctx, + d1, + ); + let-unbox b = (Bool, d1'); Step({ - apply: () => - switch (d1') { - | BoolLit(true) => d2 - | BoolLit(false) => BoolLit(false) - | _ => raise(EvaluatorError.Exception(InvalidBoxedBoolLit(d1'))) - }, + expr: Bool(!b) |> fresh, + state_update, + kind: UnOp(Bool(Not)), + is_value: true, + }); + | BinOp(Bool(And), d1, d2) => + let. _ = otherwise(env, d1 => BinOp(Bool(And), d1, d2) |> rewrap) + and. d1' = + req_value( + req(state, env), + d1 => BinOp1(Bool(And), d1, d2) |> wrap_ctx, + d1, + ); + let-unbox b1 = (Bool, d1'); + Step({ + expr: b1 ? d2 : Bool(false) |> fresh, + state_update, kind: BinBoolOp(And), - value: false, + is_value: false, }); - | BinBoolOp(Or, d1, d2) => - let. _ = otherwise(env, d1 => BinBoolOp(Or, d1, d2)) + | BinOp(Bool(Or), d1, d2) => + let. _ = otherwise(env, d1 => BinOp(Bool(Or), d1, d2) |> rewrap) and. d1' = - req_value(req(state, env), d1 => BinBoolOp1(Or, d1, d2), d1); + req_value( + req(state, env), + d1 => BinOp1(Bool(Or), d1, d2) |> wrap_ctx, + d1, + ); + let-unbox b1 = (Bool, d1'); Step({ - apply: () => - switch (d1') { - | BoolLit(true) => BoolLit(true) - | BoolLit(false) => d2 - | _ => raise(EvaluatorError.Exception(InvalidBoxedBoolLit(d2))) - }, + expr: b1 ? Bool(true) |> fresh : d2, + state_update, kind: BinBoolOp(Or), - value: false, + is_value: false, }); - | BinIntOp(op, d1, d2) => - let. _ = otherwise(env, (d1, d2) => BinIntOp(op, d1, d2)) - and. d1' = req_value(req(state, env), d1 => BinIntOp1(op, d1, d2), d1) + | BinOp(Int(op), d1, d2) => + let. _ = otherwise(env, (d1, d2) => BinOp(Int(op), d1, d2) |> rewrap) + and. d1' = + req_value( + req(state, env), + d1 => BinOp1(Int(op), d1, d2) |> wrap_ctx, + d1, + ) and. d2' = - req_value(req(state, env), d2 => BinIntOp2(op, d1, d2), d2); + req_value( + req(state, env), + d2 => BinOp2(Int(op), d1, d2) |> wrap_ctx, + d2, + ); + let-unbox n1 = (Int, d1'); + let-unbox n2 = (Int, d2'); Step({ - apply: () => - switch (d1', d2') { - | (IntLit(n1), IntLit(n2)) => + expr: + ( switch (op) { - | Plus => IntLit(n1 + n2) - | Minus => IntLit(n1 - n2) + | Plus => Int(n1 + n2) + | Minus => Int(n1 - n2) | Power when n2 < 0 => - InvalidOperation( - BinIntOp(op, IntLit(n1), IntLit(n2)), + DynamicErrorHole( + BinOp(Int(op), d1', d2') |> rewrap, NegativeExponent, ) - | Power => IntLit(IntUtil.ipow(n1, n2)) - | Times => IntLit(n1 * n2) + | Power => Int(IntUtil.ipow(n1, n2)) + | Times => Int(n1 * n2) | Divide when n2 == 0 => - InvalidOperation( - BinIntOp(op, IntLit(n1), IntLit(n2)), + DynamicErrorHole( + BinOp(Int(op), d1', d2') |> rewrap, DivideByZero, ) - | Divide => IntLit(n1 / n2) - | LessThan => BoolLit(n1 < n2) - | LessThanOrEqual => BoolLit(n1 <= n2) - | GreaterThan => BoolLit(n1 > n2) - | GreaterThanOrEqual => BoolLit(n1 >= n2) - | Equals => BoolLit(n1 == n2) - | NotEquals => BoolLit(n1 != n2) + | Divide => Int(n1 / n2) + | LessThan => Bool(n1 < n2) + | LessThanOrEqual => Bool(n1 <= n2) + | GreaterThan => Bool(n1 > n2) + | GreaterThanOrEqual => Bool(n1 >= n2) + | Equals => Bool(n1 == n2) + | NotEquals => Bool(n1 != n2) } - | (IntLit(_), _) => - raise(EvaluatorError.Exception(InvalidBoxedIntLit(d2'))) - | _ => raise(EvaluatorError.Exception(InvalidBoxedIntLit(d1'))) - }, + ) + |> fresh, + state_update, kind: BinIntOp(op), // False so that InvalidOperations are caught and made indet by the next step - value: false, + is_value: false, }); - | BinFloatOp(op, d1, d2) => - let. _ = otherwise(env, (d1, d2) => BinFloatOp(op, d1, d2)) + | BinOp(Float(op), d1, d2) => + let. _ = + otherwise(env, (d1, d2) => BinOp(Float(op), d1, d2) |> rewrap) and. d1' = - req_value(req(state, env), d1 => BinFloatOp1(op, d1, d2), d1) + req_value( + req(state, env), + d1 => BinOp1(Float(op), d1, d2) |> wrap_ctx, + d1, + ) and. d2' = - req_value(req(state, env), d2 => BinFloatOp2(op, d1, d2), d2); + req_value( + req(state, env), + d2 => BinOp2(Float(op), d1, d2) |> wrap_ctx, + d2, + ); + let-unbox n1 = (Float, d1'); + let-unbox n2 = (Float, d2'); Step({ - apply: () => - switch (d1', d2') { - | (FloatLit(n1), FloatLit(n2)) => + expr: + ( switch (op) { - | Plus => FloatLit(n1 +. n2) - | Minus => FloatLit(n1 -. n2) - | Power => FloatLit(n1 ** n2) - | Times => FloatLit(n1 *. n2) - | Divide => FloatLit(n1 /. n2) - | LessThan => BoolLit(n1 < n2) - | LessThanOrEqual => BoolLit(n1 <= n2) - | GreaterThan => BoolLit(n1 > n2) - | GreaterThanOrEqual => BoolLit(n1 >= n2) - | Equals => BoolLit(n1 == n2) - | NotEquals => BoolLit(n1 != n2) + | Plus => Float(n1 +. n2) + | Minus => Float(n1 -. n2) + | Power => Float(n1 ** n2) + | Times => Float(n1 *. n2) + | Divide => Float(n1 /. n2) + | LessThan => Bool(n1 < n2) + | LessThanOrEqual => Bool(n1 <= n2) + | GreaterThan => Bool(n1 > n2) + | GreaterThanOrEqual => Bool(n1 >= n2) + | Equals => Bool(n1 == n2) + | NotEquals => Bool(n1 != n2) } - | (FloatLit(_), _) => - raise(EvaluatorError.Exception(InvalidBoxedFloatLit(d2'))) - | _ => raise(EvaluatorError.Exception(InvalidBoxedFloatLit(d1'))) - }, + ) + |> fresh, + state_update, kind: BinFloatOp(op), - value: true, + is_value: true, }); - | BinStringOp(op, d1, d2) => - let. _ = otherwise(env, (d1, d2) => BinStringOp(op, d1, d2)) + | BinOp(String(op), d1, d2) => + let. _ = + otherwise(env, (d1, d2) => BinOp(String(op), d1, d2) |> rewrap) and. d1' = - req_value(req(state, env), d1 => BinStringOp1(op, d1, d2), d1) + req_value( + req(state, env), + d1 => BinOp1(String(op), d1, d2) |> wrap_ctx, + d1, + ) and. d2' = - req_value(req(state, env), d2 => BinStringOp2(op, d1, d2), d2); + req_value( + req(state, env), + d2 => BinOp2(String(op), d1, d2) |> wrap_ctx, + d2, + ); + let-unbox s1 = (String, d1'); + let-unbox s2 = (String, d2'); Step({ - apply: () => - switch (d1', d2') { - | (StringLit(s1), StringLit(s2)) => - switch (op) { - | Concat => StringLit(s1 ++ s2) - | Equals => BoolLit(s1 == s2) - } - | (StringLit(_), _) => - raise(EvaluatorError.Exception(InvalidBoxedStringLit(d2'))) - | _ => raise(EvaluatorError.Exception(InvalidBoxedStringLit(d1'))) + expr: + switch (op) { + | Concat => String(s1 ++ s2) |> fresh + | Equals => Bool(s1 == s2) |> fresh }, + state_update, kind: BinStringOp(op), - value: true, + is_value: true, }); | Tuple(ds) => - let. _ = otherwise(env, ds => Tuple(ds)) + let. _ = otherwise(env, ds => Tuple(ds) |> rewrap) and. _ = - req_all_final(req(state, env), (d1, ds) => Tuple(d1, ds), ds); + req_all_final( + req(state, env), + (d1, ds) => Tuple(d1, ds) |> wrap_ctx, + ds, + ); Constructor; - | Prj(d1, n) => - let. _ = otherwise(env, d1 => Prj(d1, n)) - and. d1' = req_final(req(state, env), d1 => Prj(d1, n), d1); + | Cons(d1, d2) => + let. _ = otherwise(env, (d1, d2) => Cons(d1, d2) |> rewrap) + and. d1' = + req_final(req(state, env), d1 => Cons1(d1, d2) |> wrap_ctx, d1) + and. d2' = + req_value(req(state, env), d2 => Cons2(d1, d2) |> wrap_ctx, d2); + let-unbox ds = (List, d2'); Step({ - apply: () => - switch (d1') { - | Tuple(ds) when n < 0 || List.length(ds) <= n => - raise(EvaluatorError.Exception(InvalidProjection(n))) - | Tuple(ds) => List.nth(ds, n) - | Cast(_, Prod(ts), Prod(_)) when n < 0 || List.length(ts) <= n => - raise(EvaluatorError.Exception(InvalidProjection(n))) - | Cast(d2, Prod(ts1), Prod(ts2)) => - Cast(Prj(d2, n), List.nth(ts1, n), List.nth(ts2, n)) - | _ => raise(EvaluatorError.Exception(InvalidProjection(n))) - }, - kind: Projection, - value: false, + expr: ListLit([d1', ...ds]) |> fresh, + state_update, + kind: ListCons, + is_value: true, }); - | Cons(d1, d2) => - let. _ = otherwise(env, (d1, d2) => Cons(d1, d2)) - and. d1' = req_final(req(state, env), d1 => Cons1(d1, d2), d1) - and. d2' = req_final(req(state, env), d2 => Cons2(d1, d2), d2); - switch (unbox_list(d2')) { - | ListLit(u, i, ty, ds) => - Step({ - apply: () => ListLit(u, i, ty, [d1', ...ds]), - kind: ListCons, - value: true, - }) - | _ => Indet - }; | ListConcat(d1, d2) => - let. _ = otherwise(env, (d1, d2) => ListConcat(d1, d2)) - and. d1' = req_final(req(state, env), d1 => ListConcat1(d1, d2), d1) - and. d2' = req_final(req(state, env), d2 => ListConcat2(d1, d2), d2); - switch (unbox_list(d1'), unbox_list(d2')) { - | (ListLit(u1, i1, t1, ds1), ListLit(_, _, _, ds2)) => - Step({ - apply: () => ListLit(u1, i1, t1, ds1 @ ds2), - kind: ListConcat, - value: true, - }) - | _ => Indet - }; - | ListLit(u, i, ty, ds) => - let. _ = otherwise(env, ds => ListLit(u, i, ty, ds)) + let. _ = otherwise(env, (d1, d2) => ListConcat(d1, d2) |> rewrap) + and. d1' = + req_value( + req(state, env), + d1 => ListConcat1(d1, d2) |> wrap_ctx, + d1, + ) + and. d2' = + req_value( + req(state, env), + d2 => ListConcat2(d1, d2) |> wrap_ctx, + d2, + ); + let-unbox ds1 = (List, d1'); + let-unbox ds2 = (List, d2'); + Step({ + expr: ListLit(ds1 @ ds2) |> fresh, + state_update, + kind: ListConcat, + is_value: true, + }); + | ListLit(ds) => + let. _ = otherwise(env, ds => ListLit(ds) |> rewrap) and. _ = req_all_final( req(state, env), - (d1, ds) => ListLit(u, i, ty, d1, ds), + (d1, ds) => ListLit(d1, ds) |> wrap_ctx, ds, ); Constructor; - // TODO(Matt): This will currently re-traverse d1 if it is a large constructor - | ConsistentCase(Case(d1, rules, n)) => - let. _ = otherwise(env, d1 => ConsistentCase(Case(d1, rules, n))) - and. d1' = + | Match(d1, rules) => + let. _ = otherwise(env, d1 => Match(d1, rules) |> rewrap) + and. d1 = req_final( req(state, env), - d1 => ConsistentCase(Case(d1, rules, n)), + d1 => MatchScrut(d1, rules) |> wrap_ctx, d1, ); - switch (List.nth_opt(rules, n)) { + let rec next_rule = ( + fun + | [] => None + | [(dp, d2), ...rules] => + switch (matches(dp, d1)) { + | Matches(env') => Some((env', d2)) + | DoesNotMatch => next_rule(rules) + | IndetMatch => None + } + ); + switch (next_rule(rules)) { + | Some((env', d2)) => + Step({ + expr: Closure(evaluate_extend_env(env', env), d2) |> fresh, + state_update, + kind: CaseApply, + is_value: false, + }) | None => Indet - | Some(Rule(dp, d2)) => - switch (matches(dp, d1')) { - | Matches(env') => - Step({ - apply: () => Closure(evaluate_extend_env(env', env), d2), - kind: CaseApply, - value: false, - }) - | DoesNotMatch => - Step({ - apply: () => ConsistentCase(Case(d1', rules, n + 1)), - kind: CaseNext, - value: false, - }) - | IndetMatch => Indet - } }; - | InconsistentBranches(_) as d => + | Closure(env', d) => + let. _ = otherwise(env, d => Closure(env', d) |> rewrap) + and. d' = + req_final(req(state, env'), d1 => Closure(env', d1) |> wrap_ctx, d); + Step({expr: d', state_update, kind: CompleteClosure, is_value: true}); + | MultiHole(_) => let. _ = otherwise(env, d); + // and. _ = + // req_all_final( + // req(state, env), + // (d1, ds) => MultiHole(d1, ds) |> wrap_ctx, + // ds, + // ); Indet; - | Closure(env', d) => - let. _ = otherwise(env, d => Closure(env', d)) - and. d' = req_final(req(state, env'), d1 => Closure(env', d1), d); - Step({apply: () => d', kind: CompleteClosure, value: true}); - | NonEmptyHole(reason, u, i, d1) => - let. _ = otherwise(env, d1 => NonEmptyHole(reason, u, i, d1)) + | EmptyHole + | Invalid(_) + | DynamicErrorHole(_) => + let. _ = otherwise(env, d); + Indet; + | Cast(d, t1, t2) => + let. _ = otherwise(env, d => Cast(d, t1, t2) |> rewrap) + and. d' = + req_final(req(state, env), d => Cast(d, t1, t2) |> wrap_ctx, d); + switch (Casts.transition(Cast(d', t1, t2) |> rewrap)) { + | Some(d) => Step({expr: d, state_update, kind: Cast, is_value: false}) + | None => Constructor + }; + | FailedCast(d1, t1, t2) => + let. _ = otherwise(env, d1 => FailedCast(d1, t1, t2) |> rewrap) and. _ = req_final( req(state, env), - d1 => NonEmptyHole(reason, u, i, d1), + d1 => FailedCast(d1, t1, t2) |> wrap_ctx, d1, ); Indet; - | EmptyHole(_) - | FreeVar(_) - | InvalidText(_) - | InvalidOperation(_) => + | Undefined => let. _ = otherwise(env, d); Indet; - | Cast(d, t1, t2) => - open CastHelpers; /* Cast calculus */ - - let. _ = otherwise(env, d => Cast(d, t1, t2)) - and. d' = req_final(req(state, env), d => Cast(d, t1, t2), d); - switch (ground_cases_of(t1), ground_cases_of(t2)) { - | (Hole, Hole) - | (Ground, Ground) => - /* if two types are ground and consistent, then they are eq */ - Step({apply: () => d', kind: Cast, value: true}) - | (Ground, Hole) => - /* can't remove the cast or do anything else here, so we're done */ - Constructor - | (Hole, Ground) => - switch (d') { - | Cast(d2, t3, Unknown(_)) => - /* by canonical forms, d1' must be of the form d ?> */ - if (Typ.eq(t3, t2)) { - Step({apply: () => d2, kind: Cast, value: true}); - } else { - Step({ - apply: () => FailedCast(d', t1, t2), - kind: Cast, - value: false, - }); - } - | _ => Indet - } - | (Hole, NotGroundOrHole(t2_grounded)) => - /* ITExpand rule */ - Step({ - apply: () => - DHExp.Cast(Cast(d', t1, t2_grounded), t2_grounded, t2), - kind: Cast, - value: false, - }) - | (NotGroundOrHole(t1_grounded), Hole) => - /* ITGround rule */ - Step({ - apply: () => - DHExp.Cast(Cast(d', t1, t1_grounded), t1_grounded, t2), - kind: Cast, - value: false, - }) - | (Ground, NotGroundOrHole(_)) - | (NotGroundOrHole(_), Ground) => - /* can't do anything when casting between diseq, non-hole types */ - Constructor - | (NotGroundOrHole(_), NotGroundOrHole(_)) => - /* they might be eq in this case, so remove cast if so */ - if (Typ.eq(t1, t2)) { - Step({apply: () => d', kind: Cast, value: true}); - } else { - Constructor; - } - }; - | FailedCast(d1, t1, t2) => - let. _ = otherwise(env, d1 => FailedCast(d1, t1, t2)) - and. _ = req_final(req(state, env), d1 => FailedCast(d1, t1, t2), d1); - Indet; - | Filter(Filter({pat: Closure(_), _}) as f1, d1) - | Filter(Residue(_) as f1, d1) => - let. _ = otherwise(env, d1 => Filter(f1, d1)) - and. d1 = req_final(req(state, env), d1 => Filter(f1, d1), d1); - Step({apply: () => d1, kind: CompleteFilter, value: true}); - | Filter(Filter({pat, act}) as f1, d1) => - let. _ = otherwise(env, Filter(f1, d1)); - Step({ - apply: () => Filter(Filter({pat: Closure(env, pat), act}), d1), - kind: CompleteFilter, - value: false, - }); + | Parens(d) => + let. _ = otherwise(env, d); + Step({expr: d, state_update, kind: RemoveParens, is_value: false}); + | TyAlias(_, _, d) => + let. _ = otherwise(env, d); + Step({expr: d, state_update, kind: RemoveTypeAlias, is_value: false}); + | Filter(f1, d1) => + let. _ = otherwise(env, d1 => Filter(f1, d1) |> rewrap) + and. d1 = + req_final(req(state, env), d1 => Filter(f1, d1) |> wrap_ctx, d1); + Step({expr: d1, state_update, kind: CompleteFilter, is_value: true}); }; + }; }; let should_hide_step_kind = (~settings: CoreSettings.Evaluation.t) => @@ -824,21 +856,23 @@ let should_hide_step_kind = (~settings: CoreSettings.Evaluation.t) => | LetBind | ModuleBind | DotAccess - | Sequence + | Seq | UpdateTest | TypFunAp | FunAp + | DeferredAp | BuiltinAp(_) | BinBoolOp(_) | BinIntOp(_) | BinFloatOp(_) | BinStringOp(_) + | UnOp(_) | ListCons | ListConcat | CaseApply | Projection // TODO(Matt): We don't want to show projection to the user - | Skip | Conditional(_) + | RemoveTypeAlias | InvalidStep => false | ModuleLookup | VarLookup => !settings.show_lookup_steps @@ -846,9 +880,9 @@ let should_hide_step_kind = (~settings: CoreSettings.Evaluation.t) => | CastAp | Cast => !settings.show_casts | FixUnwrap => !settings.show_fixpoints - | CaseNext | CompleteClosure | CompleteFilter | BuiltinWrap | FunClosure - | FixClosure => true; + | FixClosure + | RemoveParens => true; diff --git a/src/haz3lcore/dynamics/TypeAssignment.re b/src/haz3lcore/dynamics/TypeAssignment.re new file mode 100644 index 0000000000..f4979d94bf --- /dev/null +++ b/src/haz3lcore/dynamics/TypeAssignment.re @@ -0,0 +1,358 @@ +open Util; +open OptUtil.Syntax; + +// let equal_typ_list = (l: list(Typ.t)): option(Typ.t) => { +// switch (l) { +// | [] => None +// | [ty, ..._] => +// List.fold_left((acc, t) => {acc && Typ.eq(t, ty)}, true, l) +// ? Some(ty) : None +// }; +// }; + +// let delta_ty = (id: MetaVar.t, m: Statics.Map.t): option(Typ.t) => { +// switch (Id.Map.find_opt(id, m)) { +// | Some(InfoExp({mode, ctx, _})) => +// switch (mode) { +// | Syn +// | SynTypFun +// | SynFun => Some(Unknown(Internal)) +// | Ana(ana_ty) => Some(Typ.normalize(ctx, ana_ty)) +// } +// | _ => None +// }; +// }; + +let ground = (ty: Typ.t): bool => { + switch (Casts.ground_cases_of(ty)) { + | Casts.Ground => true + | _ => false + }; +}; + +let dhpat_extend_ctx = (dhpat: DHPat.t, ty: Typ.t, ctx: Ctx.t): option(Ctx.t) => { + let rec dhpat_var_entry = + (dhpat: DHPat.t, ty: Typ.t): option(list(Ctx.entry)) => { + switch (dhpat |> Pat.term_of) { + | Var(name) => + let entry = Ctx.VarEntry({name, id: Id.invalid, typ: ty}); + Some([entry]); + | Tuple(l1) => + let* ts = Typ.matched_prod_strict(ctx, List.length(l1), ty); + let* l = + List.map2((dhp, typ) => {dhpat_var_entry(dhp, typ)}, l1, ts) + |> OptUtil.sequence; + Some(List.concat(l)); + | Cons(dhp1, dhp2) => + let* t = Typ.matched_list_strict(ctx, ty); + let* l1 = dhpat_var_entry(dhp1, t); + let* l2 = dhpat_var_entry(dhp2, List(t) |> Typ.temp); + Some(l1 @ l2); + | ListLit(l) => + let* t = Typ.matched_list_strict(ctx, ty); + let* l = + List.map(dhp => {dhpat_var_entry(dhp, t)}, l) |> OptUtil.sequence; + Some(List.concat(l)); + | Ap({term: Constructor(name, _), _}, dhp) => + // TODO: make this stricter + let* ctrs = Typ.get_sum_constructors(ctx, ty); + let* typ = ConstructorMap.get_entry(name, ctrs); + let* (ty1, ty2) = Typ.matched_arrow_strict(ctx, typ); + Typ.eq(ty2, ty) ? dhpat_var_entry(dhp, ty1) : None; + | Ap(_) => None + | EmptyHole + | Wild + | Invalid(_) + | MultiHole(_) => Some([]) + | Parens(dhp) => dhpat_var_entry(dhp, ty) + | Int(_) => Typ.eq(ty, Int |> Typ.temp) ? Some([]) : None + | Float(_) => Typ.eq(ty, Float |> Typ.temp) ? Some([]) : None + | Bool(_) => Typ.eq(ty, Bool |> Typ.temp) ? Some([]) : None + | String(_) => Typ.eq(ty, String |> Typ.temp) ? Some([]) : None + | Constructor(_) => Some([]) // TODO: make this stricter + | Cast(dhp, ty1, ty2) => + Typ.eq(ty, ty2) ? dhpat_var_entry(dhp, ty1) : None + }; + }; + let+ l = dhpat_var_entry(dhpat, ty); + List.fold_left((ctx, entry) => Ctx.extend(ctx, entry), ctx, l); +}; + +/* patterns in functions and fixpoints must have a synthesizable type */ +let rec dhpat_synthesize = (dhpat: DHPat.t, ctx: Ctx.t): option(Typ.t) => { + switch (dhpat |> Pat.term_of) { + | Var(_) + | Constructor(_) + | Ap(_) => None + | Tuple(dhs) => + let* l = List.map(dhpat_synthesize(_, ctx), dhs) |> OptUtil.sequence; + Some(Prod(l) |> Typ.temp); + | Cons(dhp1, _) => + let* t = dhpat_synthesize(dhp1, ctx); + Some(List(t) |> Typ.temp); + | ListLit([]) => Some(List(Unknown(Internal) |> Typ.temp) |> Typ.temp) + | ListLit([x, ..._]) => + let* t_x = dhpat_synthesize(x, ctx); + Some(List(t_x) |> Typ.temp); + | EmptyHole => Some(Unknown(Internal) |> Typ.temp) + | Wild => Some(Unknown(Internal) |> Typ.temp) + | Invalid(_) + | MultiHole(_) => Some(Unknown(Internal) |> Typ.temp) + | Parens(dhp) => dhpat_synthesize(dhp, ctx) + | Int(_) => Some(Int |> Typ.temp) + | Float(_) => Some(Float |> Typ.temp) + | Bool(_) => Some(Bool |> Typ.temp) + | String(_) => Some(String |> Typ.temp) + | Cast(_, _, ty) => Some(ty) + }; +}; + +let rec env_extend_ctx = + (env: ClosureEnvironment.t, m: Statics.Map.t, ctx: Ctx.t) + : option(Ctx.t) => { + let+ l = + env + |> ClosureEnvironment.to_list + |> List.map(((name, de)) => { + let+ ty = typ_of_dhexp(ctx, m, de); + Ctx.VarEntry({name, id: Id.invalid, typ: ty}); + }) + |> OptUtil.sequence; + List.fold_left((ctx, var_entry) => Ctx.extend(ctx, var_entry), ctx, l); +} + +and typ_of_dhexp = (ctx: Ctx.t, m: Statics.Map.t, dh: DHExp.t): option(Typ.t) => { + switch (dh |> DHExp.term_of) { + | Invalid(_) + | MultiHole(_) + | EmptyHole + | Deferral(_) + | Undefined => Some(Unknown(Internal) |> Typ.temp) + | DynamicErrorHole(e, _) => typ_of_dhexp(ctx, m, e) + | Closure(env, d) => + let* ctx' = env_extend_ctx(env, m, ctx); + typ_of_dhexp(ctx', m, d); + | Filter(_, d) => typ_of_dhexp(ctx, m, d) + | Var(name) => + let* var = Ctx.lookup_var(ctx, name); + Some(var.typ); + | Seq(d1, d2) => + let* _ = typ_of_dhexp(ctx, m, d1); + typ_of_dhexp(ctx, m, d2); + | Let(dhp, de, db) => + let* ty1 = typ_of_dhexp(ctx, m, de); + let* ctx = dhpat_extend_ctx(dhp, ty1, ctx); + typ_of_dhexp(ctx, m, db); + | FixF(dhp, d, env) => + let* ty_p = dhpat_synthesize(dhp, ctx); + let* ctx = + switch (env) { + | None => Some(ctx) + | Some(env) => env_extend_ctx(env, m, ctx) + }; + let* ctx = dhpat_extend_ctx(dhp, ty_p, ctx); + typ_of_dhexp(ctx, m, d); + | Fun(dhp, d, env, _) => + let* ty_p = dhpat_synthesize(dhp, ctx); + let* ctx = + switch (env) { + | None => Some(ctx) + | Some(env) => env_extend_ctx(env, m, ctx) + }; + let* ctx = dhpat_extend_ctx(dhp, ty_p, ctx); + let* ty2 = typ_of_dhexp(ctx, m, d); + Some(Typ.Arrow(ty_p, ty2) |> Typ.temp); + | TypFun({term: Var(name), _} as utpat, d, _) + when !Ctx.shadows_typ(ctx, name) => + let ctx = + Ctx.extend_tvar(ctx, {name, id: TPat.rep_id(utpat), kind: Abstract}); + let* ty = typ_of_dhexp(ctx, m, d); + Some(Typ.Forall(utpat, ty) |> Typ.temp); + | TypFun(_, d, _) => + let* ty = typ_of_dhexp(ctx, m, d); + Some(Typ.Forall(Var("?") |> TPat.fresh, ty) |> Typ.temp); + | TypAp(d, ty1) => + let* ty = typ_of_dhexp(ctx, m, d); + let* (name, ty2) = Typ.matched_forall_strict(ctx, ty); + switch (name) { + | Some(name) => Some(Typ.subst(ty1, name, ty2)) + | None => Some(ty2) + }; + | Ap(_, d1, d2) => + let* ty1 = typ_of_dhexp(ctx, m, d1); + let* ty2 = typ_of_dhexp(ctx, m, d2); + let* (tyl, tyr) = Typ.matched_arrow_strict(ctx, ty1); + Typ.eq(tyl, ty2) ? Some(tyr) : None; + | DeferredAp(d1, d2s) => + let* ty1 = typ_of_dhexp(ctx, m, d1); + let* tys = List.map(typ_of_dhexp(ctx, m), d2s) |> OptUtil.sequence; + let* (tyl, tyr) = Typ.matched_arrow_strict(ctx, ty1); + // TODO: make strict + let tyls = Typ.matched_args(ctx, List.length(tys), tyl); + let* combined = ListUtil.combine_opt(tyls, d2s); + let without_deferrals = + List.filter(((_, d)) => !DHExp.is_deferral(d), combined); + if (List.for_all( + ((t, d)) => { + let ty = typ_of_dhexp(ctx, m, d); + switch (ty) { + | Some(ty) => Typ.eq(t, ty) + | None => false + }; + }, + without_deferrals, + )) { + let with_deferrals = + List.filter(((_, d)) => DHExp.is_deferral(d), combined); + let* tys = + List.map(((_, d)) => typ_of_dhexp(ctx, m, d), with_deferrals) + |> OptUtil.sequence; + switch (tys) { + | [] => Some(tyr) + | [ty] => Some(Typ.Arrow(ty, tyr) |> Typ.temp) + | tys => Some(Typ.Arrow(Prod(tys) |> Typ.temp, tyr) |> Typ.temp) + }; + } else { + None; + }; + + | BuiltinFun(name) => + let* var = Ctx.lookup_var(ctx, name); + Some(var.typ); + | Test(dtest) => + let* ty = typ_of_dhexp(ctx, m, dtest); + Typ.eq(ty, Bool |> Typ.temp) ? Some(Typ.Prod([]) |> Typ.temp) : None; + | Bool(_) => Some(Bool |> Typ.temp) + | Int(_) => Some(Int |> Typ.temp) + | Float(_) => Some(Float |> Typ.temp) + | String(_) => Some(String |> Typ.temp) + | BinOp(Bool(_), d1, d2) => + let* ty1 = typ_of_dhexp(ctx, m, d1); + let* ty2 = typ_of_dhexp(ctx, m, d2); + Typ.eq(ty1, Bool |> Typ.temp) && Typ.eq(ty2, Bool |> Typ.temp) + ? Some(Bool |> Typ.temp) : None; + | BinOp(Int(op), d1, d2) => + let* ty1 = typ_of_dhexp(ctx, m, d1); + let* ty2 = typ_of_dhexp(ctx, m, d2); + if (Typ.eq(ty1, Int |> Typ.temp) && Typ.eq(ty2, Int |> Typ.temp)) { + switch (op) { + | Minus + | Plus + | Times + | Power + | Divide => Some(Int |> Typ.temp) + | LessThan + | LessThanOrEqual + | GreaterThan + | GreaterThanOrEqual + | Equals + | NotEquals => Some(Bool |> Typ.temp) + }; + } else { + None; + }; + | BinOp(Float(op), d1, d2) => + let* ty1 = typ_of_dhexp(ctx, m, d1); + let* ty2 = typ_of_dhexp(ctx, m, d2); + if (Typ.eq(ty1, Float |> Typ.temp) && Typ.eq(ty2, Float |> Typ.temp)) { + switch (op) { + | Minus + | Plus + | Times + | Power + | Divide => Some(Float |> Typ.temp) + | LessThan + | LessThanOrEqual + | GreaterThan + | GreaterThanOrEqual + | Equals + | NotEquals => Some(Bool |> Typ.temp) + }; + } else { + None; + }; + | BinOp(String(op), d1, d2) => + let* ty1 = typ_of_dhexp(ctx, m, d1); + let* ty2 = typ_of_dhexp(ctx, m, d2); + if (Typ.eq(ty1, String |> Typ.temp) && Typ.eq(ty2, String |> Typ.temp)) { + switch (op) { + | Concat => Some(String |> Typ.temp) + | Equals => Some(Bool |> Typ.temp) + }; + } else { + None; + }; + | UnOp(Int(Minus), d) => + let* ty = typ_of_dhexp(ctx, m, d); + Typ.eq(ty, Int |> Typ.temp) ? Some(Int |> Typ.temp) : None; + | UnOp(Bool(Not), d) => + let* ty = typ_of_dhexp(ctx, m, d); + Typ.eq(ty, Bool |> Typ.temp) ? Some(Bool |> Typ.temp) : None; + | UnOp(Meta(Unquote), d) => + let* ty = typ_of_dhexp(ctx, m, d); + Some(ty); + | ListLit([]) => Some(List(Unknown(Internal) |> Typ.temp) |> Typ.temp) + | ListLit([x, ...xs]) => + let* t_x = typ_of_dhexp(ctx, m, x); + let* t_xs = List.map(typ_of_dhexp(ctx, m), xs) |> OptUtil.sequence; + List.for_all(t => Typ.eq(t, t_x), t_xs) + ? Some(List(t_x) |> Typ.temp) : None; + | Cons(d1, d2) => + let* ty1 = typ_of_dhexp(ctx, m, d1); + let* ty2 = typ_of_dhexp(ctx, m, d2); + let* ty3 = Typ.matched_list_strict(ctx, ty2); + Typ.eq(ty1, ty3) ? Some(ty2) : None; + | ListConcat(d1, d2) => + let* ty1 = typ_of_dhexp(ctx, m, d1); + let* ty1l = Typ.matched_list_strict(ctx, ty1); + let* ty2 = typ_of_dhexp(ctx, m, d2); + let* ty2l = Typ.matched_list_strict(ctx, ty2); + Typ.eq(ty1l, ty2l) ? Some(ty1) : None; + | Tuple(dhs) => + let+ typ_list = + dhs |> List.map(typ_of_dhexp(ctx, m)) |> OptUtil.sequence; + Prod(typ_list) |> Typ.temp; + | Constructor(_) => None // Constructors should always be surrounded by casts + | Match(_, []) => Some(Unknown(Internal) |> Typ.temp) + | Match(d_scrut, [rule, ...rules]) => + let* ty' = typ_of_dhexp(ctx, m, d_scrut); + let rule_to_ty = ((dhpat, dhexp): (Pat.t, Exp.t)) => { + let* ctx = dhpat_extend_ctx(dhpat, ty', ctx); + typ_of_dhexp(ctx, m, dhexp); + }; + let* rule_ty = rule_to_ty(rule); + let* rules_ty = List.map(rule_to_ty, rules) |> OptUtil.sequence; + List.for_all(Typ.eq(rule_ty, _), rules_ty) ? Some(rule_ty) : None; + | Cast(d, ty1, ty2) => + let* _ = Typ.join(~fix=true, ctx, ty1, ty2); + let* tyd = typ_of_dhexp(ctx, m, d); + Typ.eq(tyd, ty1) ? Some(ty2) : None; + | FailedCast(d, ty1, ty2) => + if (ground(ty1) && ground(ty2) && !Typ.eq(ty1, ty2)) { + let* tyd = typ_of_dhexp(ctx, m, d); + Typ.eq(tyd, ty1) ? Some(ty2) : None; + } else { + None; + } + | If(d_scrut, d1, d2) => + let* ty = typ_of_dhexp(ctx, m, d_scrut); + if (Typ.eq(ty, Bool |> Typ.temp)) { + let* ty1 = typ_of_dhexp(ctx, m, d1); + let* ty2 = typ_of_dhexp(ctx, m, d2); + Typ.eq(ty1, ty2) ? Some(ty1) : None; + } else { + None; + }; + | TyAlias(_, _, d) => typ_of_dhexp(ctx, m, d) + | Parens(d) => typ_of_dhexp(ctx, m, d) + }; +}; + +let property_test = (uexp_typ: Typ.t, dhexp: DHExp.t, m: Statics.Map.t): bool => { + let dhexp_typ = typ_of_dhexp(Builtins.ctx_init, m, dhexp); + + switch (dhexp_typ) { + | None => false + | Some(dh_typ) => Typ.eq(dh_typ, uexp_typ) + }; +}; diff --git a/src/haz3lcore/dynamics/Unboxing.re b/src/haz3lcore/dynamics/Unboxing.re new file mode 100644 index 0000000000..400620026c --- /dev/null +++ b/src/haz3lcore/dynamics/Unboxing.re @@ -0,0 +1,198 @@ +open Util; + +/* What is unboxing? + + When you have an expression of type list, and it's finished evaluating, + is it a list? Sadly not necessarily, it might be: + + - indeterminate, e.g. it has a hole in it + - a list with some casts wrapped around it + + Unboxing is the process of turning a list into a list if it is a list, + by pushing casts inside data structures, or giving up if it is not a list. + + Note unboxing only works one layer deep, if we have a list of lists then + the inner lists may still have casts around them after unboxing. + */ + +type unbox_request('a) = + | Int: unbox_request(int) + | Float: unbox_request(float) + | Bool: unbox_request(bool) + | String: unbox_request(string) + | Tuple(int): unbox_request(list(DHExp.t)) + | List: unbox_request(list(DHExp.t)) + | Cons: unbox_request((DHExp.t, DHExp.t)) + | SumNoArg(string): unbox_request(unit) + | SumWithArg(string): unbox_request(DHExp.t); + +type unboxed('a) = + | DoesNotMatch + | IndetMatch + | Matches('a); + +let ( let* ) = (x: unboxed('a), f: 'a => unboxed('b)): unboxed('b) => + switch (x) { + | IndetMatch => IndetMatch + | DoesNotMatch => DoesNotMatch + | Matches(x) => f(x) + }; + +let fixup_cast = Casts.transition_multiple; + +/* This function has a different return type depending on what kind of request + it is given. This unfortunately uses a crazy OCaml feature called GADTS, but + it avoids having to write a separate unbox function for each kind of request. + */ + +let rec unbox: type a. (unbox_request(a), DHExp.t) => unboxed(a) = + (request, expr) => { + switch (request, DHExp.term_of(expr)) { + /* Remove parentheses from casts */ + | (_, Cast(d, {term: Parens(x), _}, y)) + | (_, Cast(d, x, {term: Parens(y), _})) => + unbox(request, Cast(d, x, y) |> DHExp.fresh) + + /* Base types are always already unboxed because of the ITCastID rule*/ + | (Bool, Bool(b)) => Matches(b) + | (Int, Int(i)) => Matches(i) + | (Float, Float(f)) => Matches(f) + | (String, String(s)) => Matches(s) + + /* Lists can be either lists or list casts */ + | (List, ListLit(l)) => Matches(l) + | (Cons, ListLit([x, ...xs])) => + Matches((x, ListLit(xs) |> DHExp.fresh)) + | (Cons, ListLit([])) => DoesNotMatch + | (List, Cast(l, {term: List(t1), _}, {term: List(t2), _})) => + let* l = unbox(List, l); + let l = List.map(d => Cast(d, t1, t2) |> DHExp.fresh, l); + let l = List.map(fixup_cast, l); + Matches(l); + | ( + Cons, + Cast(l, {term: List(t1), _} as ct1, {term: List(t2), _} as ct2), + ) => + let* l = unbox(List, l); + switch (l) { + | [] => DoesNotMatch + | [x, ...xs] => + Matches(( + Cast(x, t1, t2) |> DHExp.fresh |> fixup_cast, + Cast(ListLit(xs) |> DHExp.fresh, ct1, ct2) |> DHExp.fresh, + )) + }; + + /* Tuples can be either tuples or tuple casts */ + | (Tuple(n), Tuple(t)) when List.length(t) == n => Matches(t) + | (Tuple(_), Tuple(_)) => DoesNotMatch + | (Tuple(n), Cast(t, {term: Prod(t1s), _}, {term: Prod(t2s), _})) + when n == List.length(t1s) && n == List.length(t2s) => + let* t = unbox(Tuple(n), t); + let t = + ListUtil.map3( + (d, t1, t2) => Cast(d, t1, t2) |> DHExp.fresh, + t, + t1s, + t2s, + ); + let t = List.map(fixup_cast, t); + Matches(t); + + /* Sum constructors can be either sum constructors, sum constructors + applied to some value or sum casts */ + | (SumNoArg(name1), Constructor(name2, _)) when name1 == name2 => + Matches() + | (SumNoArg(_), Constructor(_)) => DoesNotMatch + | (SumNoArg(_), Ap(_, {term: Constructor(_), _}, _)) => DoesNotMatch + | (SumNoArg(name), Cast(d1, {term: Sum(_), _}, {term: Sum(s2), _})) + when + ConstructorMap.has_constructor_no_args(name, s2) + || ConstructorMap.has_bad_entry(s2) => + let* d1 = unbox(SumNoArg(name), d1); + Matches(d1); + | (SumNoArg(_), Cast(_, {term: Sum(_), _}, {term: Sum(_), _})) => + IndetMatch + + | (SumWithArg(_), Constructor(_)) => DoesNotMatch + | (SumWithArg(name1), Ap(_, {term: Constructor(name2, _), _}, d3)) + when name1 == name2 => + Matches(d3) + | (SumWithArg(_), Ap(_, {term: Constructor(_), _}, _)) => DoesNotMatch + | (SumWithArg(name), Cast(d1, {term: Sum(s1), _}, {term: Sum(s2), _})) => + let get_entry_or_bad = s => + switch (ConstructorMap.get_entry(name, s)) { + | Some(x) => Some(x) + | None when ConstructorMap.has_bad_entry(s) => + Some(Typ.temp(Unknown(Internal))) + | None => None + }; + switch (get_entry_or_bad(s1), get_entry_or_bad(s2)) { + | (Some(x), Some(y)) => + let* d1 = unbox(SumWithArg(name), d1); + Matches(Cast(d1, x, y) |> Exp.fresh |> fixup_cast); + | _ => IndetMatch + }; + // There should be some sort of failure here when the cast doesn't go through. + + /* Any cast from unknown is indet */ + | (_, Cast(_, {term: Unknown(_), _}, _)) => IndetMatch + + /* Any failed cast is indet */ + | (_, FailedCast(_)) => IndetMatch + + /* Forms that are the wrong type of value - these cases indicate an error + in elaboration or in the cast calculus. */ + | ( + _, + Bool(_) | Int(_) | Float(_) | String(_) | Constructor(_) | + BuiltinFun(_) | + Deferral(_) | + DeferredAp(_) | + Fun(_, _, _, Some(_)) | + ListLit(_) | + Tuple(_) | + Cast(_) | + Ap(_, {term: Constructor(_), _}, _) | + TypFun(_) | + TypAp(_), + ) => + switch (request) { + | Bool => raise(EvaluatorError.Exception(InvalidBoxedBoolLit(expr))) + | Int => raise(EvaluatorError.Exception(InvalidBoxedIntLit(expr))) + | Float => raise(EvaluatorError.Exception(InvalidBoxedFloatLit(expr))) + | String => + raise(EvaluatorError.Exception(InvalidBoxedStringLit(expr))) + | Tuple(_) => raise(EvaluatorError.Exception(InvalidBoxedTuple(expr))) + | List + | Cons => raise(EvaluatorError.Exception(InvalidBoxedListLit(expr))) + | SumNoArg(_) + | SumWithArg(_) => + raise(EvaluatorError.Exception(InvalidBoxedSumConstructor(expr))) + } + + /* Forms that are not yet or will never be a value */ + | ( + _, + Invalid(_) | Undefined | EmptyHole | MultiHole(_) | DynamicErrorHole(_) | + Var(_) | + Let(_) | + Fun(_, _, _, None) | + FixF(_) | + TyAlias(_) | + Ap(_) | + If(_) | + Seq(_) | + Test(_) | + Filter(_) | + Closure(_) | + Parens(_) | + Cons(_) | + ListConcat(_) | + UnOp(_) | + BinOp(_) | + Match(_), + ) => + IndetMatch + }; + }; diff --git a/src/haz3lcore/dynamics/ValueChecker.re b/src/haz3lcore/dynamics/ValueChecker.re index 4bc7fea3d4..39f43daeed 100644 --- a/src/haz3lcore/dynamics/ValueChecker.re +++ b/src/haz3lcore/dynamics/ValueChecker.re @@ -1,6 +1,5 @@ open DHExp; open Transition; -open Util; type t = | Value @@ -56,6 +55,13 @@ module ValueCheckerEVMode: { ([], (Value, true)), ); + let req_final_or_value = (vc, _, d) => + switch (vc(d)) { + | Value => ((d, true), (Value, true)) + | Indet => ((d, false), (Value, true)) + | Expr => ((d, false), (Value, false)) + }; + let otherwise = (_, _) => ((), (Value, true)); let (let.) = ((v, (r, b)), rule) => @@ -71,27 +77,20 @@ module ValueCheckerEVMode: { ((v1, v2), combine(r1, r2)); }; - let update_test = ((), _, _) => (); + let update_test = (_, _, _) => (); }; module CV = Transition(ValueCheckerEVMode); -let rec check_value = ((), env, d) => CV.transition(check_value, (), env, d); +let rec check_value = (state, env, d) => + CV.transition(check_value, state, env, d); -let check_value = check_value(); - -let rec check_value_mod_ctx = ((), env) => - fun - | BoundVar(x) => - check_value_mod_ctx( - (), - env, - ClosureEnvironment.lookup(env, x) - |> OptUtil.get(() => { - print_endline("FreeInvalidVar:" ++ x); - raise(EvaluatorError.Exception(FreeInvalidVar(x))); - }), - ) - | d => CV.transition(check_value_mod_ctx, (), env, d); - -let check_value_mod_ctx = check_value_mod_ctx(); +let rec check_value_mod_ctx = ((), env, d) => + switch (DHExp.term_of(d)) { + | Var(x) => + switch (ClosureEnvironment.lookup(env, x)) { + | Some(v) => check_value_mod_ctx((), env, v) + | None => CV.transition(check_value_mod_ctx, (), env, d) + } + | _ => CV.transition(check_value_mod_ctx, (), env, d) + }; diff --git a/src/haz3lcore/dynamics/VarBstMap.re b/src/haz3lcore/dynamics/VarBstMap.re index ce126177bc..2952690388 100644 --- a/src/haz3lcore/dynamics/VarBstMap.re +++ b/src/haz3lcore/dynamics/VarBstMap.re @@ -1,4 +1,5 @@ -open Sexplib.Std; +open Util; +open Ppx_yojson_conv_lib.Yojson_conv; module Sexp = Sexplib.Sexp; module Inner = { diff --git a/src/haz3lcore/dynamics/VarErrStatus.re b/src/haz3lcore/dynamics/VarErrStatus.re index 167db32cad..d52f5809a5 100644 --- a/src/haz3lcore/dynamics/VarErrStatus.re +++ b/src/haz3lcore/dynamics/VarErrStatus.re @@ -9,4 +9,4 @@ module HoleReason = { [@deriving (show({with_path: false}), sexp, yojson)] type t = | NotInVarHole - | InVarHole(HoleReason.t, MetaVar.t); + | InVarHole(HoleReason.t, Id.t); diff --git a/src/haz3lcore/lang/Form.re b/src/haz3lcore/lang/Form.re index 8fd317eee6..8ee20c3e0b 100644 --- a/src/haz3lcore/lang/Form.re +++ b/src/haz3lcore/lang/Form.re @@ -1,4 +1,5 @@ -open Sexplib.Std; +open Util; +open StringUtil; open Mold; module P = Precedence; @@ -11,10 +12,6 @@ module P = Precedence; The wrapping functions seen in both of those tables determine the shape, precedence, and expansion behavior of the form. */ -let regexp = (r, s) => - Js_of_ocaml.Regexp.string_match(Js_of_ocaml.Regexp.regexp(r), s, 0) - |> Option.is_some; - /* A label is the textual expression of a form's delimiters */ [@deriving (show({with_path: false}), sexp, yojson)] type label = list(Token.t); @@ -68,23 +65,20 @@ let mk_nul_infix = (t: Token.t, prec) => /* A. Secondary Notation (Comments, Whitespace, etc.) */ let space = " "; -/* HACK(andrew): Using ⏎ char to represent linebreak to avoid regexp - issues with using \n. Someone who understands regexps better - should fix this. */ -let linebreak = "⏎"; -let comment_regexp = "^#[^#⏎]*#$"; /* Multiline comments not supported */ -let is_comment = t => regexp(comment_regexp, t) || t == "#"; +let linebreak = "\n"; +let comment_regexp = regexp("^#[^#\n]*#$"); /* Multiline comments not supported */ +let is_comment = t => match(comment_regexp, t) || t == "#"; let is_comment_delim = t => t == "#"; let is_secondary = t => - List.mem(t, [space, linebreak]) || regexp(comment_regexp, t); + List.mem(t, [space, linebreak]) || match(comment_regexp, t); /* STRINGS: special-case syntax */ /* is_string: last clause is a somewhat hacky way of making sure there are at most two quotes, in order to prevent merges */ +let string_regexp = regexp("^\"[^\n]*\"$"); /* Multiline strings not supported */ let is_string = t => - regexp("^\"[^⏎]*\"$", t) - && List.length(String.split_on_char('"', t)) < 4; + match(string_regexp, t) && List.length(String.split_on_char('"', t)) < 4; let string_delim = "\""; let empty_string = string_delim ++ string_delim; let is_string_delim = (==)(string_delim); @@ -111,9 +105,8 @@ let keywords = [ "else", ]; let reserved_keywords = ["of", "when", "with", "switch", "match"]; -let is_keyword = regexp("^(" ++ String.concat("|", keywords) ++ ")$"); -let is_reserved_keyword = - regexp("^(" ++ String.concat("|", reserved_keywords) ++ ")$"); +let keyword_regexp = regexp("^(" ++ String.concat("|", keywords) ++ ")$"); +let is_keyword = match(keyword_regexp); /* Potential tokens: These are fallthrough classes which determine * the behavior when inserting a character in contact with a token */ @@ -121,57 +114,62 @@ let is_potential_operand = /* gensofubi: "." is used as a operator for module, only recognized as potential operand if not appearing with letters */ x => - regexp("^[a-zA-Z0-9_'?]+$", x) || regexp("^[0-9_'\\.?]+$", x); + match(regexp("^[a-zA-Z0-9_'?]+$"), x) + || match(regexp("^[0-9_'\\.?]+$"), x); /* Anything else is considered a potential operator, as long * as it does not contain any whitespace, linebreaks, comment * delimiters, string delimiters, or the instant expanding paired * delimiters: ()[]|{} */ -let is_potential_operator = - regexp("^[^a-zA-Z0-9_'?\"#⏎\\s\\[\\]\\(\\)\\{\\}]+$"); +let potential_operator_regexp = + regexp("^[^a-zA-Z0-9_'?\"#\n\\s\\[\\]\\(\\)\\{\\}]+$"); /* Multiline operators not supported */ +let is_potential_operator = match(potential_operator_regexp); let is_potential_token = t => is_potential_operand(t) || is_potential_operator(t) || is_string(t) || is_comment(t); -let is_arbitary_int = regexp("^-?\\d+[0-9_]*$"); -let is_arbitary_float = x => - x != "." && x != "-" && regexp("^-?[0-9]*\\.?[0-9]*((e|E)-?[0-9]*)?$", x); -let is_int = str => is_arbitary_int(str) && int_of_string_opt(str) != None; +let int_regexp = regexp("^-?\\d+[0-9_]*$"); +let is_float = match(regexp("^-?[0-9]*\\.?[0-9]*((e|E)-?[0-9]*)?$")); +let is_arbitary_float = x => x != "." && x != "-" && is_float(x); +let is_int = str => match(int_regexp, str) && int_of_string_opt(str) != None; /* NOTE: The is_arbitary_int check is necessary to prevent minuses from being parsed as part of the int token. */ -let is_bad_int = str => is_arbitary_int(str) && !is_int(str); +let is_bad_int = str => match(int_regexp, str) && !is_int(str); /* NOTE: As well as making is_float disjoint from is_int, the is_arbitary_int also prevents ints over int_max from being cast as floats. The is_arbitary_float check is necessary to prevent minuses from being parsed as part of the float token. */ let is_float = str => - !is_arbitary_int(str) + !match(int_regexp, str) && is_arbitary_float(str) && float_of_string_opt(str) != None; let is_bad_float = str => is_arbitary_float(str) && !is_float(str); let bools = ["true", "false"]; -let is_bool = regexp("^(" ++ String.concat("|", bools) ++ ")$"); - +let is_bool = match(regexp("^(" ++ String.concat("|", bools) ++ ")$")); +let undefined = "undefined"; +let is_undefined = match(regexp("^" ++ undefined ++ "$")); + +let var_regexp = + regexp( + {|(^[a-z_][A-Za-z0-9_']*$)|(^[A-Z][A-Za-z0-9_']*\.[a-z][A-Za-z0-9_']*$)|}, + ); let is_var = str => !is_bool(str) + && !is_undefined(str) && str != "_" //&& !is_keyword(str) - //&& !is_reserved(str) - && regexp( - {|(^[a-z_][A-Za-z0-9_']*$)|(^[A-Z][A-Za-z0-9_']*\.[a-z][A-Za-z0-9_']*$)|}, - str, - ); -let is_capitalized_name = regexp("^[A-Z][A-Za-z0-9_]*$"); -let is_tag = is_capitalized_name; -let is_ctr = is_capitalized_name; + && match(var_regexp, str); +let capitalized_name_regexp = regexp("^[A-Z][A-Za-z0-9_]*$"); +let is_ctr = match(capitalized_name_regexp); let base_typs = ["String", "Int", "Float", "Bool"]; -let is_base_typ = regexp("^(" ++ String.concat("|", base_typs) ++ ")$"); -let is_typ_var = str => is_var(str) || is_capitalized_name(str); +let is_base_typ = + match(regexp("^(" ++ String.concat("|", base_typs) ++ ")$")); +let is_typ_var = str => is_var(str) || match(capitalized_name_regexp, str); let wild = "_"; -let is_wild = regexp("^" ++ wild ++ "$"); +let is_wild = match(regexp("^" ++ wild ++ "$")); /* List literals */ let list_start = "["; @@ -205,9 +203,8 @@ let duomerges = (lbl: Label.t): option(Label.t) => | _ => None }; -//TODO(andrew): refactor atomic_forms to seperate these out let const_mono_delims = - base_typs @ bools @ [wild, empty_list, empty_tuple, empty_string]; + base_typs @ bools @ [undefined, wild, empty_list, empty_tuple, empty_string]; let explicit_hole = "?"; let is_explicit_hole = t => t == explicit_hole; @@ -235,6 +232,7 @@ let atomic_forms: list((string, (string => bool, list(Mold.t)))) = [ ("int_lit", (is_int, [mk_op(Exp, []), mk_op(Pat, [])])), ("float_lit", (is_float, [mk_op(Exp, []), mk_op(Pat, [])])), ("bool_lit", (is_bool, [mk_op(Exp, []), mk_op(Pat, [])])), + ("undefined_lit", (is_undefined, [mk_op(Exp, []), mk_op(Pat, [])])), ("empty_list", (is_empty_list, [mk_op(Exp, []), mk_op(Pat, [])])), ( "empty_tuple", @@ -253,9 +251,9 @@ let atomic_forms: list((string, (string => bool, list(Mold.t)))) = [ let forms: list((string, t)) = [ // INFIX OPERATORS - ("typ_plus", mk_infix("+", Typ, P.or_)), - ("type-arrow", mk_infix("->", Typ, 6)), - ("cell-join", mk_infix(";", Exp, 10)), + ("typ_plus", mk_infix("+", Typ, P.type_plus)), + ("type-arrow", mk_infix("->", Typ, P.type_arrow)), + ("cell-join", mk_infix(";", Exp, P.semi)), ("plus", mk_infix("+", Exp, P.plus)), ("minus", mk_infix("-", Exp, P.plus)), ("times", mk_infix("*", Exp, P.mult)), @@ -290,14 +288,14 @@ let forms: list((string, t)) = [ ("cons_pat", mk_infix("::", Pat, P.cons)), ("typeann", mk(ss, [":"], mk_bin'(P.ann, Pat, Pat, [], Typ))), // UNARY PREFIX OPERATORS - ("not", mk(ii, ["!"], mk_pre(5, Exp, []))), //TODO: precedence + ("not", mk(ii, ["!"], mk_pre(P.not_, Exp, []))), ("typ_sum_single", mk(ss, ["+"], mk_pre(P.or_, Typ, []))), ("unary_minus", mk(ss, ["-"], mk_pre(P.neg, Exp, []))), ("unquote", mk(ss, ["$"], mk_pre(P.unquote, Exp, []))), // N-ARY OPS (on the semantics level) - ("comma_exp", mk_infix(",", Exp, P.prod)), - ("comma_pat", mk_infix(",", Pat, P.prod)), - ("comma_typ", mk_infix(",", Typ, P.prod)), + ("comma_exp", mk_infix(",", Exp, P.comma)), + ("comma_pat", mk_infix(",", Pat, P.comma)), + ("comma_typ", mk_infix(",", Typ, P.type_prod)), // PAIRED DELIMITERS: ("list_lit_exp", mk(ii, ["[", "]"], mk_op(Exp, [Exp]))), ("list_lit_pat", mk(ii, ["[", "]"], mk_op(Pat, [Pat]))), @@ -318,6 +316,7 @@ let forms: list((string, t)) = [ ("case", mk(ds, ["case", "end"], mk_op(Exp, [Rul]))), ("test", mk(ds, ["test", "end"], mk_op(Exp, [Exp]))), ("fun_", mk(ds, ["fun", "->"], mk_pre(P.fun_, Exp, [Pat]))), + ("fix", mk(ds, ["fix", "->"], mk_pre(P.fun_, Exp, [Pat]))), ("typfun", mk(ds, ["typfun", "->"], mk_pre(P.fun_, Exp, [TPat]))), ("forall", mk(ds, ["forall", "->"], mk_pre(P.fun_, Typ, [TPat]))), ("rec", mk(ds, ["rec", "->"], mk_pre(P.fun_, Typ, [TPat]))), diff --git a/src/haz3lcore/lang/Molds.re b/src/haz3lcore/lang/Molds.re index 8dd7a114ba..c754dac288 100644 --- a/src/haz3lcore/lang/Molds.re +++ b/src/haz3lcore/lang/Molds.re @@ -1,4 +1,3 @@ -open Sexplib.Std; open Util; [@deriving (show({with_path: false}), sexp, yojson)] @@ -21,7 +20,6 @@ let forms_assoc: list((Label.t, list(Mold.t))) = let get = (label: Label.t): list(Mold.t) => switch (label, List.assoc_opt(label, forms_assoc)) { | ([t], Some(molds)) when Form.atomic_molds(t) != [] => - // TODO(andrew): does this make sense? Form.atomic_molds(t) @ molds | ([t], None) when Form.atomic_molds(t) != [] => Form.atomic_molds(t) | (_, Some(molds)) => molds diff --git a/src/haz3lcore/lang/Operators.re b/src/haz3lcore/lang/Operators.re new file mode 100644 index 0000000000..aa8842b72b --- /dev/null +++ b/src/haz3lcore/lang/Operators.re @@ -0,0 +1,177 @@ +[@deriving (show({with_path: false}), sexp, yojson)] +type op_un_bool = + | Not; + +[@deriving (show({with_path: false}), sexp, yojson)] +type op_un_meta = + | Unquote; + +[@deriving (show({with_path: false}), sexp, yojson)] +type op_un_int = + | Minus; + +[@deriving (show({with_path: false}), sexp, yojson)] +type op_bin_bool = + | And + | Or; + +[@deriving (show({with_path: false}), sexp, yojson)] +type op_bin_int = + | Plus + | Minus + | Times + | Power + | Divide + | LessThan + | LessThanOrEqual + | GreaterThan + | GreaterThanOrEqual + | Equals + | NotEquals; + +[@deriving (show({with_path: false}), sexp, yojson)] +type op_bin_float = + | Plus + | Minus + | Times + | Power + | Divide + | LessThan + | LessThanOrEqual + | GreaterThan + | GreaterThanOrEqual + | Equals + | NotEquals; + +[@deriving (show({with_path: false}), sexp, yojson)] +type op_bin_string = + | Concat + | Equals; + +[@deriving (show({with_path: false}), sexp, yojson)] +type op_un = + | Meta(op_un_meta) + | Int(op_un_int) + | Bool(op_un_bool); + +[@deriving (show({with_path: false}), sexp, yojson)] +type op_bin = + | Int(op_bin_int) + | Float(op_bin_float) + | Bool(op_bin_bool) + | String(op_bin_string); + +[@deriving (show({with_path: false}), sexp, yojson)] +type ap_direction = + | Forward + | Reverse; + +// Are these show function necessary? +let show_op_un_meta: op_un_meta => string = + fun + | Unquote => "Un-quotation"; + +let show_op_un_bool: op_un_bool => string = + fun + | Not => "Boolean Negation"; + +let show_op_un_int: op_un_int => string = + fun + | Minus => "Integer Negation"; + +let show_unop: op_un => string = + fun + | Meta(op) => show_op_un_meta(op) + | Bool(op) => show_op_un_bool(op) + | Int(op) => show_op_un_int(op); + +let show_op_bin_bool: op_bin_bool => string = + fun + | And => "Boolean Conjunction" + | Or => "Boolean Disjunction"; + +let show_op_bin_int: op_bin_int => string = + fun + | Plus => "Integer Addition" + | Minus => "Integer Subtraction" + | Times => "Integer Multiplication" + | Power => "Integer Exponentiation" + | Divide => "Integer Division" + | LessThan => "Integer Less Than" + | LessThanOrEqual => "Integer Less Than or Equal" + | GreaterThan => "Integer Greater Than" + | GreaterThanOrEqual => "Integer Greater Than or Equal" + | Equals => "Integer Equality" + | NotEquals => "Integer Inequality"; + +let show_op_bin_float: op_bin_float => string = + fun + | Plus => "Float Addition" + | Minus => "Float Subtraction" + | Times => "Float Multiplication" + | Power => "Float Exponentiation" + | Divide => "Float Division" + | LessThan => "Float Less Than" + | LessThanOrEqual => "Float Less Than or Equal" + | GreaterThan => "Float Greater Than" + | GreaterThanOrEqual => "Float Greater Than or Equal" + | Equals => "Float Equality" + | NotEquals => "Float Inequality"; + +let show_op_bin_string: op_bin_string => string = + fun + | Concat => "String Concatenation" + | Equals => "String Equality"; + +let show_binop: op_bin => string = + fun + | Int(op) => show_op_bin_int(op) + | Float(op) => show_op_bin_float(op) + | Bool(op) => show_op_bin_bool(op) + | String(op) => show_op_bin_string(op); + +let bool_op_to_string = (op: op_bin_bool): string => { + switch (op) { + | And => "&&" + | Or => "||" + }; +}; + +let int_op_to_string = (op: op_bin_int): string => { + switch (op) { + | Plus => "+" + | Minus => "-" + | Times => "*" + | Power => "**" + | Divide => "/" + | LessThan => "<" + | LessThanOrEqual => "<=" + | GreaterThan => ">" + | GreaterThanOrEqual => ">=" + | Equals => "==" + | NotEquals => "!=" + }; +}; + +let float_op_to_string = (op: op_bin_float): string => { + switch (op) { + | Plus => "+." + | Minus => "-." + | Times => "*." + | Power => "**." + | Divide => "/." + | LessThan => "<." + | LessThanOrEqual => "<=." + | GreaterThan => ">." + | GreaterThanOrEqual => ">=." + | Equals => "==." + | NotEquals => "!=." + }; +}; + +let string_op_to_string = (op: op_bin_string): string => { + switch (op) { + | Concat => "++" + | Equals => "$==" + }; +}; diff --git a/src/haz3lcore/lang/Precedence.re b/src/haz3lcore/lang/Precedence.re index b7d00796a5..7d72b66404 100644 --- a/src/haz3lcore/lang/Precedence.re +++ b/src/haz3lcore/lang/Precedence.re @@ -1,4 +1,3 @@ -open Sexplib.Std; open Util; /** @@ -14,6 +13,7 @@ let ap = 2; let neg = 3; let power = 4; let mult = 5; +let not_ = 5; let plus = 6; let cons = 7; let concat = 8; @@ -23,7 +23,6 @@ let or_ = 11; let ann = 12; let if_ = 13; let fun_ = 14; -let prod = 15; let semi = 16; let let_ = 17; let filter = 18; @@ -32,7 +31,13 @@ let rule_pre = 20; let rule_sep = 21; let case_ = 22; -let min = 23; +let comma = 15; + +let type_plus = 4; +let type_arrow = 5; +let type_prod = comma; + +let min = 26; let compare = (p1: t, p2: t): int => (-1) * Int.compare((p1 :> int), (p2 :> int)); @@ -47,6 +52,7 @@ let associativity_map: IntMap.t(Direction.t) = (concat, Right), (ann, Left), (eqs, Left), + (type_arrow, Right), ] |> List.to_seq |> IntMap.of_seq; diff --git a/src/haz3lcore/lang/term/Any.re b/src/haz3lcore/lang/term/Any.re new file mode 100644 index 0000000000..b759e67fc9 --- /dev/null +++ b/src/haz3lcore/lang/term/Any.re @@ -0,0 +1 @@ +include Term.Any; diff --git a/src/haz3lcore/lang/term/Cls.re b/src/haz3lcore/lang/term/Cls.re new file mode 100644 index 0000000000..e1acb702c8 --- /dev/null +++ b/src/haz3lcore/lang/term/Cls.re @@ -0,0 +1,18 @@ +[@deriving (show({with_path: false}), sexp, yojson)] +type t = + | Exp(Exp.cls) + | Pat(Pat.cls) + | Typ(Typ.cls) + | TPat(TPat.cls) + | Rul(Rul.cls) + | Secondary(Secondary.cls); + +let show = (cls: t) => + switch (cls) { + | Exp(cls) => Exp.show_cls(cls) + | Pat(cls) => Pat.show_cls(cls) + | Typ(cls) => Typ.show_cls(cls) + | TPat(cls) => TPat.show_cls(cls) + | Rul(cls) => Rul.show_cls(cls) + | Secondary(cls) => Secondary.show_cls(cls) + }; diff --git a/src/haz3lcore/lang/term/Exp.re b/src/haz3lcore/lang/term/Exp.re new file mode 100644 index 0000000000..ff620a0166 --- /dev/null +++ b/src/haz3lcore/lang/term/Exp.re @@ -0,0 +1 @@ +include Term.Exp; diff --git a/src/haz3lcore/lang/term/IdTagged.re b/src/haz3lcore/lang/term/IdTagged.re new file mode 100644 index 0000000000..3812b0e83f --- /dev/null +++ b/src/haz3lcore/lang/term/IdTagged.re @@ -0,0 +1,32 @@ +open Util; + +[@deriving (show({with_path: false}), sexp, yojson)] +type t('a) = { + [@show.opaque] + ids: list(Id.t), + [@show.opaque] + /* UExp invariant: copied should always be false, and the id should be unique + DHExp invariant: if copied is true, then this term and its children may not + have unique ids. The flag is used to avoid deep-copying expressions during + evaluation, while keeping track of where we will need to replace the ids + at the end of evaluation to keep them unique.*/ + copied: bool, + term: 'a, +}; + +// To be used if you want to remove the id from the debug output +// let pp: ((Format.formatter, 'a) => unit, Format.formatter, t('a)) => unit = +// (fmt_a, formatter, ta) => { +// fmt_a(formatter, ta.term); +// }; +let fresh = term => { + {ids: [Id.mk()], copied: false, term}; +}; + +let term_of = x => x.term; +let unwrap = x => (x.term, term' => {...x, term: term'}); +let rep_id = ({ids, _}) => List.hd(ids); +let fast_copy = (id, {term, _}) => {ids: [id], term, copied: true}; +let new_ids = + fun + | {ids: _, term, copied} => {ids: [Id.mk()], term, copied}; diff --git a/src/haz3lcore/lang/term/Pat.re b/src/haz3lcore/lang/term/Pat.re new file mode 100644 index 0000000000..b4bb875bdd --- /dev/null +++ b/src/haz3lcore/lang/term/Pat.re @@ -0,0 +1 @@ +include Term.Pat; diff --git a/src/haz3lcore/lang/term/Rul.re b/src/haz3lcore/lang/term/Rul.re new file mode 100644 index 0000000000..9a293a4270 --- /dev/null +++ b/src/haz3lcore/lang/term/Rul.re @@ -0,0 +1 @@ +include Term.Rul; diff --git a/src/haz3lcore/lang/term/TPat.re b/src/haz3lcore/lang/term/TPat.re new file mode 100644 index 0000000000..3dade36b54 --- /dev/null +++ b/src/haz3lcore/lang/term/TPat.re @@ -0,0 +1,31 @@ +[@deriving (show({with_path: false}), sexp, yojson)] +type cls = + | Invalid + | EmptyHole + | MultiHole + | Var; + +include TermBase.TPat; + +let rep_id: t => Id.t = IdTagged.rep_id; +let fresh: term => t = IdTagged.fresh; + +let hole = (tms: list(TermBase.Any.t)) => + switch (tms) { + | [] => EmptyHole + | [_, ..._] => MultiHole(tms) + }; + +let cls_of_term: term => cls = + fun + | Invalid(_) => Invalid + | EmptyHole => EmptyHole + | MultiHole(_) => MultiHole + | Var(_) => Var; + +let show_cls: cls => string = + fun + | Invalid => "Invalid type alias" + | MultiHole => "Broken type alias" + | EmptyHole => "Empty type alias hole" + | Var => "Type alias"; diff --git a/src/haz3lcore/lang/term/Typ.re b/src/haz3lcore/lang/term/Typ.re new file mode 100644 index 0000000000..a7f91b308e --- /dev/null +++ b/src/haz3lcore/lang/term/Typ.re @@ -0,0 +1,661 @@ +open Util; +open OptUtil.Syntax; + +[@deriving (show({with_path: false}), sexp, yojson)] +type cls = + | Invalid + | EmptyHole + | MultiHole + | SynSwitch + | Internal + | Int + | Float + | Bool + | String + | Arrow + | Prod + | Sum + | List + | Var + | Constructor + | Module + | ModuleVar + | Parens + | Ap + | Rec + | Forall; + +include TermBase.Typ; + +let term_of: t => term = IdTagged.term_of; +let unwrap: t => (term, term => t) = IdTagged.unwrap; +let fresh: term => t = IdTagged.fresh; +/* fresh assigns a random id, whereas temp assigns Id.invalid, which + is a lot faster, and since we so often make types and throw them away + shortly after, it makes sense to use it. */ +let temp: term => t = term => {term, ids: [Id.invalid], copied: false}; +let rep_id: t => Id.t = IdTagged.rep_id; + +let hole = (tms: list(TermBase.Any.t)) => + switch (tms) { + | [] => Unknown(Hole(EmptyHole)) + | [_, ..._] => Unknown(Hole(MultiHole(tms))) + }; + +let cls_of_term: term => cls = + fun + | Unknown(Hole(Invalid(_))) => Invalid + | Unknown(Hole(EmptyHole)) => EmptyHole + | Unknown(Hole(MultiHole(_))) => MultiHole + | Unknown(SynSwitch) => SynSwitch + | Unknown(Internal) => Internal + | Int => Int + | Float => Float + | Bool => Bool + | String => String + | List(_) => List + | Arrow(_) => Arrow + | Var(_) => Var + | Prod(_) => Prod + | Parens(_) => Parens + | Module(_) => Module + | Ap(_) => Ap + | Sum(_) => Sum + | Rec(_) => Rec + | Forall(_) => Forall; + +let show_cls: cls => string = + fun + | Invalid => "Invalid type" + | MultiHole => "Broken type" + | EmptyHole => "Empty type hole" + | SynSwitch => "Synthetic type" + | Internal => "Internal type" + | Int + | Float + | String + | Bool => "Base type" + | Var => "Type variable" + | Constructor => "Sum constructor" + | List => "List type" + | Arrow => "Function type" + | Prod => "Product type" + | Sum => "Sum type" + | Parens => "Parenthesized type" + | Module => "Module type" + | ModuleVar => "Module path" + | Ap => "Constructor application" + | Rec => "Recursive type" + | Forall => "Forall type"; + +let rec is_arrow = (typ: t) => { + switch (typ.term) { + | Parens(typ) => is_arrow(typ) + | Arrow(_) => true + | Unknown(_) + | Int + | Float + | Bool + | String + | List(_) + | Prod(_) + | Var(_) + | Ap(_) + | Sum(_) + | Forall(_) + | Module(_) + | Rec(_) => false + }; +}; + +let rec is_forall = (typ: t) => { + switch (typ.term) { + | Parens(typ) => is_forall(typ) + | Forall(_) => true + | Unknown(_) + | Int + | Float + | Bool + | String + | Arrow(_) + | List(_) + | Prod(_) + | Var(_) + | Ap(_) + | Sum(_) + | Module(_) + | Rec(_) => false + }; +}; + +/* Functions below this point assume that types have been through the to_typ function above */ + +[@deriving (show({with_path: false}), sexp, yojson)] +type source = { + id: Id.t, + ty: t, +}; + +/* Strip location information from a list of sources */ +let of_source = List.map((source: source) => source.ty); + +/* How type provenance information should be collated when + joining unknown types. This probably requires more thought, + but right now TypeHole strictly predominates over Internal + which strictly predominates over SynSwitch. */ +let join_type_provenance = + (p1: type_provenance, p2: type_provenance): type_provenance => + switch (p1, p2) { + | (Hole(h1), Hole(h2)) when h1 == h2 => Hole(h1) + | (Hole(EmptyHole), Hole(EmptyHole) | SynSwitch) + | (SynSwitch, Hole(EmptyHole)) => Hole(EmptyHole) + | (SynSwitch, Internal) + | (Internal, SynSwitch) => SynSwitch + | (Internal | Hole(_), _) + | (_, Hole(_)) => Internal + | (SynSwitch, SynSwitch) => SynSwitch + }; + +let rec free_vars = (~bound=[], ty: t): list(Var.t) => + switch (term_of(ty)) { + | Unknown(_) + | Int + | Float + | Bool + | String => [] + | Ap(t1, t2) => free_vars(~bound, t1) @ free_vars(~bound, t2) + | Var(v) => List.mem(v, bound) ? [] : [v] + | Parens(ty) => free_vars(~bound, ty) + | List(ty) => free_vars(~bound, ty) + | Arrow(t1, t2) => free_vars(~bound, t1) @ free_vars(~bound, t2) + | Sum(sm) => ConstructorMap.free_variables(free_vars(~bound), sm) + | Prod(tys) => ListUtil.flat_map(free_vars(~bound), tys) + | Module({inner_ctx, _}) => + let ctx_entry_subst = (l: list(Token.t), e: Ctx.entry): list(Token.t) => { + switch (e) { + | VarEntry(t) + | ConstructorEntry(t) => l @ free_vars(t.typ) + | TVarEntry(_) => l + }; + }; + List.fold_left(ctx_entry_subst, [], inner_ctx); + | Member(_, ty) => free_vars(ty) + | Rec(x, ty) + | Forall(x, ty) => + free_vars(~bound=(x |> TPat.tyvar_of_utpat |> Option.to_list) @ bound, ty) + }; + +let var_count = ref(0); +let fresh_var = (var_name: string) => { + let x = var_count^; + var_count := x + 1; + var_name ++ "_α" ++ string_of_int(x); +}; + +let unroll = (ty: t): t => + switch (term_of(ty)) { + | Rec(tp, ty_body) => subst(ty, tp, ty_body) + | _ => ty + }; + +/* Type Equality: This coincides with alpha equivalence for normalized types. + Other types may be equivalent but this will not detect so if they are not normalized. */ +let eq = (t1: t, t2: t): bool => fast_equal(t1, t2); + +/* Lattice join on types. This is a LUB join in the hazel2 + sense in that any type dominates Unknown. The optional + resolve parameter specifies whether, in the case of a type + variable and a succesful join, to return the resolved join type, + or to return the (first) type variable for readability */ +let rec join = (~resolve=false, ~fix, ctx: Ctx.t, ty1: t, ty2: t): option(t) => { + let join' = join(~resolve, ~fix, ctx); + switch (term_of(ty1), term_of(ty2)) { + | (_, Parens(ty2)) => join'(ty1, ty2) + | (Parens(ty1), _) => join'(ty1, ty2) + | (Member(_, Unknown(Internal)), ty) + | (ty, Member(_, Unknown(Internal))) => Some(ty) + | (Member(n1, ty1), Member(n2, ty2)) => + if (n1 == n2) { + let* ty = join'(ty1, ty2); + Some(Member(n1, ty)); + } else { + let+ ty_join = join'(ty1, ty2); + resolve ? ty_join : Member(n1, ty_join); + } + | (Member(name, ty1), ty2) + | (ty2, Member(name, ty1)) => + let+ ty_join = join'(ty1, ty2); + resolve ? ty_join : Member(name, ty_join); + | (_, Unknown(Hole(_))) when fix => + /* NOTE(andrew): This is load bearing + for ensuring that function literals get appropriate + casts. Documentation/Dynamics has regression tests */ + Some(ty2) + | (Unknown(p1), Unknown(p2)) => + Some(Unknown(join_type_provenance(p1, p2)) |> temp) + | (Unknown(_), _) => Some(ty2) + | (_, Unknown(Internal | SynSwitch)) => Some(ty1) + | (Var(n1), Var(n2)) => + if (n1 == n2) { + Some(ty1); + } else { + let* ty1 = Ctx.lookup_alias(ctx, n1); + let* ty2 = Ctx.lookup_alias(ctx, n2); + let+ ty_join = join'(ty1, ty2); + !resolve && eq(ty1, ty_join) ? ty1 : ty_join; + } + | (Var(name), _) => + let* ty_name = Ctx.lookup_alias(ctx, name); + let+ ty_join = join'(ty_name, ty2); + !resolve && eq(ty_name, ty_join) ? ty1 : ty_join; + | (_, Var(name)) => + let* ty_name = Ctx.lookup_alias(ctx, name); + let+ ty_join = join'(ty_name, ty1); + !resolve && eq(ty_name, ty_join) ? ty2 : ty_join; + /* Note: Ordering of Unknown, Var, and Rec above is load-bearing! */ + | (Rec(tp1, ty1), Rec(tp2, ty2)) => + let ctx = Ctx.extend_dummy_tvar(ctx, tp1); + let ty1' = + switch (TPat.tyvar_of_utpat(tp2)) { + | Some(x2) => subst(Var(x2) |> temp, tp1, ty1) + | None => ty1 + }; + let+ ty_body = join(~resolve, ~fix, ctx, ty1', ty2); + Rec(tp1, ty_body) |> temp; + | (Rec(_), _) => None + | (Forall(x1, ty1), Forall(x2, ty2)) => + let ctx = Ctx.extend_dummy_tvar(ctx, x1); + let ty1' = + switch (TPat.tyvar_of_utpat(x2)) { + | Some(x2) => subst(Var(x2) |> temp, x1, ty1) + | None => ty1 + }; + let+ ty_body = join(~resolve, ~fix, ctx, ty1', ty2); + Forall(x1, ty_body) |> temp; + /* Note for above: there is no danger of free variable capture as + subst itself performs capture avoiding substitution. However this + may generate internal type variable names that in corner cases can + be exposed to the user. We preserve the variable name of the + second type to preserve synthesized type variable names, which + come from user annotations. */ + | (Forall(_), _) => None + | (Int, Int) => Some(ty1) + | (Int, _) => None + | (Float, Float) => Some(ty1) + | (Float, _) => None + | (Bool, Bool) => Some(ty1) + | (Bool, _) => None + | (String, String) => Some(ty1) + | (String, _) => None + | (Arrow(ty1, ty2), Arrow(ty1', ty2')) => + let* ty1 = join'(ty1, ty1'); + let+ ty2 = join'(ty2, ty2'); + Arrow(ty1, ty2) |> temp; + | (Arrow(_), _) => None + | (Prod(tys1), Prod(tys2)) => + let* tys = ListUtil.map2_opt(join', tys1, tys2); + let+ tys = OptUtil.sequence(tys); + Prod(tys) |> temp; + | (Prod(_), _) => None + | (Sum(sm1), Sum(sm2)) => + let+ sm' = ConstructorMap.join(eq, join(~resolve, ~fix, ctx), sm1, sm2); + Sum(sm') |> temp; + | (Sum(_), _) => None + | (List(ty1), List(ty2)) => + let+ ty = join'(ty1, ty2); + List(ty) |> temp; + | (List(_), _) => None + | (Ap(_), _) => failwith("Type join of ap") + | (Module(ctx1), Module(ctx2)) => + /* Module types can join if and only if for every variable, + Either: it appears in both ctxs and the types can join, + Or: it appears only in one ctx and the other ctx is incomplete */ + let join_entry = + ( + {inner_ctx, incomplete}: module_typ, + ctx_joined: option(Ctx.t), + ctx1_entry: Ctx.entry, + ) + : option(Ctx.t) => { + let do_incomplete = (entry1: 'a, entry2: option('a)): option('a) => + if (incomplete && entry2 == None) { + Some(entry1); + } else { + entry2; + }; + let* ctx_joined = ctx_joined; + switch (ctx1_entry) { + | VarEntry({name, typ, id} as entry1) => + let* entry2 = + Ctx.lookup_var(inner_ctx, name) |> do_incomplete(entry1); + let+ typ_joined = join'(typ, entry2.typ); + Ctx.extend(ctx_joined, VarEntry({name, typ: typ_joined, id})); + | ConstructorEntry({name, typ, id} as entry1) => + let* entry2 = + Ctx.lookup_ctr(inner_ctx, name) |> do_incomplete(entry1); + let+ typ_joined = join'(typ, entry2.typ); + Ctx.extend( + ctx_joined, + ConstructorEntry({name, typ: typ_joined, id}), + ); + | TVarEntry({name, kind, id}) => + let* entry2 = Ctx.lookup_tvar(inner_ctx, name); + let+ kind_joined = + switch (kind, entry2.kind) { + | (Abstract, Abstract) => Some(Kind.Abstract) + | (Singleton(ty1), Singleton(ty2)) => + let+ typ_joined = join'(ty1, ty2); + Kind.Singleton(typ_joined); + | _ => None + }; + Ctx.extend(ctx_joined, TVarEntry({name, kind: kind_joined, id})); + }; + }; + let* ctx = List.fold_left(join_entry(ctx2), Some([]), ctx1.inner_ctx); + let* ctx = List.fold_left(join_entry(ctx1), Some(ctx), ctx2.inner_ctx); + Some( + Module({ + inner_ctx: ctx |> Ctx.filter_duplicates, + incomplete: ctx1.incomplete && ctx2.incomplete, + }), + ); + | (Module(_), _) => None + }; +}; + +/* REQUIRES NORMALIZED TYPES + Remove synswitches from t1 by matching against t2 */ +let rec match_synswitch = (t1: t, t2: t) => { + let (term1, rewrap1) = unwrap(t1); + switch (term1, term_of(t2)) { + | (Parens(t1), _) => Parens(match_synswitch(t1, t2)) |> rewrap1 + | (Unknown(SynSwitch), _) => t2 + // These cases can't have a synswitch inside + | (Unknown(_), _) + | (Int, _) + | (Float, _) + | (Bool, _) + | (String, _) + | (Var(_), _) + | (Ap(_), _) + | (Rec(_), _) + | (Forall(_), _) => t1 + // These might + | (List(ty1), List(ty2)) => List(match_synswitch(ty1, ty2)) |> rewrap1 + | (List(_), _) => t1 + | (Arrow(ty1, ty2), Arrow(ty1', ty2')) => + Arrow(match_synswitch(ty1, ty1'), match_synswitch(ty2, ty2')) |> rewrap1 + | (Arrow(_), _) => t1 + | (Prod(tys1), Prod(tys2)) when List.length(tys1) == List.length(tys2) => + let tys = List.map2(match_synswitch, tys1, tys2); + Prod(tys) |> rewrap1; + | (Prod(_), _) => t1 + | (Sum(sm1), Sum(sm2)) => + let sm' = ConstructorMap.match_synswitch(match_synswitch, eq, sm1, sm2); + Sum(sm') |> rewrap1; + | (Sum(_), _) => t1 + }; +}; + +let join_fix = join(~fix=true); + +let join_all = (~empty: t, ctx: Ctx.t, ts: list(t)): option(t) => + List.fold_left( + (acc, ty) => OptUtil.and_then(join(~fix=false, ctx, ty), acc), + Some(empty), + ts, + ); + +let is_consistent = (ctx: Ctx.t, ty1: t, ty2: t): bool => + join(~fix=false, ctx, ty1, ty2) != None; + +let rec normalize = (ctx: Ctx.t, ty: t): t => { + let (term, rewrap) = unwrap(ty); + switch (term) { + | Var(x) => + switch (Ctx.lookup_alias(ctx, x)) { + | Some(ty) => normalize(ctx, ty) + | None => ty + } + | Unknown(_) + | Int + | Float + | Bool + | String => ty + | Parens(t) => Parens(normalize(ctx, t)) |> rewrap + | List(t) => List(normalize(ctx, t)) |> rewrap + | Ap(t1, t2) => Ap(normalize(ctx, t1), normalize(ctx, t2)) |> rewrap + | Arrow(t1, t2) => + Arrow(normalize(ctx, t1), normalize(ctx, t2)) |> rewrap + | Prod(ts) => Prod(List.map(normalize(ctx), ts)) |> rewrap + | Sum(ts) => + Sum(ConstructorMap.map(Option.map(normalize(ctx)), ts)) |> rewrap + | Module({inner_ctx, incomplete}) => + let ctx_entry_subst = (e: Ctx.entry): Ctx.entry => { + switch (e) { + | VarEntry(t) => VarEntry({...t, typ: normalize(ctx, t.typ)}) + | ConstructorEntry(t) => + ConstructorEntry({...t, typ: normalize(ctx, t.typ)}) + | TVarEntry(_) => e + }; + }; + Module({inner_ctx: List.map(ctx_entry_subst, inner_ctx), incomplete}); + | Member(name, ty) => Member(name, normalize(ctx, ty)) + | Rec(tpat, ty) => + /* NOTE: Dummy tvar added has fake id but shouldn't matter + as in current implementation Recs do not occur in the + surface syntax, so we won't try to jump to them. */ + Rec(tpat, normalize(Ctx.extend_dummy_tvar(ctx, tpat), ty)) |> rewrap + | Forall(name, ty) => + Forall(name, normalize(Ctx.extend_dummy_tvar(ctx, name), ty)) |> rewrap + }; +}; + +let rec matched_arrow_strict = (ctx, ty) => + switch (term_of(weak_head_normalize(ctx, ty))) { + | Parens(ty) => matched_arrow_strict(ctx, ty) + | Arrow(ty_in, ty_out) => Some((ty_in, ty_out)) + | Unknown(SynSwitch) => + Some((Unknown(SynSwitch) |> temp, Unknown(SynSwitch) |> temp)) + | _ => None + }; + +let matched_arrow = (ctx, ty) => + matched_arrow_strict(ctx, ty) + |> Option.value( + ~default=(Unknown(Internal) |> temp, Unknown(Internal) |> temp), + ); + +let rec matched_forall_strict = (ctx, ty) => + switch (term_of(weak_head_normalize(ctx, ty))) { + | Parens(ty) => matched_forall_strict(ctx, ty) + | Forall(t, ty) => Some((Some(t), ty)) + | Unknown(SynSwitch) => Some((None, Unknown(SynSwitch) |> temp)) + | _ => None // (None, Unknown(Internal) |> temp) + }; + +let matched_forall = (ctx, ty) => + matched_forall_strict(ctx, ty) + |> Option.value(~default=(None, Unknown(Internal) |> temp)); + +let rec matched_prod_strict = (ctx, length, ty) => + switch (term_of(weak_head_normalize(ctx, ty))) { + | Parens(ty) => matched_prod_strict(ctx, length, ty) + | Prod(tys) when List.length(tys) == length => Some(tys) + | Unknown(SynSwitch) => + Some(List.init(length, _ => Unknown(SynSwitch) |> temp)) + | _ => None + }; + +let matched_prod = (ctx, length, ty) => + matched_prod_strict(ctx, length, ty) + |> Option.value(~default=List.init(length, _ => Unknown(Internal) |> temp)); + +let rec matched_list_strict = (ctx, ty) => + switch (term_of(weak_head_normalize(ctx, ty))) { + | Parens(ty) => matched_list_strict(ctx, ty) + | List(ty) => Some(ty) + | Unknown(SynSwitch) => Some(Unknown(SynSwitch) |> temp) + | _ => None + }; + +let matched_list = (ctx, ty) => + matched_list_strict(ctx, ty) + |> Option.value(~default=Unknown(Internal) |> temp); + +let rec matched_args = (ctx, default_arity, ty) => { + let ty' = weak_head_normalize(ctx, ty); + switch (term_of(ty')) { + | Parens(ty) => matched_args(ctx, default_arity, ty) + | Prod([_, ..._] as tys) => tys + | Unknown(_) => List.init(default_arity, _ => ty') + | _ => [ty'] + }; +}; + +let rec get_sum_constructors = (ctx: Ctx.t, ty: t): option(sum_map) => { + let ty = weak_head_normalize(ctx, ty); + switch (term_of(ty)) { + | Parens(ty) => get_sum_constructors(ctx, ty) + | Member(_, ty) => get_sum_constructors(ctx, ty) + | Sum(sm) => Some(sm) + | Rec(_) => + /* Note: We must unroll here to get right ctr types; + otherwise the rec parameter will leak. However, seeing + as substitution is too expensive to be used here, we + currently making the optimization that, since all + recursive types are type alises which use the alias name + as the recursive parameter, and type aliases cannot be + shadowed, it is safe to simply remove the Rec constructor, + provided we haven't escaped the context in which the alias + is bound. If either of the above assumptions become invalid, + the below code will be incorrect! */ + let ty = + switch (ty |> term_of) { + | Rec({term: Var(x), _}, ty_body) => + switch (Ctx.lookup_alias(ctx, x)) { + | None => unroll(ty) + | Some(_) => ty_body + } + | _ => ty + }; + switch (ty |> term_of) { + | Sum(sm) => Some(sm) + | _ => None + }; + | _ => None + }; +}; + +let rec is_unknown = (ty: t): bool => + switch (ty |> term_of) { + | Parens(x) => is_unknown(x) + | Unknown(_) => true + | _ => false + }; + +/* Does the type require parentheses when on the left of an arrow for printing? */ +let rec needs_parens = (ty: t): bool => + switch (term_of(ty)) { + | Parens(ty) => needs_parens(ty) + | Ap(_) + | Unknown(_) + | Int + | Float + | String + | Bool + | Module(_) + | Member(_) + | Var(_) => false + | Rec(_, _) + | Forall(_, _) => true + | List(_) => false /* is already wrapped in [] */ + | Arrow(_, _) => true + | Prod(_) + | Sum(_) => true /* disambiguate between (A + B) -> C and A + (B -> C) */ + }; + +let pretty_print_tvar = (tv: TPat.t): string => + switch (IdTagged.term_of(tv)) { + | Var(x) => x + | Invalid(_) + | EmptyHole + | MultiHole(_) => "?" + }; + +/* Essentially recreates haz3lweb/view/Type.re's view_ty but with string output */ +let rec pretty_print = (ty: t): string => + switch (term_of(ty)) { + | Parens(ty) => pretty_print(ty) + | Ap(_) + | Unknown(_) => "?" + | Int => "Int" + | Float => "Float" + | Bool => "Bool" + | String => "String" + | Var(tvar) => tvar + | List(t) => "[" ++ pretty_print(t) ++ "]" + | Arrow(t1, t2) => paren_pretty_print(t1) ++ " -> " ++ pretty_print(t2) + | Sum(sm) => + switch (sm) { + | [] => "+?" + | [t0] => "+" ++ ctr_pretty_print(t0) + | [t0, ...ts] => + List.fold_left( + (acc, t) => acc ++ " + " ++ ctr_pretty_print(t), + ctr_pretty_print(t0), + ts, + ) + } + | Prod([]) => "()" + | Prod([t0, ...ts]) => + "(" + ++ List.fold_left( + (acc, t) => acc ++ ", " ++ pretty_print(t), + pretty_print(t0), + ts, + ) + ++ ")" + | Module({inner_ctx: [], incomplete: false}) => "Module" + | Module({inner_ctx: [], incomplete: true}) => "Module{...}" + | Module({inner_ctx: [e, ...es], incomplete}) => + let view_entry = (m: Ctx.entry): string => { + switch (m) { + | VarEntry({name: n0, typ: t0, _}) + | ConstructorEntry({name: n0, typ: t0, _}) => + n0 ++ ":" ++ pretty_print(t0) + + | TVarEntry({name: n0, kind: Singleton(t0), _}) => + "Type " ++ n0 ++ "=" ++ pretty_print(t0) + + | TVarEntry({name: n0, _}) => + "Type " ++ n0 ++ "=" ++ pretty_print(Unknown(Internal)) + }; + }; + "Module{" + ++ List.fold_left( + (acc, t) => acc ++ ", " ++ view_entry(t), + view_entry(e), + es, + ) + ++ view_entry(e) + ++ (incomplete ? ",..." : "") + ++ "}"; + | Member(name, _) => name + | Rec(tv, t) => + "rec " ++ pretty_print_tvar(tv) ++ " -> " ++ pretty_print(t) + | Forall(tv, t) => + "forall " ++ pretty_print_tvar(tv) ++ " -> " ++ pretty_print(t) + } +and ctr_pretty_print = + fun + | ConstructorMap.Variant(ctr, _, None) => ctr + | ConstructorMap.Variant(ctr, _, Some(t)) => + ctr ++ "(" ++ pretty_print(t) ++ ")" + | ConstructorMap.BadEntry(_) => "?" +and paren_pretty_print = typ => + if (needs_parens(typ)) { + "(" ++ pretty_print(typ) ++ ")"; + } else { + pretty_print(typ); + }; diff --git a/src/haz3lcore/prog/CachedStatics.re b/src/haz3lcore/prog/CachedStatics.re index 336d61f3a3..f2bc13d113 100644 --- a/src/haz3lcore/prog/CachedStatics.re +++ b/src/haz3lcore/prog/CachedStatics.re @@ -1,14 +1,14 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type statics = { - term: Term.UExp.t, + term: UExp.t, info_map: Statics.Map.t, error_ids: list(Id.t), }; let empty_statics: statics = { - term: Term.UExp.{ids: [Id.invalid], term: Triv}, + term: UExp.{ids: [Id.invalid], copied: false, term: Tuple([])}, info_map: Id.Map.empty, error_ids: [], }; diff --git a/src/haz3lcore/prog/CoreSettings.re b/src/haz3lcore/prog/CoreSettings.re index 327187cd2c..a23fbee307 100644 --- a/src/haz3lcore/prog/CoreSettings.re +++ b/src/haz3lcore/prog/CoreSettings.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; module Evaluation = { [@deriving (show({with_path: false}), sexp, yojson)] diff --git a/src/haz3lcore/prog/Interface.re b/src/haz3lcore/prog/Interface.re index 91d7237e06..3249b1aef2 100644 --- a/src/haz3lcore/prog/Interface.re +++ b/src/haz3lcore/prog/Interface.re @@ -1,38 +1,4 @@ -module Statics = { - let mk_map' = - Core.Memo.general(~cache_size_bound=1000, e => { - Statics.uexp_to_info_map( - ~ctx=Builtins.ctx_init, - ~ancestors=[], - e, - Id.Map.empty, - ) - |> snd - }); - let mk_map = (core: CoreSettings.t, exp) => - core.statics ? mk_map'(exp) : Id.Map.empty; - - let mk_map_and_info_ctx = - Core.Memo.general(~cache_size_bound=1000, (ctx, e) => { - Statics.uexp_to_info_map(~ctx, ~ancestors=[], e, Id.Map.empty) - }); - let mk_map_and_info_ctx = (core: CoreSettings.t, ctx, exp) => - core.statics - ? { - let (info, map) = mk_map_and_info_ctx(ctx, exp); - (Some(info), map); - } - : (None, Id.Map.empty); - - let mk_map_ctx = - Core.Memo.general(~cache_size_bound=1000, (ctx, e) => { - Statics.uexp_to_info_map(~ctx, ~ancestors=[], e, Id.Map.empty) |> snd - }); - let mk_map_ctx = (core: CoreSettings.t, ctx, exp) => - core.statics ? mk_map_ctx(ctx, exp) : Id.Map.empty; -}; - -let dh_err = (error: string): DHExp.t => BoundVar(error); +let dh_err = (error: string): DHExp.t => Var(error) |> DHExp.fresh; let elaborate = Core.Memo.general(~cache_size_bound=1000, Elaborator.uexp_elab); @@ -54,9 +20,9 @@ let evaluate = (~settings: CoreSettings.t, ~env=Builtins.env_init, elab: DHExp.t) : ProgramResult.t => switch () { - | _ when !settings.dynamics => Off(elab) + | _ when !settings.dynamics => Off({d: elab}) | _ => - switch (Evaluator.evaluate(env, elab)) { + switch (Evaluator.evaluate(env, {d: elab})) { | exception (EvaluatorError.Exception(reason)) => print_endline("EvaluatorError:" ++ EvaluatorError.show(reason)); ResultFail(EvaulatorError(reason)); @@ -66,17 +32,3 @@ let evaluate = | (state, result) => ResultOk({result, state}) } }; - -let eval_z = - ( - ~settings: CoreSettings.t, - ~ctx_init: Ctx.t, - ~env_init: Environment.t, - z: Zipper.t, - ) - : ProgramResult.t => { - let (term, _) = MakeTerm.from_zip_for_sem(z); - let info_map = Statics.mk_map_ctx(settings, ctx_init, term); - let d = elaborate(~settings, info_map, term); - evaluate(~settings, ~env=env_init, d); -}; diff --git a/src/haz3lcore/prog/ModelResult.re b/src/haz3lcore/prog/ModelResult.re index 5965cd1c52..e8c8980a60 100644 --- a/src/haz3lcore/prog/ModelResult.re +++ b/src/haz3lcore/prog/ModelResult.re @@ -1,6 +1,6 @@ [@deriving (show({with_path: false}), sexp, yojson)] type eval_result = { - elab: DHExp.t, + elab: Elaborator.Elaboration.t, evaluation: ProgramResult.t, previous: ProgramResult.t, }; @@ -11,7 +11,7 @@ type t = | Evaluation(eval_result) | Stepper(Stepper.t); -let init_eval = elab => +let init_eval = (elab: Elaborator.Elaboration.t) => Evaluation({elab, evaluation: ResultPending, previous: ResultPending}); let update_elab = (~settings, elab) => @@ -20,7 +20,7 @@ let update_elab = (~settings, elab) => Evaluation({elab, evaluation: ResultPending, previous: ResultPending}) | Evaluation({evaluation, _}) => Evaluation({elab, evaluation: ResultPending, previous: evaluation}) - | Stepper({elab: elab2, _}) as s when DHExp.fast_equal(elab, elab2) => s + | Stepper(s) as s' when DHExp.fast_equal(elab.d, Stepper.get_elab(s).d) => s' | Stepper(_) => Stepper(Stepper.init(~settings, elab)); let update_stepper = f => @@ -42,7 +42,7 @@ let run_pending = (~settings: CoreSettings.t) => Evaluation({ elab, previous, - evaluation: Interface.evaluate(~settings, elab), + evaluation: Interface.evaluate(~settings, elab.d), }) | Evaluation(_) as e => e | Stepper(s) => @@ -59,8 +59,12 @@ let toggle_stepper = (~settings) => fun | NoElab => NoElab | Evaluation({elab, _}) => Stepper(Stepper.init(~settings, elab)) - | Stepper({elab, _}) => - Evaluation({elab, evaluation: ResultPending, previous: ResultPending}); + | Stepper(s) => + Evaluation({ + elab: Stepper.get_elab(s), + evaluation: ResultPending, + previous: ResultPending, + }); let test_results = (result: t) => switch (result) { diff --git a/src/haz3lcore/prog/ModelResults.re b/src/haz3lcore/prog/ModelResults.re index cceeb3153d..a49d287d07 100644 --- a/src/haz3lcore/prog/ModelResults.re +++ b/src/haz3lcore/prog/ModelResults.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; /* ModelResults is used to store the results of @@ -19,7 +19,7 @@ include M; [@deriving (show({with_path: false}), sexp, yojson)] type t = M.t(ModelResult.t); -let init_eval = (ds: list((Key.t, DHExp.t))): t => +let init_eval = (ds: list((Key.t, Elaborator.Elaboration.t))): t => ds |> List.to_seq |> of_seq |> map(ModelResult.init_eval); let update_elabs = (~settings) => @@ -43,7 +43,7 @@ let run_pending = (~settings) => M.map(ModelResult.run_pending(~settings)); let timeout_all = map(ModelResult.timeout); let advance_evaluator_result = - (results: t, (key: Key.t, elab: DHExp.t)) + (results: t, (key: Key.t, elab: Elaborator.Elaboration.t)) : option((Key.t, ModelResult.t)) => switch (lookup(results, key)) { | Some(Stepper(_)) => None @@ -64,7 +64,8 @@ let stepper_result_opt = | _ => None }; -let to_evaluate = (results: t, elabs: list((Key.t, DHExp.t))): t => +let to_evaluate = + (results: t, elabs: list((Key.t, Elaborator.Elaboration.t))): t => elabs |> List.filter_map(advance_evaluator_result(results)) |> List.to_seq diff --git a/src/haz3lcore/prog/ProgramResult.re b/src/haz3lcore/prog/ProgramResult.re index a8e0eb4415..58e2e9082e 100644 --- a/src/haz3lcore/prog/ProgramResult.re +++ b/src/haz3lcore/prog/ProgramResult.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; /** The result of a program evaluation. Includes the {!type:EvaluatorResult.t}, @@ -7,7 +7,7 @@ open Sexplib.Std; */ [@deriving (show({with_path: false}), sexp, yojson)] type inner = { - result: EvaluatorResult.t, + result: Evaluator.Result.t, state: EvaluatorState.t, }; @@ -19,10 +19,10 @@ type error = [@deriving (show({with_path: false}), sexp, yojson)] type t = - | Off(DHExp.t) //elab + | Off(Elaborator.Elaboration.t) | ResultOk(inner) | ResultFail(error) | ResultPending; -let get_dhexp = (r: inner) => EvaluatorResult.unbox(r.result); +let get_dhexp = (r: inner) => Evaluator.Result.unbox(r.result); let get_state = (r: inner) => r.state; diff --git a/src/haz3lcore/statics/CoCtx.re b/src/haz3lcore/statics/CoCtx.re index f25981c622..3088ef4a28 100644 --- a/src/haz3lcore/statics/CoCtx.re +++ b/src/haz3lcore/statics/CoCtx.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; /* Co-contexts: @@ -63,8 +63,10 @@ let singleton = (name, id, expected_ty): t => [ let join: (Ctx.t, list(entry)) => Typ.t = (ctx, entries) => { let expected_tys = List.map(entry => entry.expected_ty, entries); - switch (Typ.join_all(~empty=Unknown(Internal), ctx, expected_tys)) { - | None => Unknown(Internal) + switch ( + Typ.join_all(~empty=Unknown(Internal) |> Typ.fresh, ctx, expected_tys) + ) { + | None => Unknown(Internal) |> Typ.fresh | Some(ty) => ty }; }; diff --git a/src/haz3lcore/statics/Constructor.re b/src/haz3lcore/statics/Constructor.re index 6515fd2f97..02e897a030 100644 --- a/src/haz3lcore/statics/Constructor.re +++ b/src/haz3lcore/statics/Constructor.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type t = string; diff --git a/src/haz3lcore/statics/ConstructorMap.re b/src/haz3lcore/statics/ConstructorMap.re index a350d16d92..bd4ac26195 100644 --- a/src/haz3lcore/statics/ConstructorMap.re +++ b/src/haz3lcore/statics/ConstructorMap.re @@ -1,108 +1,224 @@ open Util.OptUtil.Syntax; -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] -type binding('a) = (Constructor.t, 'a); +type variant('a) = + | Variant(Constructor.t, list(Id.t), option('a)) + | BadEntry('a); +// Invariant: Must not have duplicate constructors [@deriving (show({with_path: false}), sexp, yojson)] -type t('a) = list(binding('a)); - -let compare = compare; - -let empty: t('a) = []; - -let is_empty: t('a) => bool = - fun - | [] => true - | _ => false; - -let rec add = (ctr: Constructor.t, value: 'a, map: t('a)): t('a) => - switch (map) { - | [] => [(ctr, value)] - | [(ctr', value') as head, ...tail] => - if (Constructor.equal(ctr, ctr')) { - if (value === value') { - map; +type t('a) = list(variant('a)); + +let mk = + ( + ~mk_bad: (Constructor.t, list(Id.t), option('a)) => 'a, + with_duplicates: list(variant('a)), + ) + : t('a) => { + let rec go = (xs, seen: list(Constructor.t)) => { + switch (xs) { + | [] => [] + | [BadEntry(x), ...xs] => [BadEntry(x), ...go(xs, seen)] + | [Variant(ctr, ids, value), ...xs] => + if (List.mem(ctr, seen)) { + [BadEntry(mk_bad(ctr, ids, value)), ...go(xs, seen)]; } else { - [(ctr, value), ...tail]; - }; - } else { - [head, ...add(ctr, value, tail)]; - } + [Variant(ctr, ids, value), ...go(xs, List.cons(ctr, seen))]; + } + }; }; + go(with_duplicates, []); +}; -let singleton = (ctr: Constructor.t, value: 'a): t('a) => [(ctr, value)]; - -let compare_bindings = - ((ctr1, _): binding('a), (ctr2, _): binding('a)): int => - compare(ctr1, ctr2); - -/* compares ctrs only */ -let equal = (val_equal: ('a, 'a) => bool, map1: t('a), map2: t('a)): bool => { - let equal_bindings = - ( - val_equal: ('a, 'a) => bool, - (ctr1, val1): binding('a), - (ctr2, val2): binding('a), - ) - : bool => - Constructor.equal(ctr1, ctr2) && val_equal(val1, val2); - map1 === map2 - || { - let map1 = List.fast_sort(compare_bindings, map1); - let map2 = List.fast_sort(compare_bindings, map2); - List.equal(equal_bindings(val_equal), map1, map2); +let equal_constructor = + (eq: ('a, 'a) => bool, x: variant('a), y: variant('a)): bool => + switch (x, y) { + | (Variant(ctr1, _, Some(x1)), Variant(ctr2, _, Some(y1))) => + Constructor.equal(ctr1, ctr2) && eq(x1, y1) + | (Variant(ctr1, _, None), Variant(ctr2, _, None)) => + Constructor.equal(ctr1, ctr2) + | (BadEntry(x), BadEntry(y)) => eq(x, y) + | (Variant(_), Variant(_)) + | (BadEntry(_), Variant(_)) + | (Variant(_), BadEntry(_)) => false + }; + +let same_constructor = + (eq: ('a, 'a) => bool, x: variant('a), y: variant('a)): bool => + switch (x, y) { + | (Variant(ctr1, _, _), Variant(ctr2, _, _)) => + Constructor.equal(ctr1, ctr2) + | (BadEntry(x), BadEntry(y)) => eq(x, y) + | (BadEntry(_), Variant(_)) + | (Variant(_), BadEntry(_)) => false }; -}; -let cardinal: t('a) => int = List.length; +let has_bad_entry = (x: t('a)): bool => + List.exists( + fun + | BadEntry(_) => true + | Variant(_) => false, + x, + ); -let ctrs_of = (m: list((Constructor.t, 'a))): list(Constructor.t) => - List.map(fst, m); +let has_good_entry = (x: t('a)): bool => + List.exists( + fun + | BadEntry(_) => false + | Variant(_) => true, + x, + ); -let same_constructors_same_order = (map1: t('a), map2: t('a)): bool => - cardinal(map1) === cardinal(map2) - && List.for_all2(Constructor.equal, ctrs_of(map1), ctrs_of(map2)); +let free_variables = (f, m) => + m + |> List.map( + fun + | Variant(_, _, Some(value)) => f(value) + | _ => [], + ) + |> List.flatten; -let ctrs_equal = (map1: t('a), map2: t('a)): bool => { - let ctrs1 = ctrs_of(map1); - let ctrs2 = ctrs_of(map2); - ctrs1 === ctrs2 - || List.fast_sort(compare, ctrs1) == List.fast_sort(compare, ctrs2); +let is_ground = is_hole => + fun + | [BadEntry(x)] when is_hole(x) => true + | _ => false; + +/* computes all three regions of a venn diagram of two sets represented as lists */ +let venn_regions = + (f: ('a, 'a) => bool, xs: list('a), ys: list('a)) + : (list(('a, 'a)), list('a), list('a)) => { + let rec go = (xs, ys, acc, left, right) => + switch (xs) { + | [] => (acc |> List.rev, left |> List.rev, List.rev_append(right, ys)) + | [x, ...xs] => + switch (List.partition(f(x, _), ys)) { + | ([], _) => go(xs, ys, acc, [x, ...left], right) + | ([y], ys') => go(xs, ys', [(x, y), ...acc], left, right) + | _ => failwith("Sum type has non-unique constructors") + } + }; + go(xs, ys, [], [], []); }; -let for_all: (binding('a) => bool, t('a)) => bool = List.for_all; +let join_entry = + (join: ('a, 'a) => option('a), (x: variant('a), y: variant('a))) + : option(variant('a)) => + switch (x, y) { + | (Variant(ctr1, ids1, Some(value1)), Variant(ctr2, _, Some(value2))) + when Constructor.equal(ctr1, ctr2) => + let+ value = join(value1, value2); + Variant(ctr1, ids1, Some(value)); + | (Variant(ctr1, ids1, None), Variant(ctr2, _, None)) + when Constructor.equal(ctr1, ctr2) => + Some(Variant(ctr1, ids1, None)) + | (BadEntry(x), BadEntry(_)) => Some(BadEntry(x)) + | _ => None + }; -let bindings: t('a) => list(binding('a)) = x => x; +let join = + ( + eq: ('a, 'a) => bool, + join: ('a, 'a) => option('a), + m1: t('a), + m2: t('a), + ) + : option(t('a)) => { + let (inter, left, right) = venn_regions(same_constructor(eq), m1, m2); + let join_entries = List.filter_map(join_entry(join), inter); + if (List.length(join_entries) == List.length(inter)) { + switch ( + has_good_entry(left), + has_bad_entry(m1), + has_good_entry(right), + has_bad_entry(m2), + ) { + | (_, true, _, true) => Some(join_entries @ left @ right) + | (false, true, _, _) => Some(join_entries @ right) + | (_, _, false, true) => Some(join_entries @ left) + | _ when left == [] && right == [] => Some(join_entries) + | _ => None + }; + } else { + None; + }; +}; -let find_opt = (ctr: Constructor.t, map: t('a)): option('a) => { - let+ binding = List.find_opt(((k, _)) => Constructor.equal(ctr, k), map); - snd(binding); +let match_synswitch = + ( + match_synswitch: ('a, 'a) => 'a, + eq: ('a, 'a) => bool, + m1: t('a), + m2: t('a), + ) + : t('a) => { + let (inter, left, _) = venn_regions(same_constructor(eq), m1, m2); + let inter' = + List.map( + fun + | (Variant(ctr, ids, Some(value1)), Variant(_, _, Some(value2))) => + Variant(ctr, ids, Some(match_synswitch(value1, value2))) + | (v, _) => v, + inter, + ); + inter' @ left; }; -let map = (f: 'a => 'b, m: t('a)): t('b) => { - let (ctrs, vals) = List.split(m); - let vals = List.map(f, vals); - List.combine(ctrs, vals); +let equal = (eq: ('a, 'a) => bool, m1: t('a), m2: t('a)) => { + switch (venn_regions(same_constructor(eq), m1, m2)) { + | (inter, [], []) => + List.for_all( + ((x, y)) => + switch (x, y) { + | (Variant(_, _, Some(value1)), Variant(_, _, Some(value2))) => + eq(value1, value2) + | (Variant(_, _, None), Variant(_, _, None)) => true + | (BadEntry(x), BadEntry(y)) => eq(x, y) + | _ => false + }, + inter, + ) + | _ => false + }; }; -/* sorts on ctrs only */ -let sort = (map: t('a)): t('a) => { - List.fast_sort(compare_bindings, map); +let map = (f: option('a) => option('b), m: t('a)): t('b) => { + List.map( + fun + | Variant(ctr, args, value) => Variant(ctr, args, f(value)) + | BadEntry(value) => BadEntry(value), + m, + ); }; -let of_list: list(binding('a)) => t('a) = x => x; +let get_entry = (ctr, m) => + List.find_map( + fun + | Variant(ctr', _, value) when Constructor.equal(ctr, ctr') => value + | Variant(_) + | BadEntry(_) => None, + m, + ); -let rec is_ground = (is_ground_value: 'a => bool, map: t('a)): bool => - switch (map) { - | [] => true - | [(_, head), ...tail] => - is_ground_value(head) && tail |> is_ground(is_ground_value) - }; +let has_constructor_no_args = ctr => + List.exists( + fun + | Variant(ctr', _, None) when Constructor.equal(ctr, ctr') => true + | Variant(_) => false + | BadEntry(_) => false, + ); + +let get_constructors = + List.filter_map( + fun + | Variant(ctr, _, _) => Some(ctr) + | BadEntry(_) => None, + _, + ); let nth = (map: t('a), ctr: Constructor.t): option(int) => { // TODO: use List.find_index instead, which is available for OCaml 5.1 - let ctrs_sorted = map |> sort |> ctrs_of; + let ctrs_sorted = map |> get_constructors |> List.sort(String.compare); List.find_opt( nth => List.nth(ctrs_sorted, nth) == ctr, List.init(List.length(ctrs_sorted), Fun.id), diff --git a/src/haz3lcore/statics/Ctx.re b/src/haz3lcore/statics/Ctx.re index a7ddecd669..cfaf634304 100644 --- a/src/haz3lcore/statics/Ctx.re +++ b/src/haz3lcore/statics/Ctx.re @@ -1,4 +1,238 @@ -include TypBase.Ctx; +open Util; -/* Due to otherwise cyclic dependencies, Typ and Ctx - are jointly located in the TypBase module */ +[@deriving (show({with_path: false}), sexp, yojson)] +type kind = + | Singleton(TermBase.Typ.t) + | Abstract; + +[@deriving (show({with_path: false}), sexp, yojson)] +type var_entry = { + name: Var.t, + id: Id.t, + typ: TermBase.Typ.t, +}; + +[@deriving (show({with_path: false}), sexp, yojson)] +type tvar_entry = { + name: string, + id: Id.t, + kind, +}; + +[@deriving (show({with_path: false}), sexp, yojson)] +type entry = + | VarEntry(var_entry) + | ConstructorEntry(var_entry) + | TVarEntry(tvar_entry); + +[@deriving (show({with_path: false}), sexp, yojson)] +type t = list(entry); + +let extend = (ctx, entry) => List.cons(entry, ctx); + +let extend_tvar = (ctx: t, tvar_entry: tvar_entry): t => + extend(ctx, TVarEntry(tvar_entry)); + +let extend_alias = (ctx: t, name: string, id: Id.t, ty: TermBase.Typ.t): t => + extend_tvar(ctx, {name, id, kind: Singleton(ty)}); + +let extend_dummy_tvar = (ctx: t, tvar: TPat.t) => + switch (TPat.tyvar_of_utpat(tvar)) { + | Some(name) => extend_tvar(ctx, {kind: Abstract, name, id: Id.invalid}) + | None => ctx + }; + +let lookup_tvar = (ctx: t, name: string): option(kind) => + List.find_map( + fun + | TVarEntry(v) when v.name == name => Some(v.kind) + | _ => None, + ctx, + ); + +let lookup_tvar_id = (ctx: t, name: string): option(Id.t) => + List.find_map( + fun + | TVarEntry(v) when v.name == name => Some(v.id) + | _ => None, + ctx, + ); + +let get_id: entry => Id.t = + fun + | VarEntry({id, _}) + | ConstructorEntry({id, _}) + | TVarEntry({id, _}) => id; + +let lookup_var = (ctx: t, name: string): option(var_entry) => + List.find_map( + fun + | VarEntry(v) when v.name == name => Some(v) + | _ => None, + ctx, + ); + +let lookup_ctr = (ctx: t, name: string): option(var_entry) => + List.find_map( + fun + | ConstructorEntry(t) when t.name == name => Some(t) + | _ => None, + ctx, + ); + +let is_alias = (ctx: t, name: string): bool => + switch (lookup_tvar(ctx, name)) { + | Some(Singleton(_)) => true + | Some(Abstract) + | None => false + }; + +let is_abstract = (ctx: t, name: string): bool => + switch (lookup_tvar(ctx, name)) { + | Some(Abstract) => true + | Some(Singleton(_)) + | None => false + }; + +let lookup_alias = (ctx: t, name: string): option(TermBase.Typ.t) => + switch (lookup_tvar(ctx, name)) { + | Some(Singleton(ty)) => Some(ty) + | Some(Abstract) => None + | None => + Some(TermBase.Typ.Unknown(Hole(Invalid(name))) |> IdTagged.fresh) + }; + +let add_ctrs = (ctx: t, name: string, id: Id.t, ctrs: TermBase.Typ.sum_map): t => + List.filter_map( + fun + | ConstructorMap.Variant(ctr, _, typ) => + Some( + ConstructorEntry({ + name: ctr, + id, + typ: + switch (typ) { + | None => TermBase.Typ.Var(name) |> IdTagged.fresh + | Some(typ) => + TermBase.Typ.Arrow( + typ, + TermBase.Typ.Var(name) |> IdTagged.fresh, + ) + |> IdTagged.fresh + }, + }), + ) + | ConstructorMap.BadEntry(_) => None, + ctrs, + ) + @ ctx; + +let subtract_prefix = (ctx: t, prefix_ctx: t): option(t) => { + // NOTE: does not check that the prefix is an actual prefix + let prefix_length = List.length(prefix_ctx); + let ctx_length = List.length(ctx); + if (prefix_length > ctx_length) { + None; + } else { + Some( + List.rev( + ListUtil.sublist((prefix_length, ctx_length), List.rev(ctx)), + ), + ); + }; +}; + +let added_bindings = (ctx_after: t, ctx_before: t): t => { + /* Precondition: new_ctx is old_ctx plus some new bindings */ + let new_count = List.length(ctx_after) - List.length(ctx_before); + switch (ListUtil.split_n_opt(new_count, ctx_after)) { + | Some((ctx, _)) => ctx + | _ => [] + }; +}; + +module VarSet = Set.Make(Var); + +// Note: filter out duplicates when rendering +let filter_duplicates = (ctx: t): t => + ctx + |> List.fold_left( + ((ctx, term_set, typ_set), entry) => { + switch (entry) { + | VarEntry({name, _}) + | ConstructorEntry({name, _}) => + VarSet.mem(name, term_set) + ? (ctx, term_set, typ_set) + : ([entry, ...ctx], VarSet.add(name, term_set), typ_set) + | TVarEntry({name, _}) => + VarSet.mem(name, typ_set) + ? (ctx, term_set, typ_set) + : ([entry, ...ctx], term_set, VarSet.add(name, typ_set)) + } + }, + ([], VarSet.empty, VarSet.empty), + ) + |> (((ctx, _, _)) => List.rev(ctx)); + +let rec modulize_item = + (ctx: t, x: Token.t, ty: TermBase.Typ.t): TermBase.Typ.t => { + switch (ty) { + | Int => Int + | Float => Float + | Bool => Bool + | String => String + | Member(name, ty1) => Member(x ++ "." ++ name, ty1) + | Unknown(prov) => Unknown(prov) + | Arrow(ty1, ty2) => + Arrow(modulize_item(ctx, x, ty1), modulize_item(ctx, x, ty2)) + | Prod(tys) => Prod(List.map(modulize_item(ctx, x), tys)) + | Sum(sm) => + Sum(ConstructorMap.map(Option.map(modulize_item(ctx, x)), sm)) + | Rec(y, ty) => Rec(y, modulize_item(ctx, x, ty)) + | List(ty) => List(modulize_item(ctx, x, ty)) + | Var(n) => + x == n + ? Var(n) + : Member(x ++ "." ++ n, TermBase.Typ.weak_head_normalize(ctx, ty)) + | Module({inner_ctx, incomplete}) => + let ctx_entry_modulize = (e: entry): entry => { + switch (e) { + | VarEntry(t) => VarEntry({...t, typ: modulize_item(ctx, x, t.typ)}) + | ConstructorEntry(t) => + ConstructorEntry({...t, typ: modulize_item(ctx, x, t.typ)}) + | TVarEntry(_) => e + }; + }; + Module({inner_ctx: List.map(ctx_entry_modulize, inner_ctx), incomplete}); + | Forall(_, t) => modulize_item(ctx, x, t) + }; +}; + +let modulize = (ty: TermBase.Typ.t, x: string): TermBase.Typ.t => { + switch (ty) { + | Module({inner_ctx, incomplete}) => + Module({ + inner_ctx: + List.map( + (e: entry): entry => { + switch (e) { + | VarEntry(t) => + VarEntry({...t, typ: modulize_item(inner_ctx, x, t.typ)}) + | ConstructorEntry(t) => + ConstructorEntry({ + ...t, + typ: modulize_item(inner_ctx, x, t.typ), + }) + | TVarEntry(_) => e + } + }, + inner_ctx, + ), + incomplete, + }) + | _ => ty + }; +}; + +let shadows_typ = (ctx: t, name: string): bool => + Form.is_base_typ(name) || lookup_tvar(ctx, name) != None; diff --git a/src/haz3lcore/statics/Info.re b/src/haz3lcore/statics/Info.re index 2546ed519b..485dab2e5e 100644 --- a/src/haz3lcore/statics/Info.re +++ b/src/haz3lcore/statics/Info.re @@ -1,7 +1,5 @@ -open Sexplib.Std; open Util; open OptUtil.Syntax; -open Term; /* INFO.re @@ -147,7 +145,7 @@ type typ_expects = [@deriving (show({with_path: false}), sexp, yojson)] type error_typ = | BadToken(Token.t) /* Invalid token, treated as type hole */ - | FreeTypeVariable(TypVar.t) /* Free type variable */ + | FreeTypeVariable(string) /* Free type variable */ | DuplicateConstructor(Constructor.t) /* Duplicate ctr in same sum */ | WantTypeFoundAp | FreeTypeMember(Token.t) @@ -164,8 +162,8 @@ type error_typ = type ok_typ = | Variant(Constructor.t, Typ.t) | VariantIncomplete(Typ.t) - | TypeAlias(TypVar.t, Typ.t) | Module(Constructor.t, Ctx.t) + | TypeAlias(string, Typ.t) | Type(Typ.t); [@deriving (show({with_path: false}), sexp, yojson)] @@ -188,14 +186,14 @@ type shadow_src = /* Type pattern term errors */ [@deriving (show({with_path: false}), sexp, yojson)] type error_tpat = - | ShadowsType(TypVar.t, shadow_src) + | ShadowsType(string, shadow_src) | NotAVar(type_var_err); /* Type pattern ok statuses for cursor inspector */ [@deriving (show({with_path: false}), sexp, yojson)] type ok_tpat = | Empty - | Var(TypVar.t); + | Var(string); [@deriving (show({with_path: false}), sexp, yojson)] type status_tpat = @@ -210,7 +208,7 @@ type exp = { mode: Mode.t, /* Parental type expectations */ self: Self.exp, /* Expectation-independent type info */ co_ctx: CoCtx.t, /* Locally free variables */ - cls: Term.Cls.t, /* DERIVED: Syntax class (i.e. form name) */ + cls: Cls.t, /* DERIVED: Syntax class (i.e. form name) */ status: status_exp, /* DERIVED: Ok/Error statuses for display */ ty: Typ.t /* DERIVED: Type after nonempty hole fixing */ }; @@ -221,9 +219,10 @@ type pat = { ancestors, ctx: Ctx.t, co_ctx: CoCtx.t, + prev_synswitch: option(Typ.t), // If a pattern is first synthesized, then analysed, the initial syn is stored here. mode: Mode.t, self: Self.pat, - cls: Term.Cls.t, + cls: Cls.t, status: status_pat, ty: Typ.t, constraint_: Constraint.t, @@ -231,28 +230,27 @@ type pat = { [@deriving (show({with_path: false}), sexp, yojson)] type typ = { - term: UTyp.t, + term: Typ.t, ancestors, ctx: Ctx.t, expects: typ_expects, - cls: Term.Cls.t, + cls: Cls.t, status: status_typ, - ty: Typ.t, }; [@deriving (show({with_path: false}), sexp, yojson)] type tpat = { - term: UTPat.t, + term: TPat.t, ancestors, ctx: Ctx.t, - cls: Term.Cls.t, + cls: Cls.t, status: status_tpat, }; [@deriving (show({with_path: false}), sexp, yojson)] type secondary = { id: Id.t, // Id of term static info is sourced from - cls: Term.Cls.t, // Cls of secondary, not source term + cls: Cls.t, // Cls of secondary, not source term sort: Sort.t, // from source term ctx: Ctx.t // from source term }; @@ -307,10 +305,10 @@ let ancestors_of: t => ancestors = let id_of: t => Id.t = fun - | InfoExp(i) => Term.UExp.rep_id(i.term) - | InfoPat(i) => Term.UPat.rep_id(i.term) - | InfoTyp(i) => Term.UTyp.rep_id(i.term) - | InfoTPat(i) => Term.UTPat.rep_id(i.term) + | InfoExp(i) => Exp.rep_id(i.term) + | InfoPat(i) => Pat.rep_id(i.term) + | InfoTyp(i) => Typ.rep_id(i.term) + | InfoTPat(i) => TPat.rep_id(i.term) | Secondary(s) => s.id; let error_of: t => option(error) = @@ -337,13 +335,25 @@ let rec status_common = | (Just(ty), Syn) => NotInHole(Syn(ty)) | (Just(ty), SynFun) => switch ( - Typ.join_fix(ctx, Arrow(Unknown(Internal), Unknown(Internal)), ty) + Typ.join_fix( + ctx, + Arrow(Unknown(Internal) |> Typ.temp, Unknown(Internal) |> Typ.temp) + |> Typ.temp, + ty, + ) ) { | Some(_) => NotInHole(Syn(ty)) | None => InHole(Inconsistent(WithArrow(ty))) } | (Just(ty), SynTypFun) => - switch (Typ.join_fix(ctx, Forall("?", Unknown(Internal)), ty)) { + switch ( + Typ.join_fix( + ctx, + Forall(Var("?") |> TPat.fresh, Unknown(Internal) |> Typ.temp) + |> Typ.temp, + ty, + ) + ) { | Some(_) => NotInHole(Syn(ty)) | None => InHole(Inconsistent(WithArrow(ty))) } @@ -370,9 +380,9 @@ let rec status_common = } | (BadToken(name), _) => InHole(NoType(BadToken(name))) | (BadTrivAp(ty), _) => InHole(NoType(BadTrivAp(ty))) - | (IsMulti, _) => NotInHole(Syn(Unknown(Internal))) + | (IsMulti, _) => NotInHole(Syn(Unknown(Internal) |> Typ.temp)) | (NoJoin(wrap, tys), Ana(ana)) => - let syn: Typ.t = Self.join_of(wrap, Unknown(Internal)); + let syn: Typ.t = Self.join_of(wrap, Unknown(Internal) |> Typ.temp); switch (Typ.join_fix(ctx, ana, syn)) { | None => InHole(Inconsistent(Expectation({ana, syn}))) | Some(_) => @@ -455,14 +465,11 @@ let rec status_exp = (ctx: Ctx.t, mode: Mode.t, self: Self.exp): status_exp => separate sort. It also determines semantic properties such as whether or not a type variable reference is free, and whether a ctr name is a dupe. */ -let status_typ = - (ctx: Ctx.t, expects: typ_expects, term: TermBase.UTyp.t, ty: Typ.t) - : status_typ => - switch (term.term) { - | Invalid(token) => InHole(BadToken(token)) - | EmptyHole => NotInHole(Type(ty)) - | Var(name) - | Constructor(name) => +let status_typ = (ctx: Ctx.t, expects: typ_expects, ty: Typ.t): status_typ => + switch (ty.term) { + | Unknown(Hole(Invalid(token))) => InHole(BadToken(token)) + | Unknown(Hole(EmptyHole)) => NotInHole(Type(ty)) + | Var(name) => switch (expects) { | VariantExpected(Unique, sum_ty) | ConstructorExpected(Unique, sum_ty) => @@ -481,21 +488,21 @@ let status_typ = | false => switch (Ctx.is_abstract(ctx, name)) { | false => InHole(FreeTypeVariable(name)) - | true => NotInHole(Type(Var(name))) + | true => NotInHole(Type(Var(name) |> Typ.temp)) } | true => NotInHole(TypeAlias(name, Typ.weak_head_normalize(ctx, ty))) } | AnaTypeExpected(ana) => InHole(InconsistentMember({ana, syn: ty})) } - | Ap(t1, t2) => + | Ap(t1, ty_in) => switch (expects) { | VariantExpected(status_variant, ty_variant) => - let ty_in = UTyp.to_typ(ctx, t2); switch (status_variant, t1.term) { | (Unique, Var(name) | Constructor(name)) => - NotInHole(Variant(name, Arrow(ty_in, ty_variant))) - | _ => NotInHole(VariantIncomplete(Arrow(ty_in, ty_variant))) - }; + NotInHole(Variant(name, Arrow(ty_in, ty_variant) |> Typ.temp)) + | _ => + NotInHole(VariantIncomplete(Arrow(ty_in, ty_variant) |> Typ.temp)) + } | ModuleExpected => InHole(WantModule) | ConstructorExpected(_) => InHole(WantConstructorFoundAp) | TypeExpected => InHole(WantTypeFoundAp) @@ -524,7 +531,7 @@ let status_typ = } }; -let status_tpat = (ctx: Ctx.t, utpat: UTPat.t): status_tpat => +let status_tpat = (ctx: Ctx.t, utpat: TPat.t): status_tpat => switch (utpat.term) { | EmptyHole => NotInHole(Empty) | Var(name) when Ctx.shadows_typ(ctx, name) => @@ -554,8 +561,8 @@ let is_error = (ci: t): bool => { | InHole(_) => true | NotInHole(_) => false } - | InfoTyp({expects, ctx, term, ty, _}) => - switch (status_typ(ctx, expects, term, ty)) { + | InfoTyp({expects, ctx, term, _}) => + switch (status_typ(ctx, expects, term)) { | InHole(_) => true | NotInHole(_) => false } @@ -569,7 +576,7 @@ let is_error = (ci: t): bool => { }; /* Determined the type of an expression or pattern 'after hole fixing'; - that is, all ill-typed terms are considered to be 'wrapped in + that is, some ill-typed terms are considered to be 'wrapped in non-empty holes', i.e. assigned Unknown type. */ let fixed_typ_ok: ok_pat => Typ.t = fun @@ -577,6 +584,29 @@ let fixed_typ_ok: ok_pat => Typ.t = | Ana(Consistent({join, _})) => join | Ana(InternallyInconsistent({ana, _})) => ana; +let fixed_typ_err_common: error_common => Typ.t = + fun + | NoType(_) => Unknown(Internal) |> Typ.temp + | Inconsistent(Expectation({ana, _})) => ana + | Inconsistent(Internal(_)) => Unknown(Internal) |> Typ.temp // Should this be some sort of meet? + | Inconsistent(WithArrow(_)) => + Arrow(Unknown(Internal) |> Typ.temp, Unknown(Internal) |> Typ.temp) + |> Typ.temp; + +let fixed_typ_err: error_exp => Typ.t = + fun + | FreeVariable(_) => Unknown(Internal) |> Typ.temp + | UnusedDeferral => Unknown(Internal) |> Typ.temp + | BadPartialAp(_) => Unknown(Internal) |> Typ.temp + | InexhaustiveMatch(_) => Unknown(Internal) |> Typ.temp + | Common(err) => fixed_typ_err_common(err); + +let fixed_typ_err_pat: error_pat => Typ.t = + fun + | ExpectedConstructor => Unknown(Internal) |> Typ.temp + | Redundant(_) => Unknown(Internal) |> Typ.temp + | Common(err) => fixed_typ_err_common(err); + let fixed_typ_pat = (ctx, mode: Mode.t, self: Self.pat): Typ.t => { // TODO: get rid of unwrapping (probably by changing the implementation of error_exp.Redundant) let self = @@ -585,7 +615,7 @@ let fixed_typ_pat = (ctx, mode: Mode.t, self: Self.pat): Typ.t => { | _ => self }; switch (status_pat(ctx, mode, self)) { - | InHole(_) => Unknown(Internal) + | InHole(err) => fixed_typ_err_pat(err) | NotInHole(ok) => fixed_typ_ok(ok) }; }; @@ -600,9 +630,9 @@ let fixed_constraint_pat = ) : Constraint.t => switch (upat.term) { - | TypeAnn(_) => constraint_ + | Cast(_) => constraint_ | _ => - switch (fixed_typ_pat(ctx, mode, self)) { + switch (fixed_typ_pat(ctx, mode, self) |> Typ.term_of) { | Unknown(_) => Constraint.Hole | _ => constraint_ } @@ -610,7 +640,7 @@ let fixed_constraint_pat = let fixed_typ_exp = (ctx, mode: Mode.t, self: Self.exp): Typ.t => switch (status_exp(ctx, mode, self)) { - | InHole(_) => Unknown(Internal) + | InHole(err) => fixed_typ_err(err) | NotInHole(AnaDeferralConsistent(ana)) => ana | NotInHole(Common(ok)) => fixed_typ_ok(ok) }; @@ -635,10 +665,11 @@ let derived_pat = ~upat: UPat.t, ~ctx, ~co_ctx, + ~is_module, + ~prev_synswitch, ~mode, ~ancestors, ~self, - ~is_module, ~constraint_, ) : pat => { @@ -654,6 +685,7 @@ let derived_pat = { cls, self, + prev_synswitch, mode, ty, status, @@ -670,18 +702,18 @@ let derived_typ = (~utyp: UTyp.t, ~ctx, ~ancestors, ~expects): typ => { let cls: Cls.t = /* Hack to improve CI display */ switch (expects, UTyp.cls_of_term(utyp.term)) { - | (VariantExpected(_), Var) => Cls.Typ(Constructor) | (ModuleExpected, Var) => Cls.Typ(ModuleVar) + | (VariantExpected(_) | ConstructorExpected(_), Var) => + Cls.Typ(Constructor) | (_, cls) => Cls.Typ(cls) }; - let ty = UTyp.to_typ(ctx, utyp); - let status = status_typ(ctx, expects, utyp, ty); - {cls, ctx, ancestors, status, expects, ty, term: utyp}; + let status = status_typ(ctx, expects, utyp); + {cls, ctx, ancestors, status, expects, term: utyp}; }; /* Add derivable attributes for type patterns */ -let derived_tpat = (~utpat: UTPat.t, ~ctx, ~ancestors): tpat => { - let cls = Cls.TPat(UTPat.cls_of_term(utpat.term)); +let derived_tpat = (~utpat: TPat.t, ~ctx, ~ancestors): tpat => { + let cls = Cls.TPat(TPat.cls_of_term(utpat.term)); let status = status_tpat(ctx, utpat); {cls, ancestors, status, ctx, term: utpat}; }; @@ -693,13 +725,18 @@ let get_binding_site = (info: t): option(Id.t) => { | InfoExp({term: {term: Var(name), _}, ctx, _}) => let+ entry = Ctx.lookup_var(ctx, name); entry.id; - | InfoExp({term: {term: Constructor(name), _}, ctx, _}) - | InfoPat({term: {term: Constructor(name), _}, ctx, _}) => + | InfoExp({term: {term: Constructor(name, _), _}, ctx, _}) + | InfoPat({term: {term: Constructor(name, _), _}, ctx, _}) => let+ entry = Ctx.lookup_ctr(ctx, name); entry.id; | InfoTyp({term: {term: Var(name), _}, ctx, _}) => - let+ entry = Ctx.lookup_tvar(ctx, name); - entry.id; + Ctx.lookup_tvar_id(ctx, name) | _ => None }; }; + +let typ_is_constructor_expected = t => + switch (t) { + | {expects: ConstructorExpected(_) | VariantExpected(_), _} => true + | _ => false + }; diff --git a/src/haz3lcore/statics/Kind.re b/src/haz3lcore/statics/Kind.re deleted file mode 100644 index 8db5638e94..0000000000 --- a/src/haz3lcore/statics/Kind.re +++ /dev/null @@ -1 +0,0 @@ -include TypBase.Kind; diff --git a/src/haz3lcore/statics/MakeTerm.re b/src/haz3lcore/statics/MakeTerm.re index b5b080a10a..0738e3f9fd 100644 --- a/src/haz3lcore/statics/MakeTerm.re +++ b/src/haz3lcore/statics/MakeTerm.re @@ -11,7 +11,7 @@ */ open Util; -open Term; +open Any; // TODO make less hacky let tokens = @@ -19,6 +19,7 @@ let tokens = _ => [], _ => [" "], (t: Tile.t) => t.shards |> List.map(List.nth(t.label)), + _ => [], ); [@deriving (show({with_path: false}), sexp, yojson)] @@ -34,8 +35,14 @@ type unsorted = | Post(t, tiles) | Bin(t, tiles, t); +type t = { + term: UExp.t, + terms: TermMap.t, + projectors: Id.Map.t(Piece.projector), +}; + let is_nary = - (is_sort: any => option('sort), delim: Token.t, (delims, kids): tiles) + (is_sort: Any.t => option('sort), delim: Token.t, (delims, kids): tiles) : option(list('sort)) => if (delims |> List.map(snd) |> List.for_all((==)(([delim], [])))) { kids |> List.map(is_sort) |> OptUtil.sequence; @@ -43,10 +50,10 @@ let is_nary = None; }; -let is_tuple_exp = is_nary(TermBase.Any.is_exp, ","); -let is_tuple_pat = is_nary(TermBase.Any.is_pat, ","); -let is_tuple_typ = is_nary(TermBase.Any.is_typ, ","); -let is_typ_bsum = is_nary(TermBase.Any.is_typ, "+"); +let is_tuple_exp = is_nary(Any.is_exp, ","); +let is_tuple_pat = is_nary(Any.is_pat, ","); +let is_tuple_typ = is_nary(Any.is_typ, ","); +let is_typ_bsum = is_nary(Any.is_typ, "+"); let is_grout = tiles => Aba.get_as(tiles) |> List.map(snd) |> List.for_all((==)(([" "], []))); @@ -57,7 +64,7 @@ let is_rules = ((ts, kids): tiles): option(Aba.t(UPat.t, UExp.t)) => { ts |> List.map( fun - | (_, (["|", "=>"], [Pat(p)])) => Some(p) + | (_, (["|", "=>"], [Any.Pat(p)])) => Some(p) | _ => None, ) |> OptUtil.sequence @@ -102,14 +109,37 @@ let return = (wrap, ids, tm) => { tm; }; -let parse_sum_term: UTyp.t => UTyp.variant = +/* Map to collect projector ids */ +let projectors: ref(Id.Map.t(Piece.projector)) = ref(Id.Map.empty); + +/* Strip a projector from a segment and log it in the map */ +let rm_and_log_projectors = (seg: Segment.t): Segment.t => + List.map( + fun + | Piece.Projector(pr) => { + projectors := Id.Map.add(pr.id, pr, projectors^); + pr.syntax; + } + | x => x, + seg, + ); + +let parse_sum_term: UTyp.t => ConstructorMap.variant(UTyp.t) = fun - | {term: Var(ctr), ids} => Variant(ctr, ids, None) - | {term: Ap({term: Var(ctr), ids: ids_ctr}, u), ids: ids_ap} => + | {term: Var(ctr), ids, _} => Variant(ctr, ids, None) + | {term: Ap({term: Var(ctr), ids: ids_ctr, _}, u), ids: ids_ap, _} => Variant(ctr, ids_ctr @ ids_ap, Some(u)) | t => BadEntry(t); -let rec go_s = (s: Sort.t, skel: Skel.t, seg: Segment.t): any => +let mk_bad = (ctr, ids, value) => { + let t: Typ.t = {ids, copied: false, term: Var(ctr)}; + switch (value) { + | None => t + | Some(u) => Ap(t, u) |> Typ.fresh + }; +}; + +let rec go_s = (s: Sort.t, skel: Skel.t, seg: Segment.t): Term.Any.t => switch (s) { | Pat => Pat(pat(unsorted(skel, seg))) | TPat => TPat(tpat(unsorted(skel, seg))) @@ -138,35 +168,37 @@ let rec go_s = (s: Sort.t, skel: Skel.t, seg: Segment.t): any => and exp = unsorted => { let (term, inner_ids) = exp_term(unsorted); let ids = ids(unsorted) @ inner_ids; - return(e => Exp(e), ids, {ids, term}); + return(e => Exp(e), ids, {ids, copied: false, term}); } and exp_term: unsorted => (UExp.term, list(Id.t)) = { let ret = (tm: UExp.term) => (tm, []); - let hole = unsorted => Term.UExp.hole(kids_of_unsorted(unsorted)); + let hole = unsorted => UExp.hole(kids_of_unsorted(unsorted)); fun | Op(tiles) as tm => switch (tiles) { // single-tile case | ([(_id, t)], []) => switch (t) { - | ([t], []) when Form.is_empty_tuple(t) => ret(Triv) + | ([t], []) when Form.is_empty_tuple(t) => ret(Tuple([])) | ([t], []) when Form.is_wild(t) => ret(Deferral(OutsideAp)) | ([t], []) when Form.is_empty_list(t) => ret(ListLit([])) | ([t], []) when Form.is_bool(t) => ret(Bool(bool_of_string(t))) + | ([t], []) when Form.is_undefined(t) => ret(Undefined) | ([t], []) when Form.is_int(t) => ret(Int(int_of_string(t))) | ([t], []) when Form.is_string(t) => ret(String(Form.strip_quotes(t))) | ([t], []) when Form.is_float(t) => ret(Float(float_of_string(t))) | ([t], []) when Form.is_var(t) => ret(Var(t)) - | ([t], []) when Form.is_ctr(t) => ret(Constructor(t)) + | ([t], []) when Form.is_ctr(t) => + ret(Constructor(t, Unknown(Internal) |> Typ.temp)) | (["(", ")"], [Exp(body)]) => ret(Parens(body)) | (["[", "]"], [Exp(body)]) => switch (body) { - | {ids, term: Tuple(es)} => (ListLit(es), ids) + | {ids, copied: false, term: Tuple(es)} => (ListLit(es), ids) | term => ret(ListLit([term])) } | (["test", "end"], [Exp(test)]) => ret(Test(test)) - | (["case", "end"], [Rul({ids, term: Rules(scrut, rules)})]) => ( + | (["case", "end"], [Rul({ids, term: Rules(scrut, rules), _})]) => ( Match(scrut, rules), ids, ) @@ -184,17 +216,18 @@ and exp_term: unsorted => (UExp.term, list(Id.t)) = { | (["$"], []) => UnOp(Meta(Unquote), r) | (["-"], []) => UnOp(Int(Minus), r) | (["!"], []) => UnOp(Bool(Not), r) - | (["fun", "->"], [Pat(pat)]) => Fun(pat, r) - | (["typfun", "->"], [TPat(tpat)]) => TypFun(tpat, r) + | (["fun", "->"], [Pat(pat)]) => Fun(pat, r, None, None) + | (["fix", "->"], [Pat(pat)]) => FixF(pat, r, None) + | (["typfun", "->"], [TPat(tpat)]) => TypFun(tpat, r, None) | (["let", "=", "in"], [Pat(pat), Exp(def)]) => Let(pat, def, r) | (["hide", "in"], [Exp(filter)]) => - Filter((Eval, One), filter, r) + Filter(Filter({act: (Eval, One), pat: filter}), r) | (["eval", "in"], [Exp(filter)]) => - Filter((Eval, All), filter, r) + Filter(Filter({act: (Eval, All), pat: filter}), r) | (["pause", "in"], [Exp(filter)]) => - Filter((Step, One), filter, r) + Filter(Filter({act: (Step, One), pat: filter}), r) | (["debug", "in"], [Exp(filter)]) => - Filter((Step, All), filter, r) + Filter(Filter({act: (Step, All), pat: filter}), r) | (["type", "=", "in"], [TPat(tpat), Typ(def)]) => TyAlias(tpat, def, r) | (["if", "then", "else"], [Exp(cond), Exp(conseq)]) => @@ -211,10 +244,17 @@ and exp_term: unsorted => (UExp.term, list(Id.t)) = { | ([(_id, t)], []) => switch (t) { | (["()"], []) => - ret(Ap(l, {ids: [Id.nullary_ap_flag], term: Triv})) + ret( + Ap( + Forward, + l, + {ids: [Id.nullary_ap_flag], copied: false, term: Tuple([])}, + ), + ) | (["(", ")"], [Exp(arg)]) => let use_deferral = (arg: UExp.t): UExp.t => { ids: arg.ids, + copied: false, term: Deferral(InAp), }; switch (arg.term) { @@ -230,7 +270,7 @@ and exp_term: unsorted => (UExp.term, list(Id.t)) = { ), arg.ids, ) - | _ => ret(Ap(l, arg)) + | _ => ret(Ap(Forward, l, arg)) }; | (["@<", ">"], [Typ(ty)]) => ret(TypAp(l, ty)) | _ => ret(hole(tm)) @@ -274,7 +314,7 @@ and exp_term: unsorted => (UExp.term, list(Id.t)) = { | (["++"], []) => BinOp(String(Concat), l, r) | (["$=="], []) => BinOp(String(Equals), l, r) | (["."], []) => Dot(l, r) - | (["|>"], []) => Pipeline(l, r) + | (["|>"], []) => Ap(Reverse, r, l) | (["@"], []) => ListConcat(l, r) | _ => hole(tm) }, @@ -287,29 +327,27 @@ and exp_term: unsorted => (UExp.term, list(Id.t)) = { and pat = unsorted => { let (term, inner_ids) = pat_term(unsorted); let ids = ids(unsorted) @ inner_ids; - return(p => Pat(p), ids, {ids, term}); + return(p => Pat(p), ids, {ids, term, copied: false}); } and pat_term: unsorted => (UPat.term, list(Id.t)) = { let ret = (term: UPat.term) => (term, []); - let hole = unsorted => Term.UPat.hole(kids_of_unsorted(unsorted)); + let hole = unsorted => UPat.hole(kids_of_unsorted(unsorted)); fun | Op(tiles) as tm => switch (tiles) { | ([(_id, tile)], []) => ret( switch (tile) { - | ([t], []) when Form.is_empty_tuple(t) => Triv + | ([t], []) when Form.is_empty_tuple(t) => Tuple([]) | ([t], []) when Form.is_empty_list(t) => ListLit([]) | ([t], []) when Form.is_bool(t) => Bool(bool_of_string(t)) | ([t], []) when Form.is_float(t) => Float(float_of_string(t)) | ([t], []) when Form.is_int(t) => Int(int_of_string(t)) - | ([t], []) when Form.is_string(t) => - let s = Re.Str.string_after(t, 1); - let s = Re.Str.string_before(s, String.length(s) - 1); - String(s); + | ([t], []) when Form.is_string(t) => String(Form.strip_quotes(t)) | ([t], []) when Form.is_var(t) => Var(t) | ([t], []) when Form.is_wild(t) => Wild - | ([t], []) when Form.is_ctr(t) => Constructor(t) + | ([t], []) when Form.is_ctr(t) => + Constructor(t, Unknown(Internal) |> Typ.fresh) | ([t], []) when t != " " && !Form.is_explicit_hole(t) => Invalid(t) | (["(", ")"], [Pat(body)]) => Parens(body) @@ -348,7 +386,8 @@ and pat_term: unsorted => (UPat.term, list(Id.t)) = { | Pre(_) as tm => ret(hole(tm)) | Bin(Pat(p), tiles, Typ(ty)) as tm => switch (tiles) { - | ([(_id, ([":"], []))], []) => ret(TypeAnn(p, ty)) + | ([(_id, ([":"], []))], []) => + ret(Cast(p, ty, Unknown(Internal) |> Typ.fresh)) | _ => ret(hole(tm)) } | Bin(Pat(l), tiles, Pat(r)) as tm => @@ -365,18 +404,18 @@ and pat_term: unsorted => (UPat.term, list(Id.t)) = { and typ = unsorted => { let (term, inner_ids) = typ_term(unsorted); let ids = ids(unsorted) @ inner_ids; - return(ty => Typ(ty), ids, {ids, term}); + return(ty => Typ(ty), ids, {ids, term, copied: false}); } and typ_term: unsorted => (UTyp.term, list(Id.t)) = { let ret = (term: UTyp.term) => (term, []); - let hole = unsorted => Term.UTyp.hole(kids_of_unsorted(unsorted)); + let hole = unsorted => UTyp.hole(kids_of_unsorted(unsorted)); fun | Op(tiles) as tm => switch (tiles) { | ([(_id, tile)], []) => ret( switch (tile) { - | ([t], []) when Form.is_empty_tuple(t) => Tuple([]) + | ([t], []) when Form.is_empty_tuple(t) => Prod([]) | (["Bool"], []) => Bool | (["Int"], []) => Int | (["Float"], []) => Float @@ -386,7 +425,7 @@ and typ_term: unsorted => (UTyp.term, list(Id.t)) = { | (["[", "]"], [Typ(body)]) => List(body) | (["{", "}"], [Pat(body)]) => Module(body) | ([t], []) when t != " " && !Form.is_explicit_hole(t) => - Invalid(t) + Unknown(Hole(Invalid(t))) | _ => hole(tm) }, ) @@ -404,7 +443,7 @@ and typ_term: unsorted => (UTyp.term, list(Id.t)) = { ret(Forall(tpat, t)) | Pre(([(_id, (["rec", "->"], [TPat(tpat)]))], []), Typ(t)) => ret(Rec(tpat, t)) - | Pre(tiles, Typ({term: Sum(t0), ids})) as tm => + | Pre(tiles, Typ({term: Sum(t0), ids, _})) as tm => /* Case for leading prefix + preceeding a sum */ switch (tiles) { | ([(_, (["+"], []))], []) => (Sum(t0), ids) @@ -412,18 +451,24 @@ and typ_term: unsorted => (UTyp.term, list(Id.t)) = { } | Pre(tiles, Typ(t)) as tm => switch (tiles) { - | ([(_, (["+"], []))], []) => ret(Sum([parse_sum_term(t)])) + | ([(_, (["+"], []))], []) => + ret(Sum([parse_sum_term(t)] |> ConstructorMap.mk(~mk_bad))) | _ => ret(hole(tm)) } | Bin(Typ(t1), tiles, Typ(t2)) as tm when is_typ_bsum(tiles) != None => switch (is_typ_bsum(tiles)) { | Some(between_kids) => - ret(Sum(List.map(parse_sum_term, [t1] @ between_kids @ [t2]))) + ret( + Sum( + List.map(parse_sum_term, [t1] @ between_kids @ [t2]) + |> ConstructorMap.mk(~mk_bad), + ), + ) | None => ret(hole(tm)) } | Bin(Typ(l), tiles, Typ(r)) as tm => switch (is_tuple_typ(tiles)) { - | Some(between_kids) => ret(Tuple([l] @ between_kids @ [r])) + | Some(between_kids) => ret(Prod([l] @ between_kids @ [r])) | None => switch (tiles) { | ([(_id, (["->"], []))], []) => ret(Arrow(l, r)) @@ -436,11 +481,11 @@ and typ_term: unsorted => (UTyp.term, list(Id.t)) = { and tpat = unsorted => { let term = tpat_term(unsorted); let ids = ids(unsorted); - return(ty => TPat(ty), ids, {ids, term}); + return(ty => TPat(ty), ids, {ids, term, copied: false}); } -and tpat_term: unsorted => UTPat.term = { - let ret = (term: UTPat.term) => term; - let hole = unsorted => Term.UTPat.hole(kids_of_unsorted(unsorted)); +and tpat_term: unsorted => TPat.term = { + let ret = (term: TPat.term) => term; + let hole = unsorted => TPat.hole(kids_of_unsorted(unsorted)); fun | Op(tiles) as tm => switch (tiles) { @@ -464,8 +509,8 @@ and tpat_term: unsorted => UTPat.term = { // let ids = ids(unsorted); // return(r => Rul(r), ids, {ids, term}); // } -and rul = (unsorted: unsorted): URul.t => { - let hole = Term.URul.Hole(kids_of_unsorted(unsorted)); +and rul = (unsorted: unsorted): Rul.t => { + let hole = Rul.Hole(kids_of_unsorted(unsorted)); switch (exp(unsorted)) { | {term: MultiHole(_), _} => switch (unsorted) { @@ -475,20 +520,25 @@ and rul = (unsorted: unsorted): URul.t => { ids: ids(unsorted), term: Rules(scrut, List.combine(ps, leading_clauses @ [last_clause])), + copied: false, } - | None => {ids: ids(unsorted), term: hole} + | None => {ids: ids(unsorted), term: hole, copied: false} } - | _ => {ids: ids(unsorted), term: hole} + | _ => {ids: ids(unsorted), term: hole, copied: false} } - | e => {ids: [], term: Rules(e, [])} + | e => {ids: [], term: Rules(e, []), copied: false} }; } and unsorted = (skel: Skel.t, seg: Segment.t): unsorted => { - let tile_kids = (p: Piece.t): list(any) => + /* Remove projectors. We do this here as opposed to removing + * them in an external call to save a whole-syntax pass. */ + let seg = rm_and_log_projectors(seg); + let tile_kids = (p: Piece.t): list(Term.Any.t) => switch (p) { | Secondary(_) | Grout(_) => [] + | Projector(_) => [] | Tile({mold, shards, children, _}) => Aba.aba_triples(Aba.mk(shards, children)) |> List.map(((l, kid, r)) => { @@ -536,24 +586,20 @@ let go = ~cache_size_bound=1000, seg => { map := TermMap.empty; - let e = exp(unsorted(Segment.skel(seg), seg)); - (e, map^); + projectors := Id.Map.empty; + let term = exp(unsorted(Segment.skel(seg), seg)); + {term, terms: map^, projectors: projectors^}; }, ); -let from_zip = (~dump_backpack: bool, ~erase_buffer: bool, z: Zipper.t) => { +let from_zip_for_sem = + (~dump_backpack: bool, ~erase_buffer: bool, z: Zipper.t) => { let seg = Zipper.smart_seg(~dump_backpack, ~erase_buffer, z); go(seg); }; -let from_zip_for_view = - Core.Memo.general( - ~cache_size_bound=1000, - from_zip(~dump_backpack=false, ~erase_buffer=true), - ); - let from_zip_for_sem = Core.Memo.general( ~cache_size_bound=1000, - from_zip(~dump_backpack=true, ~erase_buffer=true), + from_zip_for_sem(~dump_backpack=true, ~erase_buffer=true), ); diff --git a/src/haz3lcore/statics/Mode.re b/src/haz3lcore/statics/Mode.re index ad53e30f00..26d68a8177 100644 --- a/src/haz3lcore/statics/Mode.re +++ b/src/haz3lcore/statics/Mode.re @@ -30,9 +30,13 @@ let ana: Typ.t => t = ty => Ana(ty); let ty_of: t => Typ.t = fun | Ana(ty) => ty - | Syn => Unknown(SynSwitch) - | SynFun => Arrow(Unknown(SynSwitch), Unknown(SynSwitch)) - | SynTypFun => Forall("syntypfun", Unknown(SynSwitch)); /* TODO: naming the type variable? */ + | Syn => Unknown(SynSwitch) |> Typ.temp + | SynFun => + Arrow(Unknown(SynSwitch) |> Typ.temp, Unknown(SynSwitch) |> Typ.temp) + |> Typ.temp + | SynTypFun => + Forall(Var("syntypfun") |> TPat.fresh, Unknown(SynSwitch) |> Typ.temp) + |> Typ.temp; /* TODO: naming the type variable? */ let of_arrow = (ctx: Ctx.t, mode: t): (t, t) => switch (mode) { @@ -42,7 +46,7 @@ let of_arrow = (ctx: Ctx.t, mode: t): (t, t) => | Ana(ty) => ty |> Typ.matched_arrow(ctx) |> TupleUtil.map2(ana) }; -let of_forall = (ctx: Ctx.t, name_opt: option(TypVar.t), mode: t): t => +let of_forall = (ctx: Ctx.t, name_opt: option(string), mode: t): t => switch (mode) { | Syn | SynFun @@ -51,7 +55,7 @@ let of_forall = (ctx: Ctx.t, name_opt: option(TypVar.t), mode: t): t => let (name_expected_opt, item) = Typ.matched_forall(ctx, ty); switch (name_opt, name_expected_opt) { | (Some(name), Some(name_expected)) => - Ana(Typ.subst(Var(name), name_expected, item)) + Ana(Typ.subst(Var(name) |> Typ.temp, name_expected, item)) | _ => Ana(item) }; }; @@ -76,8 +80,8 @@ let of_cons_tl = (ctx: Ctx.t, mode: t, hd_ty: Typ.t): t => switch (mode) { | Syn | SynFun - | SynTypFun => Ana(List(hd_ty)) - | Ana(ty) => Ana(List(Typ.matched_list(ctx, ty))) + | SynTypFun => Ana(List(hd_ty) |> Typ.temp) + | Ana(ty) => Ana(List(Typ.matched_list(ctx, ty)) |> Typ.temp) }; let of_list = (ctx: Ctx.t, mode: t): t => @@ -92,8 +96,8 @@ let of_list_concat = (ctx: Ctx.t, mode: t): t => switch (mode) { | Syn | SynFun - | SynTypFun => Ana(List(Unknown(SynSwitch))) - | Ana(ty) => Ana(List(Typ.matched_list(ctx, ty))) + | SynTypFun => Ana(List(Unknown(SynSwitch) |> Typ.temp) |> Typ.temp) + | Ana(ty) => Ana(List(Typ.matched_list(ctx, ty)) |> Typ.temp) }; let of_list_lit = (ctx: Ctx.t, length, mode: t): list(t) => @@ -104,13 +108,13 @@ let ctr_ana_typ = (ctx: Ctx.t, mode: t, ctr: Constructor.t): option(Typ.t) => { a sum type having that ctr as a variant, we consider the ctr's type to be determined by the sum type */ switch (mode) { - | Ana(Arrow(_, ty_ana)) + | Ana({term: Arrow(_, ty_ana), _}) | Ana(ty_ana) => - let* ctrs = Typ.get_sum_constructors(ctx, ty_ana); - let+ (_, ty_entry) = Typ.sum_entry(ctr, ctrs); + let+ ctrs = Typ.get_sum_constructors(ctx, ty_ana); + let ty_entry = ConstructorMap.get_entry(ctr, ctrs); switch (ty_entry) { | None => ty_ana - | Some(ty_in) => Arrow(ty_in, ty_ana) + | Some(ty_in) => Arrow(ty_in, ty_ana) |> Typ.temp }; | _ => None }; @@ -118,14 +122,14 @@ let ctr_ana_typ = (ctx: Ctx.t, mode: t, ctr: Constructor.t): option(Typ.t) => { let of_ctr_in_ap = (ctx: Ctx.t, mode: t, ctr: Constructor.t): option(t) => switch (ctr_ana_typ(ctx, mode, ctr)) { - | Some(Arrow(_) as ty_ana) => Some(Ana(ty_ana)) + | Some({term: Arrow(_), _} as ty_ana) => Some(Ana(ty_ana)) | Some(ty_ana) => /* Consider for example "let _ : +Yo = Yo("lol") in..." Here, the 'Yo' constructor should be in a hole, as it is nullary but used as unary; we reflect this by analyzing against an arrow type. Since we can't guess at what the parameter type might have be, we use Unknown. */ - Some(Ana(Arrow(Unknown(Internal), ty_ana))) + Some(Ana(Arrow(Unknown(Internal) |> Typ.temp, ty_ana) |> Typ.temp)) | None => None }; @@ -161,6 +165,6 @@ let typap_mode: t = SynTypFun; let of_deferred_ap_args = (length: int, ty_ins: list(Typ.t)): list(t) => ( List.length(ty_ins) == length - ? ty_ins : List.init(length, _ => Typ.Unknown(Internal)) + ? ty_ins : List.init(length, _ => Typ.Unknown(Internal) |> Typ.temp) ) |> List.map(ty => Ana(ty)); diff --git a/src/haz3lcore/statics/Self.re b/src/haz3lcore/statics/Self.re index 052bf581ef..cece7d2b0b 100644 --- a/src/haz3lcore/statics/Self.re +++ b/src/haz3lcore/statics/Self.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; /* SELF.re @@ -50,7 +50,7 @@ type error_partial_ap = type exp = | Free(Var.t) | InexhaustiveMatch(exp) - | IsDeferral(Term.UExp.deferral_position) + | IsDeferral(Exp.deferral_position) | IsBadPartialAp(error_partial_ap) | Common(t); @@ -62,7 +62,7 @@ type pat = let join_of = (j: join_type, ty: Typ.t): Typ.t => switch (j) { | Id => ty - | List => List(ty) + | List => List(ty) |> Typ.fresh }; /* What the type would be if the position had been @@ -119,22 +119,24 @@ let of_deferred_ap = (args, ty_ins: list(Typ.t), ty_out: Typ.t): exp => { let actual = List.length(args); if (expected != actual) { IsBadPartialAp(ArityMismatch({expected, actual})); - } else if (List.for_all(Term.UExp.is_deferral, args)) { + } else if (List.for_all(Exp.is_deferral, args)) { IsBadPartialAp(NoDeferredArgs); } else { let ty_ins = List.combine(args, ty_ins) - |> List.filter(((arg, _ty)) => Term.UExp.is_deferral(arg)) + |> List.filter(((arg, _ty)) => Exp.is_deferral(arg)) |> List.map(snd); - let ty_in = List.length(ty_ins) == 1 ? List.hd(ty_ins) : Prod(ty_ins); - Common(Just(Arrow(ty_in, ty_out))); + let ty_in = + List.length(ty_ins) == 1 + ? List.hd(ty_ins) : Prod(ty_ins) |> Typ.fresh; + Common(Just(Arrow(ty_in, ty_out) |> Typ.fresh)); }; }; let add_source = List.map2((id, ty) => Typ.{id, ty}); let match = (ctx: Ctx.t, tys: list(Typ.t), ids: list(Id.t)): t => - switch (Typ.join_all(~empty=Unknown(Internal), ctx, tys)) { + switch (Typ.join_all(~empty=Unknown(Internal) |> Typ.fresh, ctx, tys)) { | None => NoJoin(Id, add_source(ids, tys)) | Some(ty) => Just(ty) }; @@ -142,11 +144,11 @@ let match = (ctx: Ctx.t, tys: list(Typ.t), ids: list(Id.t)): t => let listlit = (~empty, ctx: Ctx.t, tys: list(Typ.t), ids: list(Id.t)): t => switch (Typ.join_all(~empty, ctx, tys)) { | None => NoJoin(List, add_source(ids, tys)) - | Some(ty) => Just(List(ty)) + | Some(ty) => Just(List(ty) |> Typ.fresh) }; let list_concat = (ctx: Ctx.t, tys: list(Typ.t), ids: list(Id.t)): t => - switch (Typ.join_all(~empty=Unknown(Internal), ctx, tys)) { + switch (Typ.join_all(~empty=Unknown(Internal) |> Typ.fresh, ctx, tys)) { | None => NoJoin(List, add_source(ids, tys)) | Some(ty) => Just(ty) }; diff --git a/src/haz3lcore/statics/Statics.re b/src/haz3lcore/statics/Statics.re index 68b30bfaf5..4caa6d7c3f 100644 --- a/src/haz3lcore/statics/Statics.re +++ b/src/haz3lcore/statics/Statics.re @@ -1,5 +1,3 @@ -open Term; - /* STATICS.re This module determines the statics semantics of a program. @@ -36,22 +34,12 @@ module Map = { [@deriving (show({with_path: false}), sexp, yojson)] type t = Id.Map.t(Info.t); - let error_ids = (term_ranges: TermRanges.t, info_map: t): list(Id.t) => + let error_ids = (info_map: t): list(Id.t) => Id.Map.fold( (id, info, acc) => - /* Because of artefacts in Maketerm ID handling, - * there are be situations where ids appear in the - * info_map which do not occur in term_ranges. These - * ids should be purely duplicative, so skipping them - * when iterating over the info_map should have no - * effect, beyond supressing the resulting Not_found exs */ - switch (Id.Map.find_opt(id, term_ranges)) { - | Some(_) when Info.is_error(info) && id == Info.id_of(info) => [ - id, - ...acc, - ] - | _ => acc - }, + /* Second clause is to eliminate non-representative ids, + * which will not be found in the measurements map */ + Info.is_error(info) && id == Info.id_of(info) ? [id, ...acc] : acc, info_map, [], ); @@ -68,7 +56,7 @@ let add_info = (ids: list(Id.t), info: Info.t, m: Map.t): Map.t => ids |> List.fold_left((m, id) => Id.Map.add(id, info, m), m); let rec is_arrow_like = (t: Typ.t) => { - switch (t) { + switch (t |> Typ.term_of) { | Unknown(_) => true | Arrow(_) => true | Forall(_, t) => is_arrow_like(t) @@ -77,57 +65,69 @@ let rec is_arrow_like = (t: Typ.t) => { }; let is_recursive = (ctx, p, def, syn: Typ.t) => { - switch (Term.UPat.get_num_of_vars(p), Term.UExp.get_num_of_functions(def)) { + switch (Pat.get_num_of_vars(p), Exp.get_num_of_functions(def)) { | (Some(num_vars), Some(num_fns)) when num_vars != 0 && num_vars == num_fns => - switch (Typ.normalize(ctx, syn)) { + let norm = Typ.normalize(ctx, syn); + switch (norm |> Typ.term_of) { | Prod(syns) when List.length(syns) == num_vars => syns |> List.for_all(is_arrow_like) - | t when is_arrow_like(t) => num_vars == 1 + | _ when is_arrow_like(norm) => num_vars == 1 | _ => false - } + }; | _ => false }; }; -let typ_exp_binop_bin_int: UExp.op_bin_int => Typ.t = +let typ_exp_binop_bin_int: Operators.op_bin_int => Typ.t = fun - | (Plus | Minus | Times | Power | Divide) as _op => Int + | (Plus | Minus | Times | Power | Divide) as _op => Int |> Typ.temp | ( LessThan | GreaterThan | LessThanOrEqual | GreaterThanOrEqual | Equals | NotEquals ) as _op => - Bool; + Bool |> Typ.temp; -let typ_exp_binop_bin_float: UExp.op_bin_float => Typ.t = +let typ_exp_binop_bin_float: Operators.op_bin_float => Typ.t = fun - | (Plus | Minus | Times | Power | Divide) as _op => Float + | (Plus | Minus | Times | Power | Divide) as _op => Float |> Typ.temp | ( LessThan | GreaterThan | LessThanOrEqual | GreaterThanOrEqual | Equals | NotEquals ) as _op => - Bool; + Bool |> Typ.temp; -let typ_exp_binop_bin_string: UExp.op_bin_string => Typ.t = +let typ_exp_binop_bin_string: Operators.op_bin_string => Typ.t = fun - | Concat => String - | Equals => Bool; + | Concat => String |> Typ.temp + | Equals => Bool |> Typ.temp; -let typ_exp_binop: UExp.op_bin => (Typ.t, Typ.t, Typ.t) = +let typ_exp_binop: Operators.op_bin => (Typ.t, Typ.t, Typ.t) = fun - | Bool(And | Or) => (Bool, Bool, Bool) - | Int(op) => (Int, Int, typ_exp_binop_bin_int(op)) - | Float(op) => (Float, Float, typ_exp_binop_bin_float(op)) - | String(op) => (String, String, typ_exp_binop_bin_string(op)); + | Bool(And | Or) => (Bool |> Typ.temp, Bool |> Typ.temp, Bool |> Typ.temp) + | Int(op) => (Int |> Typ.temp, Int |> Typ.temp, typ_exp_binop_bin_int(op)) + | Float(op) => ( + Float |> Typ.temp, + Float |> Typ.temp, + typ_exp_binop_bin_float(op), + ) + | String(op) => ( + String |> Typ.temp, + String |> Typ.temp, + typ_exp_binop_bin_string(op), + ); -let typ_exp_unop: UExp.op_un => (Typ.t, Typ.t) = +let typ_exp_unop: Operators.op_un => (Typ.t, Typ.t) = fun - | Meta(Unquote) => (Var("$Meta"), Unknown(Free("$Meta"))) - | Bool(Not) => (Bool, Bool) - | Int(Minus) => (Int, Int); + | Meta(Unquote) => ( + Var("$Meta") |> Typ.temp, + Unknown(Internal) |> Typ.temp, + ) + | Bool(Not) => (Bool |> Typ.temp, Bool |> Typ.temp) + | Int(Minus) => (Int |> Typ.temp, Int |> Typ.temp); let rec any_to_info_map = - (~ctx: Ctx.t, ~ancestors, any: any, m: Map.t): (CoCtx.t, Map.t) => + (~ctx: Ctx.t, ~ancestors, any: Any.t, m: Map.t): (CoCtx.t, Map.t) => switch (any) { | Exp(e) => let ({co_ctx, _}: Info.exp, m) = @@ -172,14 +172,14 @@ and uexp_to_info_map = ~mode=Mode.Syn, ~is_in_filter=false, ~ancestors, - {ids, term} as uexp: UExp.t, + {ids, copied: _, term} as uexp: UExp.t, m: Map.t, ) : (Info.exp, Map.t) => { /* Maybe switch mode to syn */ let mode = switch (mode) { - | Ana(Unknown(SynSwitch)) => Mode.Syn + | Ana({term: Unknown(SynSwitch), _}) => Mode.Syn | _ => mode }; let add' = (~self, ~co_ctx, m) => { @@ -212,25 +212,34 @@ and uexp_to_info_map = let go_module = uexp_to_module(~ancestors); let atomic = self => add(~self, ~co_ctx=CoCtx.empty, m); switch (term) { + | Closure(_) => + failwith( + "TODO: implement closure type checking - see how dynamic type assignment does it", + ) | MultiHole(tms) => let (co_ctxs, m) = multi(~ctx, ~ancestors, m, tms); add(~self=IsMulti, ~co_ctx=CoCtx.union(co_ctxs), m); + | Cast(e, t1, t2) + | FailedCast(e, t1, t2) => + let (e, m) = go(~mode=Ana(t1), e, m); + add(~self=Just(t2), ~co_ctx=e.co_ctx, m); | Invalid(token) => atomic(BadToken(token)) - | EmptyHole => atomic(Just(Unknown(Internal))) - | Triv => atomic(Just(Prod([]))) + | EmptyHole => atomic(Just(Unknown(Internal) |> Typ.temp)) | Deferral(position) => add'(~self=IsDeferral(position), ~co_ctx=CoCtx.empty, m) - | Bool(_) => atomic(Just(Bool)) - | Int(_) => atomic(Just(Int)) - | Float(_) => atomic(Just(Float)) - | String(_) => atomic(Just(String)) + | Undefined => atomic(Just(Unknown(Hole(EmptyHole)) |> Typ.temp)) + | Bool(_) => atomic(Just(Bool |> Typ.temp)) + | Int(_) => atomic(Just(Int |> Typ.temp)) + | Float(_) => atomic(Just(Float |> Typ.temp)) + | String(_) => atomic(Just(String |> Typ.temp)) | ListLit(es) => let ids = List.map(UExp.rep_id, es); let modes = Mode.of_list_lit(ctx, List.length(es), mode); let (es, m) = map_m_go(m, modes, es); let tys = List.map(Info.exp_ty, es); add( - ~self=Self.listlit(~empty=Unknown(Internal), ctx, tys, ids), + ~self= + Self.listlit(~empty=Unknown(Internal) |> Typ.temp, ctx, tys, ids), ~co_ctx=CoCtx.union(List.map(Info.exp_co_ctx, es)), m, ); @@ -238,13 +247,13 @@ and uexp_to_info_map = let (hd, m) = go(~mode=Mode.of_cons_hd(ctx, mode), hd, m); let (tl, m) = go(~mode=Mode.of_cons_tl(ctx, mode, hd.ty), tl, m); add( - ~self=Just(List(hd.ty)), + ~self=Just(List(hd.ty) |> Typ.temp), ~co_ctx=CoCtx.union([hd.co_ctx, tl.co_ctx]), m, ); | ListConcat(e1, e2) => let mode = Mode.of_list_concat(ctx, mode); - let ids = List.map(Term.UExp.rep_id, [e1, e2]); + let ids = List.map(UExp.rep_id, [e1, e2]); let (e1, m) = go(~mode, e1, m); let (e2, m) = go(~mode, e2, m); add( @@ -258,21 +267,23 @@ and uexp_to_info_map = ~co_ctx=CoCtx.singleton(name, UExp.rep_id(uexp), Mode.ty_of(mode)), m, ) + | DynamicErrorHole(e, _) | Parens(e) => let (e, m) = go(~mode, e, m); add(~self=Just(e.ty), ~co_ctx=e.co_ctx, m); | UnOp(Meta(Unquote), e) when is_in_filter => let e: UExp.t = { ids: e.ids, + copied: false, term: switch (e.term) { - | Var("e") => UExp.Constructor("$e") - | Var("v") => UExp.Constructor("$v") + | Var("e") => UExp.Constructor("$e", Unknown(Internal) |> Typ.temp) + | Var("v") => UExp.Constructor("$v", Unknown(Internal) |> Typ.temp) | _ => e.term }, }; - let ty_in = Typ.Var("$Meta"); - let ty_out = Typ.Unknown(Internal); + let ty_in = Typ.Var("$Meta") |> Typ.temp; + let ty_out = Typ.Unknown(Internal) |> Typ.temp; let (e, m) = go(~mode=Ana(ty_in), e, m); add(~self=Just(ty_out), ~co_ctx=e.co_ctx, m); | UnOp(op, e) => @@ -284,18 +295,24 @@ and uexp_to_info_map = let (e1, m) = go(~mode=Ana(ty1), e1, m); let (e2, m) = go(~mode=Ana(ty2), e2, m); add(~self=Just(ty_out), ~co_ctx=CoCtx.union([e1.co_ctx, e2.co_ctx]), m); + | BuiltinFun(string) => + add'( + ~self=Self.of_exp_var(Builtins.ctx_init, string), + ~co_ctx=CoCtx.empty, + m, + ) | Tuple(es) => let modes = Mode.of_prod(ctx, mode, List.length(es)); let (es, m) = map_m_go(m, modes, es); add( - ~self=Just(Prod(List.map(Info.exp_ty, es))), + ~self=Just(Prod(List.map(Info.exp_ty, es)) |> Typ.temp), ~co_ctx=CoCtx.union(List.map(Info.exp_co_ctx, es)), m, ); | Test(e) => - let (e, m) = go(~mode=Ana(Bool), e, m); - add(~self=Just(Prod([])), ~co_ctx=e.co_ctx, m); - | Filter(_, cond, body) => + let (e, m) = go(~mode=Ana(Bool |> Typ.temp), e, m); + add(~self=Just(Prod([]) |> Typ.temp), ~co_ctx=e.co_ctx, m); + | Filter(Filter({pat: cond, _}), body) => let (cond, m) = go(~mode=Syn, cond, m, ~is_in_filter=true); let (body, m) = go(~mode, body, m); add( @@ -303,6 +320,9 @@ and uexp_to_info_map = ~co_ctx=CoCtx.union([cond.co_ctx, body.co_ctx]), m, ); + | Filter(Residue(_), body) => + let (body, m) = go(~mode, body, m); + add(~self=Just(body.ty), ~co_ctx=CoCtx.union([body.co_ctx]), m); | Seq(e1, e2) => let (e1, m) = go(~mode=Syn, e1, m); let (e2, m) = go(~mode, e2, m); @@ -325,15 +345,14 @@ and uexp_to_info_map = | IsBadPartialAp(_) | InexhaustiveMatch(_) => atomic(Self.of_ctr(ctx, ctr)) }; - | Ap(fn, arg) - | Pipeline(arg, fn) => + | Ap(_, fn, arg) => let fn_mode = Mode.of_ap(ctx, mode, UExp.ctr_name(fn)); let (fn, m) = go(~mode=fn_mode, fn, m); let (ty_in, ty_out) = Typ.matched_arrow(ctx, fn.ty); let (arg, m) = go(~mode=Ana(ty_in), arg, m); let self: Self.t = Id.is_nullary_ap_flag(arg.term.ids) - && !Typ.is_consistent(ctx, ty_in, Prod([])) + && !Typ.is_consistent(ctx, ty_in, Prod([]) |> Typ.temp) ? BadTrivAp(ty_in) : Just(ty_out); add(~self, ~co_ctx=CoCtx.union([fn.co_ctx, arg.co_ctx]), m); | TypAp(fn, utyp) => @@ -341,10 +360,9 @@ and uexp_to_info_map = let (fn, m) = go(~mode=typfn_mode, fn, m); let (_, m) = utyp_to_info_map(~ctx, ~ancestors, utyp, m); let (option_name, ty_body) = Typ.matched_forall(ctx, fn.ty); - let ty = Term.UTyp.to_typ(ctx, utyp); switch (option_name) { | Some(name) => - add(~self=Just(Typ.subst(ty, name, ty_body)), ~co_ctx=fn.co_ctx, m) + add(~self=Just(Typ.subst(utyp, name, ty_body)), ~co_ctx=fn.co_ctx, m) | None => add(~self=Just(ty_body), ~co_ctx=fn.co_ctx, m) /* invalid name matches with no free type variables. */ }; | DeferredAp(fn, args) => @@ -358,7 +376,7 @@ and uexp_to_info_map = let (args, m) = map_m_go(m, modes, args); let arg_co_ctx = CoCtx.union(List.map(Info.exp_co_ctx, args)); add'(~self, ~co_ctx=CoCtx.union([fn.co_ctx, arg_co_ctx]), m); - | Fun(p, e) => + | Fun(p, e, _, _) => let (mode_pat, mode_body) = Mode.of_arrow(ctx, mode); let (p', _) = go_pat(~is_synswitch=false, ~co_ctx=CoCtx.empty, ~mode=mode_pat, p, m); @@ -367,27 +385,33 @@ and uexp_to_info_map = let (p, m) = go_pat(~is_synswitch=false, ~co_ctx=e.co_ctx, ~mode=mode_pat, p, m); // TODO: factor out code - let unwrapped_self: Self.exp = Common(Just(Arrow(p.ty, e.ty))); + let unwrapped_self: Self.exp = + Common(Just(Arrow(p.ty, e.ty) |> Typ.temp)); let is_exhaustive = p |> Info.pat_constraint |> Incon.is_exhaustive; let self = is_exhaustive ? unwrapped_self : InexhaustiveMatch(unwrapped_self); add'(~self, ~co_ctx=CoCtx.mk(ctx, p.ctx, e.co_ctx), m); - | TypFun({term: Var(name), _} as utpat, body) + | TypFun({term: Var(name), _} as utpat, body, _) when !Ctx.shadows_typ(ctx, name) => let mode_body = Mode.of_forall(ctx, Some(name), mode); let m = utpat_to_info_map(~ctx, ~ancestors, utpat, m) |> snd; let ctx_body = - Ctx.extend_tvar( - ctx, - {name, id: Term.UTPat.rep_id(utpat), kind: Abstract}, - ); + Ctx.extend_tvar(ctx, {name, id: TPat.rep_id(utpat), kind: Abstract}); let (body, m) = go'(~ctx=ctx_body, ~mode=mode_body, body, m); - add(~self=Just(Forall(name, body.ty)), ~co_ctx=body.co_ctx, m); - | TypFun(utpat, body) => + add( + ~self=Just(Forall(utpat, body.ty) |> Typ.temp), + ~co_ctx=body.co_ctx, + m, + ); + | TypFun(utpat, body, _) => let mode_body = Mode.of_forall(ctx, None, mode); let m = utpat_to_info_map(~ctx, ~ancestors, utpat, m) |> snd; let (body, m) = go(~mode=mode_body, body, m); - add(~self=Just(Forall("?", body.ty)), ~co_ctx=body.co_ctx, m); + add( + ~self=Just(Forall(utpat, body.ty) |> Typ.temp), + ~co_ctx=body.co_ctx, + m, + ); | Let(p, def, body) => let (p_syn, _) = go_pat(~is_synswitch=true, ~co_ctx=CoCtx.empty, ~mode=Syn, p, m); @@ -420,16 +444,20 @@ and uexp_to_info_map = let def_ctx = p_ana'.ctx; let (def_base2, _) = go'(~ctx=def_ctx, ~mode=Ana(p_syn.ty), def, m); let ana_ty_fn = ((ty_fn1, ty_fn2), ty_p) => { - ty_p == Typ.Unknown(SynSwitch) && !Typ.eq(ty_fn1, ty_fn2) + Typ.term_of(ty_p) == Typ.Unknown(SynSwitch) + && !Typ.eq(ty_fn1, ty_fn2) ? ty_fn1 : ty_p; }; let ana = - switch ((def_base.ty, def_base2.ty), p_syn.ty) { + switch ( + (def_base.ty |> Typ.term_of, def_base2.ty |> Typ.term_of), + p_syn.ty |> Typ.term_of, + ) { | ((Prod(ty_fns1), Prod(ty_fns2)), Prod(ty_ps)) => let tys = List.map2(ana_ty_fn, List.combine(ty_fns1, ty_fns2), ty_ps); - Typ.Prod(tys); - | ((ty_fn1, ty_fn2), ty_p) => ana_ty_fn((ty_fn1, ty_fn2), ty_p) + Typ.Prod(tys) |> Typ.temp; + | ((_, _), _) => ana_ty_fn((def_base.ty, def_base2.ty), p_syn.ty) }; let (def, m) = go'(~ctx=def_ctx, ~mode=Ana(ana), def, m); (def, def_ctx, m, ty_p_ana); @@ -455,9 +483,20 @@ and uexp_to_info_map = CoCtx.union([def.co_ctx, CoCtx.mk(ctx, p_ana.ctx, body.co_ctx)]), m, ); + | FixF(p, e, _) => + let (p', _) = + go_pat(~is_synswitch=false, ~co_ctx=CoCtx.empty, ~mode, p, m); + let (e', m) = go'(~ctx=p'.ctx, ~mode=Ana(p'.ty), e, m); + let (p'', m) = + go_pat(~is_synswitch=false, ~co_ctx=e'.co_ctx, ~mode, p, m); + add( + ~self=Just(p'.ty), + ~co_ctx=CoCtx.union([CoCtx.mk(ctx, p''.ctx, e'.co_ctx)]), + m, + ); | If(e0, e1, e2) => let branch_ids = List.map(UExp.rep_id, [e1, e2]); - let (cond, m) = go(~mode=Ana(Bool), e0, m); + let (cond, m) = go(~mode=Ana(Bool |> Typ.temp), e0, m); let (cons, m) = go(~mode, e1, m); let (alt, m) = go(~mode, e2, m); add( @@ -595,13 +634,13 @@ and uexp_to_info_map = let unwrapped_self: Self.exp = Common(Self.match(ctx, e_tys, branch_ids)); let constraint_ty = - switch (scrut.ty) { + switch (scrut.ty.term) { | Unknown(_) => map_m(go_pat(~is_synswitch=false, ~co_ctx=CoCtx.empty), ps, m) |> fst |> List.map(Info.pat_ty) - |> Typ.join_all(~empty=Unknown(Internal), ctx) - | ty => Some(ty) + |> Typ.join_all(~empty=Unknown(Internal) |> Typ.temp, ctx) + | _ => Some(scrut.ty) }; let (self, m) = switch (constraint_ty) { @@ -638,6 +677,7 @@ and uexp_to_info_map = ~co_ctx=p.co_ctx, ~mode=p.mode, ~ancestors=p.ancestors, + ~prev_synswitch=None, ~self, ~is_module=false, // Mark patterns as redundant at the top level @@ -690,20 +730,21 @@ and uexp_to_info_map = tentatively add an abtract type to the ctx, representing the speculative rec parameter. */ let (ty_def, ctx_def, ctx_body) = { - let ty_pre = UTyp.to_typ(Ctx.extend_dummy_tvar(ctx, name), utyp); switch (utyp.term) { - | Sum(_) when List.mem(name, Typ.free_vars(ty_pre)) => + | Sum(_) when List.mem(name, Typ.free_vars(utyp)) => /* NOTE: When debugging type system issues it may be beneficial to use a different name than the alias for the recursive parameter */ //let ty_rec = Typ.Rec("α", Typ.subst(Var("α"), name, ty_pre)); - let ty_rec = Typ.Rec(name, ty_pre); + let ty_rec = + Typ.Rec(TPat.Var(name) |> IdTagged.fresh, utyp) |> Typ.temp; let ctx_def = - Ctx.extend_alias(ctx, name, UTPat.rep_id(typat), ty_rec); + Ctx.extend_alias(ctx, name, TPat.rep_id(typat), ty_rec); (ty_rec, ctx_def, ctx_def); - | _ => - let ty = UTyp.to_typ(ctx, utyp); - (ty, ctx, Ctx.extend_alias(ctx, name, UTPat.rep_id(typat), ty)); - }; + | _ => ( + utyp, + ctx, + Ctx.extend_alias(ctx, name, TPat.rep_id(typat), utyp), + ) /* NOTE(yuchen): Below is an alternative implementation that attempts to add a rec whenever type alias is present. It may cause trouble to the runtime, so precede with caution. */ @@ -717,6 +758,7 @@ and uexp_to_info_map = // let ty = Term.UTyp.to_typ(ctx, utyp); // (ty, ctx, Ctx.add_alias(ctx, name, utpat_id(typat), ty)); // }; + }; }; let ctx_body = switch (Typ.get_sum_constructors(ctx, ty_def)) { @@ -726,7 +768,7 @@ and uexp_to_info_map = let ({co_ctx, ty: ty_body, _}: Info.exp, m) = go'(~ctx=ctx_body, ~mode, body, m); /* Make sure types don't escape their scope */ - let ty_escape = Typ.subst(ty_def, name, ty_body); + let ty_escape = Typ.subst(ty_def, typat, ty_body); let m = utyp_to_info_map(~ctx=ctx_def, ~ancestors, utyp, m) |> snd; add(~self=Just(ty_escape), ~co_ctx, m); | Var(_) @@ -748,13 +790,21 @@ and upat_to_info_map = ~ancestors: Info.ancestors, ~mode: Mode.t=Mode.Syn, ~is_module=false, - {ids, term} as upat: UPat.t, + {ids, term, _} as upat: UPat.t, m: Map.t, ) : (Info.pat, Map.t) => { let add = (~self, ~ctx, ~constraint_, m) => { + let prev_synswitch = + switch (Id.Map.find_opt(Pat.rep_id(upat), m)) { + | Some(Info.InfoPat({mode: Syn | SynFun, ty, _})) => Some(ty) + | Some(Info.InfoPat({mode: Ana(_), prev_synswitch, _})) => prev_synswitch + | Some(_) + | None => None + }; let info = Info.derived_pat( + ~prev_synswitch, ~upat, ~ctx, ~co_ctx, @@ -769,7 +819,7 @@ and upat_to_info_map = let atomic = (self, constraint_) => add(~self, ~ctx, ~constraint_, m); let ancestors = [UPat.rep_id(upat)] @ ancestors; let go = upat_to_info_map(~is_synswitch, ~ancestors, ~co_ctx, ~is_module); - let unknown = Typ.Unknown(is_synswitch ? SynSwitch : Internal); + let unknown = Typ.Unknown(is_synswitch ? SynSwitch : Internal) |> Typ.temp; let ctx_fold = (ctx: Ctx.t, m) => List.fold_left2( ((ctx, tys, cons, m), e, mode) => @@ -791,17 +841,19 @@ and upat_to_info_map = add(~self=IsMulti, ~ctx, ~constraint_=Constraint.Hole, m); | Invalid(token) => hole(BadToken(token)) | EmptyHole => hole(Just(unknown)) - | Int(int) => atomic(Just(Int), Constraint.Int(int)) - | Float(float) => atomic(Just(Float), Constraint.Float(float)) - | Triv => atomic(Just(Prod([])), Constraint.Truth) + | Int(int) => atomic(Just(Int |> Typ.temp), Constraint.Int(int)) + | Float(float) => + atomic(Just(Float |> Typ.temp), Constraint.Float(float)) + | Tuple([]) => atomic(Just(Prod([]) |> Typ.temp), Constraint.Truth) | Bool(bool) => atomic( - Just(Bool), + Just(Bool |> Typ.temp), bool ? Constraint.InjL(Constraint.Truth) : Constraint.InjR(Constraint.Truth), ) - | String(string) => atomic(Just(String), Constraint.String(string)) + | String(string) => + atomic(Just(String |> Typ.temp), Constraint.String(string)) | ListLit(ps) => let ids = List.map(UPat.rep_id, ps); let modes = Mode.of_list_lit(ctx, List.length(ps), mode); @@ -823,7 +875,7 @@ and upat_to_info_map = let (tl, m) = go(~ctx=hd.ctx, ~mode=Mode.of_cons_tl(ctx, mode, hd.ty), tl, m); add( - ~self=Just(List(hd.ty)), + ~self=Just(List(hd.ty) |> Typ.temp), ~ctx=tl.ctx, ~constraint_= Constraint.InjR(Constraint.Pair(hd.constraint_, tl.constraint_)), @@ -838,7 +890,11 @@ and upat_to_info_map = hole(BadToken(name)); } else { let ctx_typ = - Info.fixed_typ_pat(ctx, mode, Common(Just(Unknown(Internal)))); + Info.fixed_typ_pat( + ctx, + mode, + Common(Just(Unknown(Internal) |> Typ.temp)), + ); let entry = Ctx.VarEntry({name, id: UPat.rep_id(upat), typ: ctx_typ}); add( ~self=Just(unknown), @@ -857,7 +913,7 @@ and upat_to_info_map = | [hd, ...tl] => Constraint.Pair(hd, cons_fold_tuple(tl)) }; add( - ~self=Just(Prod(tys)), + ~self=Just(Prod(tys) |> Typ.temp), ~ctx, ~constraint_=cons_fold_tuple(cons), m, @@ -865,7 +921,7 @@ and upat_to_info_map = | Parens(p) => let (p, m) = go(~ctx, ~mode, p, m); add(~self=Just(p.ty), ~ctx=p.ctx, ~constraint_=p.constraint_, m); - | Constructor(ctr) => + | Constructor(ctr, _) => if (Mode.is_module_ana(mode, ctx, is_module)) { let ctx_typ = Info.fixed_typ_pat(ctx, mode, Common(Just(Unknown(Internal)))); @@ -916,44 +972,10 @@ and upat_to_info_map = Constraint.of_ap(ctx, mode, ctr, arg.constraint_, Some(ty_out)), m, ); - | TypeAnn(p, ann) => + | Cast(p, ann, _) => let (ann, m) = utyp_to_info_map(~ctx, ~ancestors, ann, m); - let (p, m) = go(~ctx, ~mode=Ana(ann.ty), p, m); - add(~self=Just(ann.ty), ~ctx=p.ctx, ~constraint_=p.constraint_, m); - | TyAlias(typat, utyp) => - let m = utpat_to_info_map(~ctx, ~ancestors, typat, m) |> snd; - switch (typat.term) { - | Var(name) - when !Form.is_base_typ(name) && Ctx.lookup_alias(ctx, name) == None => - let (ty_def, ctx_def, ctx_body) = { - let ty_pre = UTyp.to_typ(Ctx.extend_dummy_tvar(ctx, name), utyp); - switch (utyp.term) { - | Sum(_) when List.mem(name, Typ.free_vars(ty_pre)) => - let ty_rec = Typ.Rec("α", Typ.subst(Var("α"), name, ty_pre)); - let ctx_def = - Ctx.extend_alias(ctx, name, UTPat.rep_id(typat), ty_rec); - (ty_rec, ctx_def, ctx_def); - | _ => - let ty = UTyp.to_typ(ctx, utyp); - (ty, ctx, Ctx.extend_alias(ctx, name, UTPat.rep_id(typat), ty)); - }; - }; - let ctx_body = - switch (Typ.get_sum_constructors(ctx, ty_def)) { - | Some(sm) => Ctx.add_ctrs(ctx_body, name, UTyp.rep_id(utyp), sm) - | None => ctx_body - }; - let m = utyp_to_info_map(~ctx=ctx_def, ~ancestors, utyp, m) |> snd; - add( - ~self=Just(ty_def), - ~ctx=ctx_body, - ~constraint_=Constraint.Truth, - m, - ); - | _ => - let m = utyp_to_info_map(~ctx, ~ancestors, utyp, m) |> snd; - add(~self=Just(unknown), ~ctx, ~constraint_=Constraint.Truth, m); - }; + let (p, m) = go(~ctx, ~mode=Ana(ann.term), p, m); + add(~self=Just(ann.term), ~ctx=p.ctx, ~constraint_=p.constraint_, m); }; } and utyp_to_info_map = @@ -961,7 +983,7 @@ and utyp_to_info_map = ~ctx, ~expects=Info.TypeExpected, ~ancestors, - {ids, term} as utyp: UTyp.t, + {ids, term, _} as utyp: UTyp.t, m: Map.t, ) : (Info.typ, Map.t) => { @@ -972,19 +994,16 @@ and utyp_to_info_map = let ancestors = [UTyp.rep_id(utyp)] @ ancestors; let go' = utyp_to_info_map(~ctx, ~ancestors); let go = go'(~expects=TypeExpected); - //TODO(andrew): make this return free, replacing Typ.free_vars switch (term) { - | MultiHole(tms) => + | Unknown(Hole(MultiHole(tms))) => let (_, m) = multi(~ctx, ~ancestors, m, tms); add(m); - | Invalid(_) - | EmptyHole + | Unknown(_) | Int | Float | Bool | String => add(m) - | Var(_) - | Constructor(_) => + | Var(_) => /* Names are resolved in Info.status_typ */ add(m) | List(t) @@ -993,25 +1012,27 @@ and utyp_to_info_map = let m = go(t1, m) |> snd; let m = go(t2, m) |> snd; add(m); - | Tuple(ts) => + | Prod(ts) => let m = map_m(go, ts, m) |> snd; add(m); | Ap(t1, t2) => - let ty_in = UTyp.to_typ(ctx, t2); let t1_mode: Info.typ_expects = switch (expects) { | VariantExpected(m, sum_ty) => - ConstructorExpected(m, Arrow(ty_in, sum_ty)) - | _ => ConstructorExpected(Unique, Arrow(ty_in, Unknown(Internal))) + ConstructorExpected(m, Arrow(t2, sum_ty) |> Typ.temp) + | _ => + ConstructorExpected( + Unique, + Arrow(t2, Unknown(Internal) |> Typ.temp) |> Typ.temp, + ) }; let m = go'(~expects=t1_mode, t1, m) |> snd; let m = go'(~expects=TypeExpected, t2, m) |> snd; add(m); | Sum(variants) => - let ty_sum = UTyp.to_typ(ctx, utyp); let (m, _) = List.fold_left( - variant_to_info_map(~ctx, ~ancestors, ~ty_sum), + variant_to_info_map(~ctx, ~ancestors, ~ty_sum=utyp), (m, []), variants, ); @@ -1043,10 +1064,7 @@ and utyp_to_info_map = add(m); | Forall({term: Var(name), _} as utpat, tbody) => let body_ctx = - Ctx.extend_tvar( - ctx, - {name, id: Term.UTPat.rep_id(utpat), kind: Abstract}, - ); + Ctx.extend_tvar(ctx, {name, id: TPat.rep_id(utpat), kind: Abstract}); let m = utyp_to_info_map( tbody, @@ -1066,10 +1084,7 @@ and utyp_to_info_map = add(m); // TODO: check with andrew | Rec({term: Var(name), _} as utpat, tbody) => let body_ctx = - Ctx.extend_tvar( - ctx, - {name, id: Term.UTPat.rep_id(utpat), kind: Abstract}, - ); + Ctx.extend_tvar(ctx, {name, id: TPat.rep_id(utpat), kind: Abstract}); let m = utyp_to_info_map( tbody, @@ -1090,13 +1105,13 @@ and utyp_to_info_map = }; } and utpat_to_info_map = - (~ctx, ~ancestors, {ids, term} as utpat: UTPat.t, m: Map.t) + (~ctx, ~ancestors, {ids, term, _} as utpat: TPat.t, m: Map.t) : (Info.tpat, Map.t) => { let add = m => { let info = Info.derived_tpat(~utpat, ~ctx, ~ancestors); (info, add_info(ids, InfoTPat(info), m)); }; - let ancestors = [UTPat.rep_id(utpat)] @ ancestors; + let ancestors = [TPat.rep_id(utpat)] @ ancestors; switch (term) { | MultiHole(tms) => let (_, m) = multi(~ctx, ~ancestors, m, tms); @@ -1500,7 +1515,13 @@ and uexp_to_module = } and variant_to_info_map = - (~ctx, ~ancestors, ~ty_sum, (m, ctrs), uty: UTyp.variant) => { + ( + ~ctx, + ~ancestors, + ~ty_sum, + (m, ctrs), + uty: ConstructorMap.variant(UTyp.t), + ) => { let go = expects => utyp_to_info_map(~ctx, ~ancestors, ~expects); switch (uty) { | BadEntry(uty) => @@ -1513,7 +1534,7 @@ and variant_to_info_map = List.mem(ctr, ctrs) ? Duplicate : Unique, ty_sum, ), - {term: Constructor(ctr), ids}, + {term: Var(ctr), ids, copied: false}, m, ) |> snd; @@ -1526,6 +1547,48 @@ and variant_to_info_map = }; }; +let mk = + Core.Memo.general(~cache_size_bound=1000, (ctx, e) => { + uexp_to_info_map(~ctx, ~ancestors=[], e, Id.Map.empty) |> snd + }); + +let mk = (core: CoreSettings.t, ctx, exp) => + core.statics ? mk(ctx, exp) : Id.Map.empty; + +let get_error_at = (info_map: Map.t, id: Id.t) => { + id + |> Id.Map.find_opt(_, info_map) + |> Option.bind( + _, + fun + | InfoExp(e) => Some(e) + | _ => None, + ) + |> Option.bind(_, e => + switch (e.status) { + | InHole(err_info) => Some(err_info) + | NotInHole(_) => None + } + ); +}; + +let get_pat_error_at = (info_map: Map.t, id: Id.t) => { + id + |> Id.Map.find_opt(_, info_map) + |> Option.bind( + _, + fun + | InfoPat(e) => Some(e) + | _ => None, + ) + |> Option.bind(_, e => + switch (e.status) { + | InHole(err_info) => Some(err_info) + | NotInHole(_) => None + } + ); +}; + let collect_errors = (map: Map.t): list((Id.t, Info.error)) => Id.Map.fold( (id, info: Info.t, acc) => diff --git a/src/haz3lcore/statics/Term.re b/src/haz3lcore/statics/Term.re index 7e5b518bb4..2075968433 100644 --- a/src/haz3lcore/statics/Term.re +++ b/src/haz3lcore/statics/Term.re @@ -1,437 +1,246 @@ -/* TERM - - These data structures define the term structures on which - the static and dynamic semantics of the language are based. - Each sort has a corresponding U module. - - The contained cls type lists the terms of that sort, and - should be in 1-1 correspondence with the term type which - is used to build composite terms. - - This is wrapped in a record type to associate a unique id - with each term. These unique ids are the same as from the - tile structure from the syntax module, as there is a 1-1 - correspondence between terms and tiles. - - TODO: add tests to check if there are forms and/or terms - without correponding syntax classes */ - -include TermBase.Any; -type any = t; - -module UTPat = { - [@deriving (show({with_path: false}), sexp, yojson)] - type cls = - | Invalid - | EmptyHole - | MultiHole - | Var; - - include TermBase.UTPat; - - let rep_id = ({ids, _}) => { - assert(ids != []); - List.hd(ids); - }; - - let hole = (tms: list(any)) => - switch (tms) { - | [] => EmptyHole - | [_, ..._] => MultiHole(tms) - }; - - let cls_of_term: term => cls = - fun - | Invalid(_) => Invalid - | EmptyHole => EmptyHole - | MultiHole(_) => MultiHole - | Var(_) => Var; - - let show_cls: cls => string = - fun - | Invalid => "Invalid type binding name" - | MultiHole => "Broken type binding" - | EmptyHole => "Empty type binding hole" - | Var => "Type binding"; - - let tyvar_of_utpat = ({ids: _, term}) => - switch (term) { - | Var(x) => Some(x) - | _ => None - }; -}; - -module UTyp = { - [@deriving (show({with_path: false}), sexp, yojson)] - type cls = - | Invalid - | EmptyHole - | MultiHole - | Int - | Float - | Bool - | String - | Arrow - | Tuple - | Sum - | List - | Var - | Constructor - | Module - | ModuleVar - | Parens - | Ap - | Dot - | Forall - | Rec; - - include TermBase.UTyp; - - let rep_id = ({ids, _}: t) => { - assert(ids != []); - List.hd(ids); - }; - - let hole = (tms: list(any)) => - switch (tms) { - | [] => EmptyHole - | [_, ..._] => MultiHole(tms) - }; - - let cls_of_term: term => cls = - fun - | Invalid(_) => Invalid - | EmptyHole => EmptyHole - | MultiHole(_) => MultiHole - | Int => Int - | Float => Float - | Bool => Bool - | String => String - | List(_) => List - | Arrow(_) => Arrow - | Var(_) => Var - | Constructor(_) => Constructor - | Tuple(_) => Tuple - | Parens(_) => Parens - | Module(_) => Module - | Ap(_) => Ap - | Dot(_) => Dot - | Sum(_) => Sum - | Forall(_) => Forall - | Rec(_) => Rec; - - let show_cls: cls => string = - fun - | Invalid => "Invalid type" - | MultiHole => "Broken type" - | EmptyHole => "Empty type hole" - | Int - | Float - | String - | Bool => "Base type" - | Var => "Type variable" - | Constructor => "Sum constructor" - | List => "List type" - | Arrow => "Function type" - | Tuple => "Product type" - | Sum => "Sum type" - | Parens => "Parenthesized type" - | Module => "Module type" - | ModuleVar => "Module path" - | Dot => "Member type" - | Ap => "Constructor application" - | Forall => "Forall Type" - | Rec => "Recursive Type"; - - let rec is_arrow = (typ: t) => { - switch (typ.term) { - | Parens(typ) => is_arrow(typ) - | Arrow(_) => true - | Invalid(_) - | EmptyHole - | MultiHole(_) - | Int - | Float - | Bool - | String - | List(_) - | Tuple(_) - | Var(_) - | Constructor(_) - | Ap(_) - | Module(_) - | Dot(_) - | Sum(_) - | Forall(_) - | Rec(_) => false - }; - }; - - let rec is_forall = (typ: t) => { - switch (typ.term) { - | Parens(typ) => is_forall(typ) - | Forall(_) => true - | Invalid(_) - | EmptyHole - | MultiHole(_) - | Int - | Float - | Bool - | String - | Arrow(_) - | List(_) - | Tuple(_) - | Var(_) - | Constructor(_) - | Module(_) - | Dot(_) - | Ap(_) - | Sum(_) - | Rec(_) => false - }; - }; - - /* Converts a syntactic type into a semantic type */ - let rec to_typ: (Ctx.t, t) => Typ.t = - (ctx, utyp) => - switch (utyp.term) { - | Invalid(_) - | MultiHole(_) => Unknown(Internal) - | EmptyHole => Unknown(TypeHole) - | Bool => Bool - | Int => Int - | Float => Float - | String => String - | Var(name) => - switch (Ctx.lookup_tvar(ctx, name)) { - | Some(_) => Var(name) - | None => Unknown(Free(name)) - } - | Arrow(u1, u2) => Arrow(to_typ(ctx, u1), to_typ(ctx, u2)) - | Tuple(us) => Prod(List.map(to_typ(ctx), us)) - | Sum(uts) => Sum(to_ctr_map(ctx, uts)) - | List(u) => List(to_typ(ctx, u)) - | Parens(u) => to_typ(ctx, u) - | Forall({term: Var(name), _} as utpat, tbody) => - let ctx = - Ctx.extend_tvar( - ctx, - {name, id: UTPat.rep_id(utpat), kind: Abstract}, - ); - Forall(name, to_typ(ctx, tbody)); - // Rec is same as Forall - | Rec({term: Var(name), _} as utpat, tbody) => - let ctx = - Ctx.extend_tvar( - ctx, - {name, id: UTPat.rep_id(utpat), kind: Abstract}, - ); - Rec(name, to_typ(ctx, tbody)); - | Forall({term: Invalid(_), _}, tbody) - | Forall({term: EmptyHole, _}, tbody) - | Forall({term: MultiHole(_), _}, tbody) => - Forall("?", to_typ(ctx, tbody)) - | Rec({term: Invalid(_), _}, tbody) - | Rec({term: EmptyHole, _}, tbody) - | Rec({term: MultiHole(_), _}, tbody) => Rec("?", to_typ(ctx, tbody)) - /* The below cases should occur only inside sums */ - | Constructor(_) - | Ap(_) => Unknown(Internal) - | Module(u) => - let rep_id_p = ({ids, _}: TermBase.UPat.t) => { - assert(ids != []); - List.hd(ids); - }; - let rep_id_t = ({ids, _}: TermBase.UTPat.t) => { - assert(ids != []); - List.hd(ids); - }; - let rec upat_to_ctx = - ( - (outer_ctx: Ctx.t, inner_ctx: Ctx.t, incomplete: bool), - upat: TermBase.UPat.t, - ) => { - switch (upat.term) { - | Invalid(_) - | EmptyHole - | MultiHole(_) - | Int(_) - | Float(_) - | Bool(_) - | String(_) - | Triv - | ListLit(_) - | Cons(_) - | Tuple(_) - | Wild - | Ap(_) => (outer_ctx, inner_ctx, incomplete) - // | Wild => (outer_ctx, inner_ctx, true) // disabled due to casting issues. - | TypeAnn(var, utyp1) => - switch (var.term, utyp1.term) { - | (Var(name), _) - // All constructors appearing here should be Modules. - | (Constructor(name), _) => ( - outer_ctx, - [ - VarEntry({ - name, - id: rep_id_p(var), - typ: to_typ(outer_ctx, utyp1), - }), - ...inner_ctx, - ], - incomplete, - ) - | _ => (outer_ctx, inner_ctx, incomplete) - } - | Var(name) => ( - outer_ctx, - [ - VarEntry({name, id: rep_id_p(upat), typ: Unknown(TypeHole)}), - ...inner_ctx, - ], - incomplete, - ) - | Constructor(name) => ( - outer_ctx, - [ - ConstructorEntry({ - name, - id: rep_id_p(upat), - typ: Unknown(TypeHole), - }), - ...inner_ctx, - ], - incomplete, - ) - | TyAlias(typat, utyp) => - switch (typat.term) { - | Var(name) - when - !Form.is_base_typ(name) - && Ctx.lookup_alias(inner_ctx, name) == None => - /* NOTE(andrew): See TyAlias in Statics.uexp_to_info_map */ - let (ty_def, ctx_body, new_inner) = { - let ty_pre = - to_typ(Ctx.extend_dummy_tvar(outer_ctx, name), utyp); - switch (utyp.term) { - | Sum(_) when List.mem(name, Typ.free_vars(ty_pre)) => - let ty_rec = - Typ.Rec("α", Typ.subst(Var("α"), name, ty_pre)); - ( - ty_rec, - Ctx.extend_alias( - outer_ctx, - name, - rep_id_t(typat), - ty_rec, - ), - Ctx.extend_alias( - inner_ctx, - name, - rep_id_t(typat), - ty_rec, - ), - ); - | _ => - let ty = to_typ(outer_ctx, utyp); - ( - ty, - Ctx.extend_alias(outer_ctx, name, rep_id_t(typat), ty), - Ctx.extend_alias(inner_ctx, name, rep_id_t(typat), ty), - ); - }; - }; - switch (Typ.get_sum_constructors(outer_ctx, ty_def)) { - | Some(sm) => ( - Ctx.add_ctrs(ctx_body, name, rep_id(utyp), sm), - Ctx.add_ctrs(new_inner, name, rep_id(utyp), sm), - incomplete, - ) - | None => (ctx_body, new_inner, incomplete) - }; - - | _ => (outer_ctx, inner_ctx, incomplete) - } - | Parens(p) => upat_to_ctx((outer_ctx, inner_ctx, incomplete), p) - }; - }; - let rec get_Tuple: TermBase.UPat.t => Typ.t = ( - ut => - switch (ut.term) { - | Tuple(us) => - let (_, inner_ctx, incomplete) = - List.fold_left(upat_to_ctx, (ctx, [], false), us); - Module({inner_ctx, incomplete}); - | Parens(p) => get_Tuple(p) - | TypeAnn(_) - | Var(_) - | Constructor(_) - | TyAlias(_) - | Invalid(_) - | EmptyHole - | MultiHole(_) - | Wild - | Int(_) - | Float(_) - | Bool(_) - | String(_) - | Triv - | ListLit(_) - | Cons(_) - | Ap(_) => - let (_, inner_ctx, incomplete) = - upat_to_ctx((ctx, [], false), ut); - Module({inner_ctx, incomplete}); - } - ); - get_Tuple(u); - | Dot(typ1, typ2) => - /** Currently, the only possible way to introduce modules are through - a variable in Constructor form. - - Maybe better to put to_typ in Statics? */ - open Util.OptUtil.Syntax; - let rec inner_normalize = (ctx: Ctx.t, ty: Typ.t): option(Typ.t) => - switch (ty) { - | Var(x) => - let* ty = Ctx.lookup_alias(ctx, x); - inner_normalize(ctx, ty); - | _ => Some(ty) - }; - let res = { - let* name = Module.get_tyname(typ2); - let+ (tag_name, inner_ctx) = Module.get_module("", ctx, typ1); - let ty = { - let* inner_ctx = inner_ctx; - inner_normalize(inner_ctx, to_typ(inner_ctx, typ2)); - }; - (tag_name ++ name, ty); - }; - switch (res) { - | Some((name, Some(ty))) => Member(name, ty) - | Some((name, None)) => Member(name, Unknown(Internal)) - | None => Member("?", Unknown(Internal)) - }; - } - and to_variant: - (Ctx.t, variant) => option(ConstructorMap.binding(option(Typ.t))) = - ctx => - fun - | Variant(ctr, _, u) => Some((ctr, Option.map(to_typ(ctx), u))) - | BadEntry(_) => None - and to_ctr_map = (ctx: Ctx.t, uts: list(variant)): Typ.sum_map => { - List.fold_left( - (acc, ut) => - List.find_opt(((ctr, _)) => ctr == fst(ut), acc) == None - ? acc @ [ut] : acc, - [], - List.filter_map(to_variant(ctx), uts), - ); - }; -}; - -module UPat = { +// module UTyp = { + +// /* Converts a syntactic type into a semantic type */ +// let rec to_typ: (Ctx.t, t) => Typ.t = +// (ctx, utyp) => +// switch (utyp.term) { +// | Invalid(_) +// | MultiHole(_) => Unknown(Internal) +// | EmptyHole => Unknown(TypeHole) +// | Bool => Bool +// | Int => Int +// | Float => Float +// | String => String +// | Var(name) => +// switch (Ctx.lookup_tvar(ctx, name)) { +// | Some(_) => Var(name) +// | None => Unknown(Free(name)) +// } +// | Arrow(u1, u2) => Arrow(to_typ(ctx, u1), to_typ(ctx, u2)) +// | Tuple(us) => Prod(List.map(to_typ(ctx), us)) +// | Sum(uts) => Sum(to_ctr_map(ctx, uts)) +// | List(u) => List(to_typ(ctx, u)) +// | Parens(u) => to_typ(ctx, u) +// | Forall({term: Var(name), _} as utpat, tbody) => +// let ctx = +// Ctx.extend_tvar( +// ctx, +// {name, id: UTPat.rep_id(utpat), kind: Abstract}, +// ); +// Forall(name, to_typ(ctx, tbody)); +// // Rec is same as Forall +// | Rec({term: Var(name), _} as utpat, tbody) => +// let ctx = +// Ctx.extend_tvar( +// ctx, +// {name, id: UTPat.rep_id(utpat), kind: Abstract}, +// ); +// Rec(name, to_typ(ctx, tbody)); +// | Forall({term: Invalid(_), _}, tbody) +// | Forall({term: EmptyHole, _}, tbody) +// | Forall({term: MultiHole(_), _}, tbody) => +// Forall("?", to_typ(ctx, tbody)) +// | Rec({term: Invalid(_), _}, tbody) +// | Rec({term: EmptyHole, _}, tbody) +// | Rec({term: MultiHole(_), _}, tbody) => Rec("?", to_typ(ctx, tbody)) +// /* The below cases should occur only inside sums */ +// | Constructor(_) +// | Ap(_) => Unknown(Internal) +// | Module(u) => +// let rep_id_p = ({ids, _}: TermBase.UPat.t) => { +// assert(ids != []); +// List.hd(ids); +// }; +// let rep_id_t = ({ids, _}: TermBase.UTPat.t) => { +// assert(ids != []); +// List.hd(ids); +// }; +// let rec upat_to_ctx = +// ( +// (outer_ctx: Ctx.t, inner_ctx: Ctx.t, incomplete: bool), +// upat: TermBase.UPat.t, +// ) => { +// switch (upat.term) { +// | Invalid(_) +// | EmptyHole +// | MultiHole(_) +// | Int(_) +// | Float(_) +// | Bool(_) +// | String(_) +// | Triv +// | ListLit(_) +// | Cons(_) +// | Tuple(_) +// | Wild +// | Ap(_) => (outer_ctx, inner_ctx, incomplete) +// // | Wild => (outer_ctx, inner_ctx, true) // disabled due to casting issues. +// | TypeAnn(var, utyp1) => +// switch (var.term, utyp1.term) { +// | (Var(name), _) +// // All constructors appearing here should be Modules. +// | (Constructor(name), _) => ( +// outer_ctx, +// [ +// VarEntry({ +// name, +// id: rep_id_p(var), +// typ: to_typ(outer_ctx, utyp1), +// }), +// ...inner_ctx, +// ], +// incomplete, +// ) +// | _ => (outer_ctx, inner_ctx, incomplete) +// } +// | Var(name) => ( +// outer_ctx, +// [ +// VarEntry({name, id: rep_id_p(upat), typ: Unknown(TypeHole)}), +// ...inner_ctx, +// ], +// incomplete, +// ) +// | Constructor(name) => ( +// outer_ctx, +// [ +// ConstructorEntry({ +// name, +// id: rep_id_p(upat), +// typ: Unknown(TypeHole), +// }), +// ...inner_ctx, +// ], +// incomplete, +// ) +// | TyAlias(typat, utyp) => +// switch (typat.term) { +// | Var(name) +// when +// !Form.is_base_typ(name) +// && Ctx.lookup_alias(inner_ctx, name) == None => +// /* NOTE(andrew): See TyAlias in Statics.uexp_to_info_map */ +// let (ty_def, ctx_body, new_inner) = { +// let ty_pre = +// to_typ(Ctx.extend_dummy_tvar(outer_ctx, name), utyp); +// switch (utyp.term) { +// | Sum(_) when List.mem(name, Typ.free_vars(ty_pre)) => +// let ty_rec = +// Typ.Rec("α", Typ.subst(Var("α"), name, ty_pre)); +// ( +// ty_rec, +// Ctx.extend_alias( +// outer_ctx, +// name, +// rep_id_t(typat), +// ty_rec, +// ), +// Ctx.extend_alias( +// inner_ctx, +// name, +// rep_id_t(typat), +// ty_rec, +// ), +// ); +// | _ => +// let ty = to_typ(outer_ctx, utyp); +// ( +// ty, +// Ctx.extend_alias(outer_ctx, name, rep_id_t(typat), ty), +// Ctx.extend_alias(inner_ctx, name, rep_id_t(typat), ty), +// ); +// }; +// }; +// switch (Typ.get_sum_constructors(outer_ctx, ty_def)) { +// | Some(sm) => ( +// Ctx.add_ctrs(ctx_body, name, rep_id(utyp), sm), +// Ctx.add_ctrs(new_inner, name, rep_id(utyp), sm), +// incomplete, +// ) +// | None => (ctx_body, new_inner, incomplete) +// }; + +// | _ => (outer_ctx, inner_ctx, incomplete) +// } +// | Parens(p) => upat_to_ctx((outer_ctx, inner_ctx, incomplete), p) +// }; +// }; +// let rec get_Tuple: TermBase.UPat.t => Typ.t = ( +// ut => +// switch (ut.term) { +// | Tuple(us) => +// let (_, inner_ctx, incomplete) = +// List.fold_left(upat_to_ctx, (ctx, [], false), us); +// Module({inner_ctx, incomplete}); +// | Parens(p) => get_Tuple(p) +// | TypeAnn(_) +// | Var(_) +// | Constructor(_) +// | TyAlias(_) +// | Invalid(_) +// | EmptyHole +// | MultiHole(_) +// | Wild +// | Int(_) +// | Float(_) +// | Bool(_) +// | String(_) +// | Triv +// | ListLit(_) +// | Cons(_) +// | Ap(_) => +// let (_, inner_ctx, incomplete) = +// upat_to_ctx((ctx, [], false), ut); +// Module({inner_ctx, incomplete}); +// } +// ); +// get_Tuple(u); +// | Dot(typ1, typ2) => +// /** Currently, the only possible way to introduce modules are through +// a variable in Constructor form. + +// Maybe better to put to_typ in Statics? */ +// open Util.OptUtil.Syntax; +// let rec inner_normalize = (ctx: Ctx.t, ty: Typ.t): option(Typ.t) => +// switch (ty) { +// | Var(x) => +// let* ty = Ctx.lookup_alias(ctx, x); +// inner_normalize(ctx, ty); +// | _ => Some(ty) +// }; +// let res = { +// let* name = Module.get_tyname(typ2); +// let+ (tag_name, inner_ctx) = Module.get_module("", ctx, typ1); +// let ty = { +// let* inner_ctx = inner_ctx; +// inner_normalize(inner_ctx, to_typ(inner_ctx, typ2)); +// }; +// (tag_name ++ name, ty); +// }; +// switch (res) { +// | Some((name, Some(ty))) => Member(name, ty) +// | Some((name, None)) => Member(name, Unknown(Internal)) +// | None => Member("?", Unknown(Internal)) +// }; +// } +// and to_variant: +// (Ctx.t, variant) => option(ConstructorMap.binding(option(Typ.t))) = +// ctx => +// fun +// | Variant(ctr, _, u) => Some((ctr, Option.map(to_typ(ctx), u))) +// | BadEntry(_) => None +// and to_ctr_map = (ctx: Ctx.t, uts: list(variant)): Typ.sum_map => { +// List.fold_left( +// (acc, ut) => +// List.find_opt(((ctr, _)) => ctr == fst(ut), acc) == None +// ? acc @ [ut] : acc, +// [], +// List.filter_map(to_variant(ctx), uts), +// ); +// }; +// }; + +module Pat = { [@deriving (show({with_path: false}), sexp, yojson)] type cls = | Invalid @@ -442,7 +251,6 @@ module UPat = { | Float | Bool | String - | Triv | ListLit | Constructor | Cons @@ -451,17 +259,22 @@ module UPat = { | Tuple | Parens | Ap - | TypeAnn - | TyAlias; + | Cast; - include TermBase.UPat; + include TermBase.Pat; let rep_id = ({ids, _}: t) => { assert(ids != []); List.hd(ids); }; - let hole = (tms: list(any)) => + let term_of: t => TermBase.Pat.term = IdTagged.term_of; + + let unwrap: t => (term, term => t) = IdTagged.unwrap; + + let fresh: term => t = IdTagged.fresh; + + let hole = (tms: list(TermBase.Any.t)) => switch (tms) { | [] => EmptyHole | [_, ..._] => MultiHole(tms) @@ -477,7 +290,6 @@ module UPat = { | Float(_) => Float | Bool(_) => Bool | String(_) => String - | Triv => Triv | ListLit(_) => ListLit | Constructor(_) => Constructor | Cons(_) => Cons @@ -485,8 +297,8 @@ module UPat = { | Tuple(_) => Tuple | Parens(_) => Parens | Ap(_) => Ap - | TypeAnn(_) => TypeAnn - | TyAlias(_) => TyAlias; + | TyAlias(_) => TyAlias + | Cast(_) => Cast; let show_cls: cls => string = fun @@ -498,7 +310,6 @@ module UPat = { | Float => "Float literal" | Bool => "Boolean literal" | String => "String literal" - | Triv => "Trivial literal" | ListLit => "List literal" | Constructor => "Constructor" | Cons => "Cons" @@ -508,12 +319,12 @@ module UPat = { | Parens => "Parenthesized pattern" | Ap => "Constructor application" | TyAlias => "Type alias definition pattern" - | TypeAnn => "Annotation"; + | Cast => "Annotation"; let rec is_var = (pat: t) => { switch (pat.term) { | Parens(pat) - | TypeAnn(pat, _) => is_var(pat) + | Cast(pat, _, _) => is_var(pat) | Var(_) => true | TyAlias(_) | Invalid(_) @@ -524,7 +335,6 @@ module UPat = { | Float(_) | Bool(_) | String(_) - | Triv | ListLit(_) | Cons(_, _) | Tuple(_) @@ -536,8 +346,8 @@ module UPat = { let rec is_fun_var = (pat: t) => { switch (pat.term) { | Parens(pat) => is_fun_var(pat) - | TypeAnn(pat, typ) => - is_var(pat) && (UTyp.is_arrow(typ) || UTyp.is_forall(typ)) + | Cast(pat, typ, _) => + is_var(pat) && (UTyp.is_arrow(typ) || Typ.is_forall(typ)) | Invalid(_) | EmptyHole | MultiHole(_) @@ -546,7 +356,6 @@ module UPat = { | Float(_) | Bool(_) | String(_) - | Triv | ListLit(_) | Cons(_, _) | Var(_) @@ -571,11 +380,10 @@ module UPat = { | Float(_) | Bool(_) | String(_) - | Triv | ListLit(_) | Cons(_, _) | Var(_) - | TypeAnn(_) + | Cast(_) | Constructor(_) | TyAlias(_) | Ap(_) => false @@ -587,7 +395,7 @@ module UPat = { || ( switch (pat.term) { | Parens(pat) - | TypeAnn(pat, _) => is_tuple_of_vars(pat) + | Cast(pat, _, _) => is_tuple_of_vars(pat) | Tuple(pats) => pats |> List.for_all(is_var) | Invalid(_) | EmptyHole @@ -597,7 +405,6 @@ module UPat = { | Float(_) | Bool(_) | String(_) - | Triv | ListLit(_) | Cons(_, _) | Var(_) @@ -609,10 +416,10 @@ module UPat = { let rec get_var = (pat: t) => { switch (pat.term) { - | Parens(pat) - | TypeAnn(pat, _) => get_var(pat) + | Parens(pat) => get_var(pat) | Var(x) => Some(x) | TyAlias(_) + | Cast(x, _, _) => get_var(x) | Invalid(_) | EmptyHole | MultiHole(_) @@ -621,7 +428,6 @@ module UPat = { | Float(_) | Bool(_) | String(_) - | Triv | ListLit(_) | Cons(_, _) | Tuple(_) @@ -633,8 +439,8 @@ module UPat = { let rec get_fun_var = (pat: t) => { switch (pat.term) { | Parens(pat) => get_fun_var(pat) - | TypeAnn(pat, typ) => - if (UTyp.is_arrow(typ) || UTyp.is_forall(typ)) { + | Cast(pat, t1, _) => + if (Typ.is_arrow(t1) || UTyp.is_forall(t1)) { get_var(pat) |> Option.map(var => var); } else { None; @@ -647,7 +453,6 @@ module UPat = { | Float(_) | Bool(_) | String(_) - | Triv | ListLit(_) | Cons(_, _) | Var(_) @@ -691,7 +496,7 @@ module UPat = { | None => switch (pat.term) { | Parens(pat) - | TypeAnn(pat, _) => get_bindings(pat) + | Cast(pat, _, _) => get_bindings(pat) | Tuple(pats) => let vars = pats |> List.map(get_var); if (List.exists(Option.is_none, vars)) { @@ -707,7 +512,6 @@ module UPat = { | Float(_) | Bool(_) | String(_) - | Triv | ListLit(_) | Cons(_, _) | Var(_) @@ -717,23 +521,51 @@ module UPat = { } }; + let rec get_num_of_vars = (pat: t) => + if (is_var(pat)) { + Some(1); + } else { + switch (pat.term) { + | Parens(pat) + | Cast(pat, _, _) => get_num_of_vars(pat) + | Tuple(pats) => + is_tuple_of_vars(pat) ? Some(List.length(pats)) : None + | Invalid(_) + | EmptyHole + | MultiHole(_) + | Wild + | Int(_) + | Float(_) + | Bool(_) + | String(_) + | ListLit(_) + | Cons(_, _) + | Var(_) + | Constructor(_) + | Ap(_) => None + }; + }; + let ctr_name = (p: t): option(Constructor.t) => switch (p.term) { - | Constructor(name) => Some(name) + | Constructor(name, _) => Some(name) | _ => None }; }; -module UExp = { - include TermBase.UExp; +module Exp = { + include TermBase.Exp; [@deriving (show({with_path: false}), sexp, yojson)] type cls = | Invalid | EmptyHole | MultiHole - | Triv + | StaticErrorHole + | DynamicErrorHole + | FailedCast | Deferral + | Undefined | Bool | Int | Float @@ -749,6 +581,7 @@ module UExp = { | Module | ModuleVar | Dot + | FixF | TyAlias | Ap | TypAp @@ -758,31 +591,35 @@ module UExp = { | Seq | Test | Filter + | Closure | Parens | Cons - | UnOp(op_un) - | BinOp(op_bin) + | UnOp(Operators.op_un) + | BinOp(Operators.op_bin) + | BuiltinFun | Match + | Cast | ListConcat; - let hole = (tms: list(any)): term => + let hole = (tms: list(TermBase.Any.t)): term => switch (tms) { | [] => EmptyHole | [_, ..._] => MultiHole(tms) }; - let rep_id = ({ids, _}) => { - assert(ids != []); - List.hd(ids); - }; + let rep_id: t => Id.t = IdTagged.rep_id; + let fresh: term => t = IdTagged.fresh; + let unwrap: t => (term, term => t) = IdTagged.unwrap; let cls_of_term: term => cls = fun | Invalid(_) => Invalid | EmptyHole => EmptyHole | MultiHole(_) => MultiHole - | Triv => Triv + | DynamicErrorHole(_) => DynamicErrorHole + | FailedCast(_) => FailedCast | Deferral(_) => Deferral + | Undefined => Undefined | Bool(_) => Bool | Int(_) => Int | Float(_) => Float @@ -796,92 +633,35 @@ module UExp = { | Let(_) => Let | Module(_) => Module | Dot(_) => Dot + | FixF(_) => FixF | TyAlias(_) => TyAlias | Ap(_) => Ap | TypAp(_) => TypAp | DeferredAp(_) => DeferredAp - | Pipeline(_) => Pipeline | If(_) => If | Seq(_) => Seq | Test(_) => Test | Filter(_) => Filter + | Closure(_) => Closure | Parens(_) => Parens | Cons(_) => Cons | ListConcat(_) => ListConcat | UnOp(op, _) => UnOp(op) | BinOp(op, _, _) => BinOp(op) - | Match(_) => Match; - - let show_op_un_meta: op_un_meta => string = - fun - | Unquote => "Un-quotation"; - - let show_op_un_bool: op_un_bool => string = - fun - | Not => "Boolean Negation"; - - let show_op_un_int: op_un_int => string = - fun - | Minus => "Integer Negation"; - - let show_unop: op_un => string = - fun - | Meta(op) => show_op_un_meta(op) - | Bool(op) => show_op_un_bool(op) - | Int(op) => show_op_un_int(op); - - let show_op_bin_bool: op_bin_bool => string = - fun - | And => "Boolean Conjunction" - | Or => "Boolean Disjunction"; - - let show_op_bin_int: op_bin_int => string = - fun - | Plus => "Integer Addition" - | Minus => "Integer Subtraction" - | Times => "Integer Multiplication" - | Power => "Integer Exponentiation" - | Divide => "Integer Division" - | LessThan => "Integer Less Than" - | LessThanOrEqual => "Integer Less Than or Equal" - | GreaterThan => "Integer Greater Than" - | GreaterThanOrEqual => "Integer Greater Than or Equal" - | Equals => "Integer Equality" - | NotEquals => "Integer Inequality"; - - let show_op_bin_float: op_bin_float => string = - fun - | Plus => "Float Addition" - | Minus => "Float Subtraction" - | Times => "Float Multiplication" - | Power => "Float Exponentiation" - | Divide => "Float Division" - | LessThan => "Float Less Than" - | LessThanOrEqual => "Float Less Than or Equal" - | GreaterThan => "Float Greater Than" - | GreaterThanOrEqual => "Float Greater Than or Equal" - | Equals => "Float Equality" - | NotEquals => "Float Inequality"; - - let show_op_bin_string: op_bin_string => string = - fun - | Concat => "String Concatenation" - | Equals => "String Equality"; - - let show_binop: op_bin => string = - fun - | Int(op) => show_op_bin_int(op) - | Float(op) => show_op_bin_float(op) - | Bool(op) => show_op_bin_bool(op) - | String(op) => show_op_bin_string(op); + | BuiltinFun(_) => BuiltinFun + | Match(_) => Match + | Cast(_) => Cast; let show_cls: cls => string = fun | Invalid => "Invalid expression" | MultiHole => "Broken expression" | EmptyHole => "Empty expression hole" - | Triv => "Trivial literal" + | StaticErrorHole => "Static error hole" + | DynamicErrorHole => "Dynamic error hole" + | FailedCast => "Failed cast" | Deferral => "Deferral" + | Undefined => "Undefined expression" | Bool => "Boolean literal" | Int => "Integer literal" | Float => "Float literal" @@ -897,6 +677,7 @@ module UExp = { | Module => "Module expression" | ModuleVar => "Module path" | Dot => "Dot access" + | FixF => "Fixpoint operator" | TyAlias => "Type Alias definition" | Ap => "Application" | TypAp => "Type application" @@ -906,25 +687,32 @@ module UExp = { | Seq => "Sequence expression" | Test => "Test" | Filter => "Filter" + | Closure => "Closure" | Parens => "Parenthesized expression" | Cons => "Cons" | ListConcat => "List Concatenation" - | BinOp(op) => show_binop(op) - | UnOp(op) => show_unop(op) - | Match => "Case expression"; + | BinOp(op) => Operators.show_binop(op) + | UnOp(op) => Operators.show_unop(op) + | BuiltinFun => "Built-in Function" + | Match => "Case expression" + | Cast => "Cast expression"; // Typfun should be treated as a function here as this is only used to // determine when to allow for recursive definitions in a let binding. let rec is_fun = (e: t) => { switch (e.term) { | Parens(e) => is_fun(e) + | Cast(e, _, _) => is_fun(e) | TypFun(_) - | Fun(_) => true + | Fun(_) + | BuiltinFun(_) => true | Invalid(_) | EmptyHole | MultiHole(_) - | Triv + | DynamicErrorHole(_) + | FailedCast(_) | Deferral(_) + | Undefined | Bool(_) | Int(_) | Float(_) @@ -935,17 +723,18 @@ module UExp = { | Let(_) | Module(_) | Dot(_) + | FixF(_) | TyAlias(_) | Ap(_) | TypAp(_) | DeferredAp(_) - | Pipeline(_) | If(_) | Seq(_) | Test(_) | Filter(_) | Cons(_) | ListConcat(_) + | Closure(_) | UnOp(_) | BinOp(_) | Match(_) @@ -957,13 +746,16 @@ module UExp = { is_fun(e) || ( switch (e.term) { + | Cast(e, _, _) | Parens(e) => is_tuple_of_functions(e) | Tuple(es) => es |> List.for_all(is_fun) | Invalid(_) | EmptyHole | MultiHole(_) - | Triv + | DynamicErrorHole(_) + | FailedCast(_) | Deferral(_) + | Undefined | Bool(_) | Int(_) | Float(_) @@ -971,15 +763,17 @@ module UExp = { | ListLit(_) | Fun(_) | TypFun(_) + | Closure(_) + | BuiltinFun(_) | Var(_) | Let(_) | Module(_) | Dot(_) + | FixF(_) | TyAlias(_) | Ap(_) | TypAp(_) | DeferredAp(_) - | Pipeline(_) | If(_) | Seq(_) | Test(_) @@ -995,7 +789,7 @@ module UExp = { let ctr_name = (e: t): option(Constructor.t) => switch (e.term) { - | Constructor(name) => Some(name) + | Constructor(name, _) => Some(name) | _ => None }; @@ -1016,8 +810,14 @@ module UExp = { | Invalid(_) | EmptyHole | MultiHole(_) - | Triv + | DynamicErrorHole(_) + | FailedCast(_) + | FixF(_) + | Closure(_) + | BuiltinFun(_) + | Cast(_) | Deferral(_) + | Undefined | Bool(_) | Int(_) | Float(_) @@ -1034,7 +834,6 @@ module UExp = { | Ap(_) | TypAp(_) | DeferredAp(_) - | Pipeline(_) | If(_) | Seq(_) | Test(_) @@ -1048,9 +847,8 @@ module UExp = { }; }; -// TODO(d): consider just folding this into UExp -module URul = { - include TermBase.URul; +module Rul = { + include TermBase.Rul; [@deriving (show({with_path: false}), sexp, yojson)] type cls = @@ -1059,7 +857,7 @@ module URul = { // example of awkwardness induced by having forms like rules // that may have a different-sorted child with no delimiters // (eg scrut with no rules) - let ids = (~any_ids, {ids, term}: t) => + let ids = (~any_ids, {ids, term, _}: t) => switch (ids) { | [_, ..._] => ids | [] => @@ -1072,59 +870,55 @@ module URul = { let rep_id = (~any_ids, tm) => switch (ids(~any_ids, tm)) { - | [] => raise(Invalid_argument("Term.UExp.rep_id")) + | [] => raise(Invalid_argument("UExp.rep_id")) | [id, ..._] => id }; }; -module Cls = { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - | Exp(UExp.cls) - | Pat(UPat.cls) - | Typ(UTyp.cls) - | TPat(UTPat.cls) - | Rul(URul.cls) - | Secondary(Secondary.cls); - - let show = (cls: t) => - switch (cls) { - | Exp(cls) => UExp.show_cls(cls) - | Pat(cls) => UPat.show_cls(cls) - | Typ(cls) => UTyp.show_cls(cls) - | TPat(cls) => UTPat.show_cls(cls) - | Rul(cls) => URul.show_cls(cls) - | Secondary(cls) => Secondary.show_cls(cls) - }; -}; +module Any = { + include TermBase.Any; -let rec ids = - fun - | Exp(tm) => tm.ids - | Pat(tm) => tm.ids - | Typ(tm) => tm.ids - | TPat(tm) => tm.ids - | Rul(tm) => URul.ids(~any_ids=ids, tm) - | Nul () - | Any () => []; + let is_exp: t => option(TermBase.Exp.t) = + fun + | Exp(e) => Some(e) + | _ => None; + let is_pat: t => option(TermBase.Pat.t) = + fun + | Pat(p) => Some(p) + | _ => None; + let is_typ: t => option(TermBase.Typ.t) = + fun + | Typ(t) => Some(t) + | _ => None; -// Terms may consist of multiple tiles, eg the commas in an n-tuple, -// the rules of a case expression + the surrounding case-end tile, -// the list brackets tile coupled with the elem-separating commas. -// The _representative id_ is the canonical tile id used to identify -// and look up info about a term. -// -// In instances like case expressions and list literals, where a parent -// tile surrounds the other tiles, the representative id is the parent tile's. -// In other instances like n-tuples, where the commas are all siblings, -// the representative id is one of the comma ids, unspecified which one. -// (This would change for n-tuples if we decided parentheses are necessary.) -let rep_id = - fun - | Exp(tm) => UExp.rep_id(tm) - | Pat(tm) => UPat.rep_id(tm) - | Typ(tm) => UTyp.rep_id(tm) - | TPat(tm) => UTPat.rep_id(tm) - | Rul(tm) => URul.rep_id(~any_ids=ids, tm) - | Nul () - | Any () => raise(Invalid_argument("Term.rep_id")); + let rec ids = + fun + | Exp(tm) => tm.ids + | Pat(tm) => tm.ids + | Typ(tm) => tm.ids + | TPat(tm) => tm.ids + | Rul(tm) => Rul.ids(~any_ids=ids, tm) + | Nul () + | Any () => []; + + // Terms may consist of multiple tiles, eg the commas in an n-tuple, + // the rules of a case expression + the surrounding case-end tile, + // the list brackets tile coupled with the elem-separating commas. + // The _representative id_ is the canonical tile id used to identify + // and look up info about a term. + // + // In instances like case expressions and list literals, where a parent + // tile surrounds the other tiles, the representative id is the parent tile's. + // In other instances like n-tuples, where the commas are all siblings, + // the representative id is one of the comma ids, unspecified which one. + // (This would change for n-tuples if we decided parentheses are necessary.) + let rep_id = + fun + | Exp(tm) => Exp.rep_id(tm) + | Pat(tm) => Pat.rep_id(tm) + | Typ(tm) => Typ.rep_id(tm) + | TPat(tm) => TPat.rep_id(tm) + | Rul(tm) => Rul.rep_id(~any_ids=ids, tm) + | Nul () + | Any () => raise(Invalid_argument("Term.rep_id")); +}; diff --git a/src/haz3lcore/statics/TermBase.re b/src/haz3lcore/statics/TermBase.re index afcc754423..0c45437588 100644 --- a/src/haz3lcore/statics/TermBase.re +++ b/src/haz3lcore/statics/TermBase.re @@ -1,138 +1,131 @@ -open Sexplib.Std; +open Util; -module rec Any: { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - | Exp(UExp.t) - | Pat(UPat.t) - | Typ(UTyp.t) - | TPat(UTPat.t) - | Rul(URul.t) - | Nul(unit) - | Any(unit); +let continue = x => x; +let stop = (_, x) => x; - let is_exp: t => option(UExp.t); - let is_pat: t => option(UPat.t); - let is_typ: t => option(UTyp.t); -} = { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - | Exp(UExp.t) - | Pat(UPat.t) - | Typ(UTyp.t) - | TPat(UTPat.t) - | Rul(URul.t) - | Nul(unit) - | Any(unit); +/* + This megafile contains the definitions of the expression data types in + Hazel. They are all in one file because they are mutually recursive, and + OCaml doesn't let us have mutually recursive files. Any definition that + is not mutually recursive across the whole data structure should be + defined in Any.re, Exp.re, Typ.re, Pat.re, TPat.re, etc... - let is_exp: t => option(UExp.t) = - fun - | Exp(e) => Some(e) - | _ => None; - let is_pat: t => option(UPat.t) = - fun - | Pat(p) => Some(p) - | _ => None; - let is_typ: t => option(UTyp.t) = - fun - | Typ(t) => Some(t) - | _ => None; -} -and UExp: { - [@deriving (show({with_path: false}), sexp, yojson)] - type op_un_bool = - | Not; + Each module has: - [@deriving (show({with_path: false}), sexp, yojson)] - type op_un_meta = - | Unquote; + - A type definition for the term - [@deriving (show({with_path: false}), sexp, yojson)] - type op_un_int = - | Minus; + - A map_term function that allows you to apply a function to every term in + the data structure with the following type: - [@deriving (show({with_path: false}), sexp, yojson)] - type op_bin_bool = - | And - | Or; + map_term: + ( + ~f_exp: (Exp.t => Exp.t, Exp.t) => Exp.t=?, + ~f_pat: (Pat.t => Pat.t, Pat.t) => Pat.t=?, + ~f_typ: (Typ.t => Typ.t, Typ.t) => Typ.t=?, + ~f_tpat: (TPat.t => TPat.t, TPat.t) => TPat.t=?, + ~f_rul: (Rul.t => Rul.t, Rul.t) => Rul.t=?, + ~f_any: (Any.t => Any.t, Any.t) => Any.t=?, + t + ) => + t; - [@deriving (show({with_path: false}), sexp, yojson)] - type op_bin_int = - | Plus - | Minus - | Times - | Power - | Divide - | LessThan - | LessThanOrEqual - | GreaterThan - | GreaterThanOrEqual - | Equals - | NotEquals; + Each argument to `map_term` specifies what should happen at each node in the + data structure. Each function takes two arguments: a `continue` function that + allows the map to continue on all the children nodes, and the current node + itself. If you don't explicitly call the `continue` function, the map will + not traverse the children nodes. If you don't provide a function for a + specific kind of node, the map will simply continue at that node without + any additional action. - [@deriving (show({with_path: false}), sexp, yojson)] - type op_bin_float = - | Plus - | Minus - | Times - | Power - | Divide - | LessThan - | LessThanOrEqual - | GreaterThan - | GreaterThanOrEqual - | Equals - | NotEquals; + - A fast_equal function that compares two terms for equality, it performs + structural equality except for the case of closures, where it just compares + the id of the closure. + */ +module rec Any: { [@deriving (show({with_path: false}), sexp, yojson)] - type op_bin_string = - | Concat - | Equals; + type t = + | Exp(Exp.t) + | Pat(Pat.t) + | Typ(Typ.t) + | TPat(TPat.t) + | Rul(Rul.t) + | Nul(unit) + | Any(unit); - [@deriving (show({with_path: false}), sexp, yojson)] - type op_un = - | Meta(op_un_meta) - | Int(op_un_int) - | Bool(op_un_bool); + let map_term: + ( + ~f_exp: (Exp.t => Exp.t, Exp.t) => Exp.t=?, + ~f_pat: (Pat.t => Pat.t, Pat.t) => Pat.t=?, + ~f_typ: (Typ.t => Typ.t, Typ.t) => Typ.t=?, + ~f_tpat: (TPat.t => TPat.t, TPat.t) => TPat.t=?, + ~f_rul: (Rul.t => Rul.t, Rul.t) => Rul.t=?, + ~f_any: (Any.t => Any.t, Any.t) => Any.t=?, + t + ) => + t; + let fast_equal: (t, t) => bool; +} = { [@deriving (show({with_path: false}), sexp, yojson)] - type op_bin = - | Int(op_bin_int) - | Float(op_bin_float) - | Bool(op_bin_bool) - | String(op_bin_string); + type t = + | Exp(Exp.t) + | Pat(Pat.t) + | Typ(Typ.t) + | TPat(TPat.t) + | Rul(Rul.t) + | Nul(unit) + | Any(unit); - [@deriving (show({with_path: false}), sexp, yojson)] - type cls = - | Invalid - | EmptyHole - | MultiHole - | Triv - | Bool - | Int - | Float - | String - | ListLit - | Constructor - | Fun - | TypFun - | Tuple - | Var - | Let - | TyAlias - | Ap - | TypAp - | If - | Seq - | Test - | Filter - | Parens - | Cons - | ListConcat - | UnOp(op_un) - | BinOp(op_bin) - | Match; + let map_term = + ( + ~f_exp=continue, + ~f_pat=continue, + ~f_typ=continue, + ~f_tpat=continue, + ~f_rul=continue, + ~f_any=continue, + x, + ) => { + let rec_call = y => + switch (y) { + | Exp(x) => + Exp(Exp.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any, x)) + | Pat(x) => + Pat(Pat.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any, x)) + | Typ(x) => + Typ(Typ.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any, x)) + | TPat(x) => + TPat( + TPat.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any, x), + ) + | Rul(x) => + Rul(Rul.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any, x)) + | Nul () => Nul() + | Any () => Any() + }; + x |> f_any(rec_call); + }; + let fast_equal = (x, y) => + switch (x, y) { + | (Exp(x), Exp(y)) => Exp.fast_equal(x, y) + | (Pat(x), Pat(y)) => Pat.fast_equal(x, y) + | (Typ(x), Typ(y)) => Typ.fast_equal(x, y) + | (TPat(x), TPat(y)) => TPat.fast_equal(x, y) + | (Rul(x), Rul(y)) => Rul.fast_equal(x, y) + | (Nul (), Nul ()) => true + | (Any (), Any ()) => true + | (Exp(_), _) + | (Pat(_), _) + | (Typ(_), _) + | (TPat(_), _) + | (Rul(_), _) + | (Nul (), _) + | (Any (), _) => false + }; +} +and Exp: { [@deriving (show({with_path: false}), sexp, yojson)] type deferral_position = | InAp @@ -143,141 +136,65 @@ and UExp: { | Invalid(string) | EmptyHole | MultiHole(list(Any.t)) - | Triv + | DynamicErrorHole(t, InvalidOperationError.t) + | FailedCast(t, Typ.t, Typ.t) | Deferral(deferral_position) + | Undefined | Bool(bool) | Int(int) | Float(float) | String(string) | ListLit(list(t)) - | Constructor(string) - | Fun(UPat.t, t) - | TypFun(UTPat.t, t) + | Constructor(string, Typ.t) // Typ.t field is only meaningful in dynamic expressions + | Fun( + Pat.t, + t, + [@show.opaque] option(ClosureEnvironment.t), + option(Var.t), + ) + | TypFun(TPat.t, t, option(Var.t)) | Tuple(list(t)) | Var(Var.t) - | Let(UPat.t, t, t) - | Module(UPat.t, t, t) + | Module(Pat.t, t, t) | Dot(t, t) - | TyAlias(UTPat.t, UTyp.t, t) - | Ap(t, t) - | TypAp(t, UTyp.t) + | Let(Pat.t, t, t) + | FixF(Pat.t, t, option(ClosureEnvironment.t)) + | TyAlias(TPat.t, Typ.t, t) + | Ap(Operators.ap_direction, t, t) + | TypAp(t, Typ.t) | DeferredAp(t, list(t)) - | Pipeline(t, t) | If(t, t, t) | Seq(t, t) | Test(t) - | Filter(FilterAction.t, t, t) + | Filter(StepperFilterKind.t, t) + | Closure([@show.opaque] ClosureEnvironment.t, t) | Parens(t) // ( | Cons(t, t) | ListConcat(t, t) - | UnOp(op_un, t) - | BinOp(op_bin, t, t) - | Match(t, list((UPat.t, t))) - and t = { - // invariant: nonempty - ids: list(Id.t), - term, - }; + | UnOp(Operators.op_un, t) + | BinOp(Operators.op_bin, t, t) + | BuiltinFun(string) + | Match(t, list((Pat.t, t))) + /* INVARIANT: in dynamic expressions, casts must be between + two consistent types. Both types should be normalized in + dynamics for the cast calculus to work right. */ + | Cast(t, Typ.t, Typ.t) // first Typ.t field is only meaningful in dynamic expressions + and t = IdTagged.t(term); - let bool_op_to_string: op_bin_bool => string; - let int_op_to_string: op_bin_int => string; - let float_op_to_string: op_bin_float => string; - let string_op_to_string: op_bin_string => string; -} = { - [@deriving (show({with_path: false}), sexp, yojson)] - type op_un_bool = - | Not; - - [@deriving (show({with_path: false}), sexp, yojson)] - type op_un_meta = - | Unquote; - - [@deriving (show({with_path: false}), sexp, yojson)] - type op_un_int = - | Minus; - - [@deriving (show({with_path: false}), sexp, yojson)] - type op_bin_bool = - | And - | Or; - - [@deriving (show({with_path: false}), sexp, yojson)] - type op_bin_int = - | Plus - | Minus - | Times - | Power - | Divide - | LessThan - | LessThanOrEqual - | GreaterThan - | GreaterThanOrEqual - | Equals - | NotEquals; - - [@deriving (show({with_path: false}), sexp, yojson)] - type op_bin_float = - | Plus - | Minus - | Times - | Power - | Divide - | LessThan - | LessThanOrEqual - | GreaterThan - | GreaterThanOrEqual - | Equals - | NotEquals; - - [@deriving (show({with_path: false}), sexp, yojson)] - type op_bin_string = - | Concat - | Equals; - - [@deriving (show({with_path: false}), sexp, yojson)] - type op_un = - | Meta(op_un_meta) - | Int(op_un_int) - | Bool(op_un_bool); - - [@deriving (show({with_path: false}), sexp, yojson)] - type op_bin = - | Int(op_bin_int) - | Float(op_bin_float) - | Bool(op_bin_bool) - | String(op_bin_string); - - [@deriving (show({with_path: false}), sexp, yojson)] - type cls = - | Invalid - | EmptyHole - | MultiHole - | Triv - | Bool - | Int - | Float - | String - | ListLit - | Constructor - | Fun - | TypFun - | Tuple - | Var - | Let - | TyAlias - | Ap - | TypAp - | If - | Seq - | Test - | Filter - | Parens - | Cons - | ListConcat - | UnOp(op_un) - | BinOp(op_bin) - | Match; + let map_term: + ( + ~f_exp: (Exp.t => Exp.t, Exp.t) => Exp.t=?, + ~f_pat: (Pat.t => Pat.t, Pat.t) => Pat.t=?, + ~f_typ: (Typ.t => Typ.t, Typ.t) => Typ.t=?, + ~f_tpat: (TPat.t => TPat.t, TPat.t) => TPat.t=?, + ~f_rul: (Rul.t => Rul.t, Rul.t) => Rul.t=?, + ~f_any: (Any.t => Any.t, Any.t) => Any.t=?, + t + ) => + t; + let fast_equal: (t, t) => bool; +} = { [@deriving (show({with_path: false}), sexp, yojson)] type deferral_position = | InAp @@ -288,89 +205,252 @@ and UExp: { | Invalid(string) | EmptyHole | MultiHole(list(Any.t)) - | Triv + | DynamicErrorHole(t, InvalidOperationError.t) + | FailedCast(t, Typ.t, Typ.t) | Deferral(deferral_position) + | Undefined | Bool(bool) | Int(int) | Float(float) | String(string) | ListLit(list(t)) - | Constructor(string) - | Fun(UPat.t, t) - | TypFun(UTPat.t, t) + | Constructor(string, Typ.t) + | Fun( + Pat.t, + t, + [@show.opaque] option(ClosureEnvironment.t), + option(Var.t), + ) + | TypFun(TPat.t, t, option(string)) | Tuple(list(t)) | Var(Var.t) - | Let(UPat.t, t, t) - | Module(UPat.t, t, t) + | Module(Pat.t, t, t) | Dot(t, t) - | TyAlias(UTPat.t, UTyp.t, t) - | Ap(t, t) - | TypAp(t, UTyp.t) + | Let(Pat.t, t, t) + | FixF(Pat.t, t, [@show.opaque] option(ClosureEnvironment.t)) + | TyAlias(TPat.t, Typ.t, t) + | Ap(Operators.ap_direction, t, t) // note: function is always first then argument; even in pipe mode + | TypAp(t, Typ.t) | DeferredAp(t, list(t)) - | Pipeline(t, t) | If(t, t, t) | Seq(t, t) | Test(t) - | Filter(FilterAction.t, t, t) - | Parens(t) // ( + | Filter(StepperFilterKind.t, t) + | Closure([@show.opaque] ClosureEnvironment.t, t) + | Parens(t) | Cons(t, t) | ListConcat(t, t) - | UnOp(op_un, t) - | BinOp(op_bin, t, t) - | Match(t, list((UPat.t, t))) - and t = { - // invariant: nonempty - ids: list(Id.t), - term, - }; - - let bool_op_to_string = (op: op_bin_bool): string => { - switch (op) { - | And => "&&" - | Or => "||" - }; - }; - - let int_op_to_string = (op: op_bin_int): string => { - switch (op) { - | Plus => "+" - | Minus => "-" - | Times => "*" - | Power => "**" - | Divide => "/" - | LessThan => "<" - | LessThanOrEqual => "<=" - | GreaterThan => ">" - | GreaterThanOrEqual => ">=" - | Equals => "==" - | NotEquals => "!=" - }; - }; + | UnOp(Operators.op_un, t) + | BinOp(Operators.op_bin, t, t) + | BuiltinFun(string) /// Doesn't currently have a distinguishable syntax + | Match(t, list((Pat.t, t))) + | Cast(t, Typ.t, Typ.t) + and t = IdTagged.t(term); - let float_op_to_string = (op: op_bin_float): string => { - switch (op) { - | Plus => "+." - | Minus => "-." - | Times => "*." - | Power => "**." - | Divide => "/." - | LessThan => "<." - | LessThanOrEqual => "<=." - | GreaterThan => ">." - | GreaterThanOrEqual => ">=." - | Equals => "==." - | NotEquals => "!=." + let map_term = + ( + ~f_exp=continue, + ~f_pat=continue, + ~f_typ=continue, + ~f_tpat=continue, + ~f_rul=continue, + ~f_any=continue, + x, + ) => { + let exp_map_term = + Exp.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let pat_map_term = + Pat.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let typ_map_term = + Typ.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let tpat_map_term = + TPat.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let any_map_term = + Any.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let flt_map_term = + StepperFilterKind.map_term( + ~f_exp, + ~f_pat, + ~f_typ, + ~f_tpat, + ~f_rul, + ~f_any, + ); + let rec_call = ({term, _} as exp: t) => { + ...exp, + term: + switch (term) { + | EmptyHole + | Invalid(_) + | Bool(_) + | Int(_) + | Float(_) + | Constructor(_) + | String(_) + | Deferral(_) + | Var(_) + | Undefined => term + | MultiHole(things) => MultiHole(List.map(any_map_term, things)) + | DynamicErrorHole(e, err) => DynamicErrorHole(exp_map_term(e), err) + | FailedCast(e, t1, t2) => FailedCast(exp_map_term(e), t1, t2) + | ListLit(ts) => ListLit(List.map(exp_map_term, ts)) + | Fun(p, e, env, f) => + Fun(pat_map_term(p), exp_map_term(e), env, f) + | TypFun(tp, e, f) => TypFun(tpat_map_term(tp), exp_map_term(e), f) + | Tuple(xs) => Tuple(List.map(exp_map_term, xs)) + | Let(p, e1, e2) => + Let(pat_map_term(p), exp_map_term(e1), exp_map_term(e2)) + | FixF(p, e, env) => FixF(pat_map_term(p), exp_map_term(e), env) + | TyAlias(tp, t, e) => + TyAlias(tpat_map_term(tp), typ_map_term(t), exp_map_term(e)) + | Ap(op, e1, e2) => Ap(op, exp_map_term(e1), exp_map_term(e2)) + | TypAp(e, t) => TypAp(exp_map_term(e), typ_map_term(t)) + | DeferredAp(e, es) => + DeferredAp(exp_map_term(e), List.map(exp_map_term, es)) + | If(e1, e2, e3) => + If(exp_map_term(e1), exp_map_term(e2), exp_map_term(e3)) + | Seq(e1, e2) => Seq(exp_map_term(e1), exp_map_term(e2)) + | Test(e) => Test(exp_map_term(e)) + | Filter(f, e) => Filter(flt_map_term(f), exp_map_term(e)) + | Closure(env, e) => Closure(env, exp_map_term(e)) + | Parens(e) => Parens(exp_map_term(e)) + | Cons(e1, e2) => Cons(exp_map_term(e1), exp_map_term(e2)) + | ListConcat(e1, e2) => + ListConcat(exp_map_term(e1), exp_map_term(e2)) + | UnOp(op, e) => UnOp(op, exp_map_term(e)) + | BinOp(op, e1, e2) => + BinOp(op, exp_map_term(e1), exp_map_term(e2)) + | BuiltinFun(str) => BuiltinFun(str) + | Match(e, rls) => + Match( + exp_map_term(e), + List.map( + ((p, e)) => (pat_map_term(p), exp_map_term(e)), + rls, + ), + ) + | Cast(e, t1, t2) => Cast(exp_map_term(e), t1, t2) + }, }; + x |> f_exp(rec_call); }; - let string_op_to_string = (op: op_bin_string): string => { - switch (op) { - | Concat => "++" - | Equals => "$==" + let rec fast_equal = (e1, e2) => + switch (e1 |> IdTagged.term_of, e2 |> IdTagged.term_of) { + | (DynamicErrorHole(x, _), _) + | (Parens(x), _) => fast_equal(x, e2) + | (_, DynamicErrorHole(x, _)) + | (_, Parens(x)) => fast_equal(e1, x) + | (EmptyHole, EmptyHole) => true + | (Undefined, Undefined) => true + | (Invalid(s1), Invalid(s2)) => s1 == s2 + | (MultiHole(xs), MultiHole(ys)) when List.length(xs) == List.length(ys) => + List.equal(Any.fast_equal, xs, ys) + | (FailedCast(e1, t1, t2), FailedCast(e2, t3, t4)) => + Exp.fast_equal(e1, e2) + && Typ.fast_equal(t1, t3) + && Typ.fast_equal(t2, t4) + | (Deferral(d1), Deferral(d2)) => d1 == d2 + | (Bool(b1), Bool(b2)) => b1 == b2 + | (Int(i1), Int(i2)) => i1 == i2 + | (Float(f1), Float(f2)) => f1 == f2 + | (String(s1), String(s2)) => s1 == s2 + | (ListLit(xs), ListLit(ys)) => + List.length(xs) == List.length(ys) && List.equal(fast_equal, xs, ys) + | (Constructor(c1, ty1), Constructor(c2, ty2)) => + c1 == c2 && Typ.fast_equal(ty1, ty2) + | (Fun(p1, e1, env1, _), Fun(p2, e2, env2, _)) => + Pat.fast_equal(p1, p2) + && fast_equal(e1, e2) + && Option.equal(ClosureEnvironment.id_equal, env1, env2) + | (TypFun(tp1, e1, _), TypFun(tp2, e2, _)) => + TPat.fast_equal(tp1, tp2) && fast_equal(e1, e2) + | (Tuple(xs), Tuple(ys)) => + List.length(xs) == List.length(ys) && List.equal(fast_equal, xs, ys) + | (Var(v1), Var(v2)) => v1 == v2 + | (Let(p1, e1, e2), Let(p2, e3, e4)) => + Pat.fast_equal(p1, p2) && fast_equal(e1, e3) && fast_equal(e2, e4) + | (FixF(p1, e1, c1), FixF(p2, e2, c2)) => + Pat.fast_equal(p1, p2) + && fast_equal(e1, e2) + && Option.equal(ClosureEnvironment.id_equal, c1, c2) + | (TyAlias(tp1, t1, e1), TyAlias(tp2, t2, e2)) => + TPat.fast_equal(tp1, tp2) + && Typ.fast_equal(t1, t2) + && fast_equal(e1, e2) + | (Ap(d1, e1, e2), Ap(d2, e3, e4)) => + d1 == d2 && fast_equal(e1, e3) && fast_equal(e2, e4) + | (TypAp(e1, t1), TypAp(e2, t2)) => + fast_equal(e1, e2) && Typ.fast_equal(t1, t2) + | (DeferredAp(e1, es1), DeferredAp(e2, es2)) => + List.length(es1) == List.length(es2) + && fast_equal(e1, e2) + && List.equal(fast_equal, es1, es2) + | (If(e1, e2, e3), If(e4, e5, e6)) => + fast_equal(e1, e4) && fast_equal(e2, e5) && fast_equal(e3, e6) + | (Seq(e1, e2), Seq(e3, e4)) => + fast_equal(e1, e3) && fast_equal(e2, e4) + | (Test(e1), Test(e2)) => fast_equal(e1, e2) + | (Filter(f1, e1), Filter(f2, e2)) => + StepperFilterKind.fast_equal(f1, f2) && fast_equal(e1, e2) + | (Closure(c1, e1), Closure(c2, e2)) => + ClosureEnvironment.id_equal(c1, c2) && fast_equal(e1, e2) + | (Cons(e1, e2), Cons(e3, e4)) => + fast_equal(e1, e3) && fast_equal(e2, e4) + | (ListConcat(e1, e2), ListConcat(e3, e4)) => + fast_equal(e1, e3) && fast_equal(e2, e4) + | (UnOp(o1, e1), UnOp(o2, e2)) => o1 == o2 && fast_equal(e1, e2) + | (BinOp(o1, e1, e2), BinOp(o2, e3, e4)) => + o1 == o2 && fast_equal(e1, e3) && fast_equal(e2, e4) + | (BuiltinFun(f1), BuiltinFun(f2)) => f1 == f2 + | (Match(e1, rls1), Match(e2, rls2)) => + fast_equal(e1, e2) + && List.length(rls1) == List.length(rls2) + && List.for_all2( + ((p1, e1), (p2, e2)) => + Pat.fast_equal(p1, p2) && fast_equal(e1, e2), + rls1, + rls2, + ) + | (Cast(e1, t1, t2), Cast(e2, t3, t4)) => + fast_equal(e1, e2) && Typ.fast_equal(t1, t3) && Typ.fast_equal(t2, t4) + | (Invalid(_), _) + | (FailedCast(_), _) + | (Deferral(_), _) + | (Bool(_), _) + | (Int(_), _) + | (Float(_), _) + | (String(_), _) + | (ListLit(_), _) + | (Constructor(_), _) + | (Fun(_), _) + | (TypFun(_), _) + | (Tuple(_), _) + | (Var(_), _) + | (Let(_), _) + | (FixF(_), _) + | (TyAlias(_), _) + | (Ap(_), _) + | (TypAp(_), _) + | (DeferredAp(_), _) + | (If(_), _) + | (Seq(_), _) + | (Test(_), _) + | (Filter(_), _) + | (Closure(_), _) + | (Cons(_), _) + | (ListConcat(_), _) + | (UnOp(_), _) + | (BinOp(_), _) + | (BuiltinFun(_), _) + | (Match(_), _) + | (Cast(_), _) + | (MultiHole(_), _) + | (EmptyHole, _) + | (Undefined, _) => false }; - }; } -and UPat: { +and Pat: { [@deriving (show({with_path: false}), sexp, yojson)] type term = | Invalid(string) @@ -381,20 +461,29 @@ and UPat: { | Float(float) | Bool(bool) | String(string) - | Triv | ListLit(list(t)) - | Constructor(string) + | Constructor(string, Typ.t) // Typ.t field is only meaningful in dynamic patterns | Cons(t, t) | Var(Var.t) | Tuple(list(t)) | Parens(t) | Ap(t, t) - | TypeAnn(t, UTyp.t) - | TyAlias(UTPat.t, UTyp.t) - and t = { - ids: list(Id.t), - term, - }; + | Cast(t, Typ.t, Typ.t) // The second Typ.t field is only meaningful in dynamic patterns + and t = IdTagged.t(term); + + let map_term: + ( + ~f_exp: (Exp.t => Exp.t, Exp.t) => Exp.t=?, + ~f_pat: (Pat.t => Pat.t, Pat.t) => Pat.t=?, + ~f_typ: (Typ.t => Typ.t, Typ.t) => Typ.t=?, + ~f_tpat: (TPat.t => TPat.t, TPat.t) => TPat.t=?, + ~f_rul: (Rul.t => Rul.t, Rul.t) => Rul.t=?, + ~f_any: (Any.t => Any.t, Any.t) => Any.t=?, + t + ) => + t; + + let fast_equal: (t, t) => bool; } = { [@deriving (show({with_path: false}), sexp, yojson)] type term = @@ -406,121 +495,746 @@ and UPat: { | Float(float) | Bool(bool) | String(string) - | Triv | ListLit(list(t)) - | Constructor(string) + | Constructor(string, Typ.t) | Cons(t, t) | Var(Var.t) | Tuple(list(t)) | Parens(t) | Ap(t, t) - | TypeAnn(t, UTyp.t) - | TyAlias(UTPat.t, UTyp.t) - and t = { - ids: list(Id.t), - term, + | Cast(t, Typ.t, Typ.t) // The second one is hidden from the user + and t = IdTagged.t(term); + + let map_term = + ( + ~f_exp=continue, + ~f_pat=continue, + ~f_typ=continue, + ~f_tpat=continue, + ~f_rul=continue, + ~f_any=continue, + x, + ) => { + let pat_map_term = + Pat.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let typ_map_term = + Typ.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let any_map_term = + Any.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let rec_call = ({term, _} as exp: t) => { + ...exp, + term: + switch (term) { + | EmptyHole + | Invalid(_) + | Wild + | Bool(_) + | Int(_) + | Float(_) + | Constructor(_) + | String(_) + | Var(_) => term + | MultiHole(things) => MultiHole(List.map(any_map_term, things)) + | ListLit(ts) => ListLit(List.map(pat_map_term, ts)) + | Ap(e1, e2) => Ap(pat_map_term(e1), pat_map_term(e2)) + | Cons(e1, e2) => Cons(pat_map_term(e1), pat_map_term(e2)) + | Tuple(xs) => Tuple(List.map(pat_map_term, xs)) + | Parens(e) => Parens(pat_map_term(e)) + | Cast(e, t1, t2) => + Cast(pat_map_term(e), typ_map_term(t1), typ_map_term(t2)) + }, + }; + x |> f_pat(rec_call); }; + + let rec fast_equal = (p1, p2) => + switch (p1 |> IdTagged.term_of, p2 |> IdTagged.term_of) { + | (Parens(x), _) => fast_equal(x, p2) + | (_, Parens(x)) => fast_equal(p1, x) + | (EmptyHole, EmptyHole) => true + | (MultiHole(xs), MultiHole(ys)) => + List.length(xs) == List.length(ys) + && List.equal(Any.fast_equal, xs, ys) + | (Invalid(s1), Invalid(s2)) => s1 == s2 + | (Wild, Wild) => true + | (Bool(b1), Bool(b2)) => b1 == b2 + | (Int(i1), Int(i2)) => i1 == i2 + | (Float(f1), Float(f2)) => f1 == f2 + | (String(s1), String(s2)) => s1 == s2 + | (Constructor(c1, t1), Constructor(c2, t2)) => + c1 == c2 && Typ.fast_equal(t1, t2) + | (Var(v1), Var(v2)) => v1 == v2 + | (ListLit(xs), ListLit(ys)) => + List.length(xs) == List.length(ys) && List.equal(fast_equal, xs, ys) + | (Cons(x1, y1), Cons(x2, y2)) => + fast_equal(x1, x2) && fast_equal(y1, y2) + | (Tuple(xs), Tuple(ys)) => + List.length(xs) == List.length(ys) && List.equal(fast_equal, xs, ys) + | (Ap(x1, y1), Ap(x2, y2)) => fast_equal(x1, x2) && fast_equal(y1, y2) + | (Cast(x1, t1, t2), Cast(x2, u1, u2)) => + fast_equal(x1, x2) && Typ.fast_equal(t1, u1) && Typ.fast_equal(t2, u2) + | (EmptyHole, _) + | (MultiHole(_), _) + | (Invalid(_), _) + | (Wild, _) + | (Bool(_), _) + | (Int(_), _) + | (Float(_), _) + | (String(_), _) + | (ListLit(_), _) + | (Constructor(_), _) + | (Cons(_), _) + | (Var(_), _) + | (Tuple(_), _) + | (Ap(_), _) + | (Cast(_), _) => false + }; } -and UTyp: { +and Typ: { [@deriving (show({with_path: false}), sexp, yojson)] - type term = + type type_hole = | Invalid(string) | EmptyHole - | MultiHole(list(Any.t)) + | MultiHole(list(Any.t)); + + /* TYPE_PROVENANCE: From whence does an unknown type originate? + Is it generated from an unannotated pattern variable (SynSwitch), + a pattern variable annotated with a type hole (TypeHole), or + generated by an internal judgement (Internal)? */ + [@deriving (show({with_path: false}), sexp, yojson)] + type type_provenance = + | SynSwitch + | Hole(type_hole) + | Internal; + + type module_typ = { + inner_ctx: Ctx.t, + incomplete: bool, + }; + + [@deriving (show({with_path: false}), sexp, yojson)] + type term = + | Unknown(Typ.type_provenance) | Int | Float | Bool | String - | List(t) | Var(string) - | Constructor(string) + | List(t) | Arrow(t, t) - | Tuple(list(t)) + | Sum(ConstructorMap.t(t)) + | Prod(list(t)) + | Module(module_typ) + | Member(Token.t, t) | Parens(t) - | Module(UPat.t) | Ap(t, t) - | Dot(t, t) - | Sum(list(variant)) - | Forall(UTPat.t, t) - | Rec(UTPat.t, t) - and variant = - | Variant(Constructor.t, list(Id.t), option(t)) - | BadEntry(t) - and t = { - ids: list(Id.t), - term, - }; + | Rec(TPat.t, t) + | Forall(TPat.t, t) + and t = IdTagged.t(term); + + type sum_map = ConstructorMap.t(t); + + let map_term: + ( + ~f_exp: (Exp.t => Exp.t, Exp.t) => Exp.t=?, + ~f_pat: (Pat.t => Pat.t, Pat.t) => Pat.t=?, + ~f_typ: (Typ.t => Typ.t, Typ.t) => Typ.t=?, + ~f_tpat: (TPat.t => TPat.t, TPat.t) => TPat.t=?, + ~f_rul: (Rul.t => Rul.t, Rul.t) => Rul.t=?, + ~f_any: (Any.t => Any.t, Any.t) => Any.t=?, + t + ) => + t; + + let subst: (t, TPat.t, t) => t; + + let fast_equal: (t, t) => bool; } = { [@deriving (show({with_path: false}), sexp, yojson)] - type term = + type type_hole = | Invalid(string) | EmptyHole - | MultiHole(list(Any.t)) + | MultiHole(list(Any.t)); + + /* TYPE_PROVENANCE: From whence does an unknown type originate? + Is it generated from an unannotated pattern variable (SynSwitch), + a pattern variable annotated with a type hole (TypeHole), or + generated by an internal judgement (Internal)? */ + [@deriving (show({with_path: false}), sexp, yojson)] + type type_provenance = + | SynSwitch + | Hole(type_hole) + | Internal; + + type module_typ = { + inner_ctx: Ctx.t, + incomplete: bool, + }; + + [@deriving (show({with_path: false}), sexp, yojson)] + type term = + | Unknown(Typ.type_provenance) | Int | Float | Bool | String - | List(t) | Var(string) - | Constructor(string) + | List(t) | Arrow(t, t) - | Tuple(list(t)) + | Sum(ConstructorMap.t(t)) + | Prod(list(t)) + | Module(module_typ) + | Member(Token.t, t) | Parens(t) - | Module(UPat.t) | Ap(t, t) - | Dot(t, t) - | Sum(list(variant)) - | Forall(UTPat.t, t) - | Rec(UTPat.t, t) - and variant = - | Variant(Constructor.t, list(Id.t), option(t)) - | BadEntry(t) - and t = { - ids: list(Id.t), - term, + | Rec(TPat.t, t) + | Forall(TPat.t, t) + and t = IdTagged.t(term); + + type sum_map = ConstructorMap.t(t); + + let map_term = + ( + ~f_exp=continue, + ~f_pat=continue, + ~f_typ=continue, + ~f_tpat=continue, + ~f_rul=continue, + ~f_any=continue, + x, + ) => { + let typ_map_term = + Typ.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let any_map_term = + Any.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let tpat_map_term = + TPat.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let rec_call = ({term, _} as exp: t) => { + ...exp, + term: + switch (term) { + | Unknown(Hole(EmptyHole)) + | Unknown(Hole(Invalid(_))) + | Unknown(SynSwitch) + | Unknown(Internal) + | Bool + | Int + | Float + | String + | Var(_) => term + | List(t) => List(typ_map_term(t)) + | Unknown(Hole(MultiHole(things))) => + Unknown(Hole(MultiHole(List.map(any_map_term, things)))) + | Ap(e1, e2) => Ap(typ_map_term(e1), typ_map_term(e2)) + | Prod(xs) => Prod(List.map(typ_map_term, xs)) + | Parens(e) => Parens(typ_map_term(e)) + | Arrow(t1, t2) => Arrow(typ_map_term(t1), typ_map_term(t2)) + | Sum(variants) => + Sum( + List.map( + fun + | ConstructorMap.Variant(c, ids, t) => + ConstructorMap.Variant(c, ids, Option.map(typ_map_term, t)) + | ConstructorMap.BadEntry(t) => + ConstructorMap.BadEntry(typ_map_term(t)), + variants, + ), + ) + | Rec(tp, t) => Rec(tpat_map_term(tp), typ_map_term(t)) + | Forall(tp, t) => Forall(tpat_map_term(tp), typ_map_term(t)) + }, + }; + x |> f_typ(rec_call); }; + + let rec subst = (s: t, x: TPat.t, ty: t) => { + switch (TPat.tyvar_of_utpat(x)) { + | Some(str) => + let (term, rewrap) = IdTagged.unwrap(ty); + switch (term) { + | Int => Int |> rewrap + | Float => Float |> rewrap + | Bool => Bool |> rewrap + | String => String |> rewrap + | Unknown(prov) => Unknown(prov) |> rewrap + | Arrow(ty1, ty2) => + Arrow(subst(s, x, ty1), subst(s, x, ty2)) |> rewrap + | Prod(tys) => Prod(List.map(subst(s, x), tys)) |> rewrap + | Sum(sm) => + Sum(ConstructorMap.map(Option.map(subst(s, x)), sm)) |> rewrap + | Forall(tp2, ty) + when TPat.tyvar_of_utpat(x) == TPat.tyvar_of_utpat(tp2) => + Forall(tp2, ty) |> rewrap + | Forall(tp2, ty) => Forall(tp2, subst(s, x, ty)) |> rewrap + | Rec(tp2, ty) when TPat.tyvar_of_utpat(x) == TPat.tyvar_of_utpat(tp2) => + Rec(tp2, ty) |> rewrap + | Rec(tp2, ty) => Rec(tp2, subst(s, x, ty)) |> rewrap + | List(ty) => List(subst(s, x, ty)) |> rewrap + | Var(y) => str == y ? s : Var(y) |> rewrap + | Module({inner_ctx, incomplete}) => + let ctx_entry_subst = (e: Ctx.entry): Ctx.entry => { + switch (e) { + | VarEntry(t) => VarEntry({...t, typ: subst(s, x, t.typ)}) + | ConstructorEntry(t) => + ConstructorEntry({...t, typ: subst(s, x, t.typ)}) + | TVarEntry(_) => e + }; + }; + Module({ + inner_ctx: List.map(ctx_entry_subst, inner_ctx), + incomplete, + }); + | Member(name, ty) => Member(name, subst(s, x, ty)) + | Parens(ty) => Parens(subst(s, x, ty)) |> rewrap + | Ap(t1, t2) => Ap(subst(s, x, t1), subst(s, x, t2)) |> rewrap + }; + | None => ty + }; + }; + + let rec weak_head_normalize = (ctx: Ctx.t, ty: t): t => + switch (term_of(ty)) { + | Parens(t) => weak_head_normalize(ctx, t) + | Var(x) => + switch (Ctx.lookup_alias(ctx, x)) { + | Some(ty) => weak_head_normalize(ctx, ty) + | None => ty + } + | _ => ty + }; + + /* Type Equality: This coincides with alpha equivalence for normalized types. + Other types may be equivalent but this will not detect so if they are not normalized. */ + + let rec eq_internal = (n: int, t1: t, t2: t) => { + switch (IdTagged.term_of(t1), IdTagged.term_of(t2)) { + | (Parens(t1), _) => eq_internal(n, t1, t2) + | (_, Parens(t2)) => eq_internal(n, t1, t2) + | (Member(_, ty1), ty2) => eq_internal(n, ty1, ty2) + | (ty1, Member(_, ty2)) => eq_internal(n, ty1, ty2) + | (Module(ctx1), Module(ctx2)) => + let entry_equal = (e1: Ctx.entry, e2: Ctx.entry) => { + switch (e1, e2) { + | ( + VarEntry({typ: t1, name: n1, _}), + VarEntry({typ: t2, name: n2, _}), + ) => + eq_internal(n, t1, t2) && n1 == n2 + | ( + TVarEntry({kind: t1, name: n1, _}), + TVarEntry({kind: t2, name: n2, _}), + ) => + t1 == t2 && n1 == n2 + | ( + ConstructorEntry({typ: t1, name: n1, _}), + ConstructorEntry({typ: t2, name: n2, _}), + ) => + eq_internal(n, t1, t2) && n1 == n2 + | _ => false + }; + }; + List.equal(entry_equal, ctx1.inner_ctx, ctx2.inner_ctx) + && ctx1.incomplete == ctx2.incomplete; + | (Module(_), _) => false + | (Rec(x1, t1), Rec(x2, t2)) + | (Forall(x1, t1), Forall(x2, t2)) => + let alpha_subst = + subst({ + term: Var("=" ++ string_of_int(n)), + copied: false, + ids: [Id.invalid], + }); + eq_internal(n + 1, alpha_subst(x1, t1), alpha_subst(x2, t2)); + | (Rec(_), _) => false + | (Forall(_), _) => false + | (Int, Int) => true + | (Int, _) => false + | (Float, Float) => true + | (Float, _) => false + | (Bool, Bool) => true + | (Bool, _) => false + | (String, String) => true + | (String, _) => false + | (Ap(t1, t2), Ap(t1', t2')) => + eq_internal(n, t1, t1') && eq_internal(n, t2, t2') + | (Ap(_), _) => false + | (Unknown(_), Unknown(_)) => true + | (Unknown(_), _) => false + | (Arrow(t1, t2), Arrow(t1', t2')) => + eq_internal(n, t1, t1') && eq_internal(n, t2, t2') + | (Arrow(_), _) => false + | (Prod(tys1), Prod(tys2)) => List.equal(eq_internal(n), tys1, tys2) + | (Prod(_), _) => false + | (List(t1), List(t2)) => eq_internal(n, t1, t2) + | (List(_), _) => false + | (Sum(sm1), Sum(sm2)) => + /* Does not normalize the types. */ + ConstructorMap.equal(eq_internal(n), sm1, sm2) + | (Sum(_), _) => false + | (Var(n1), Var(n2)) => n1 == n2 + | (Var(_), _) => false + }; + }; + + let fast_equal = eq_internal(0); } -and UTPat: { +and TPat: { [@deriving (show({with_path: false}), sexp, yojson)] type term = | Invalid(string) | EmptyHole | MultiHole(list(Any.t)) - | Var(TypVar.t) - and t = { - ids: list(Id.t), - term, - }; + | Var(string) + and t = IdTagged.t(term); + + let map_term: + ( + ~f_exp: (Exp.t => Exp.t, Exp.t) => Exp.t=?, + ~f_pat: (Pat.t => Pat.t, Pat.t) => Pat.t=?, + ~f_typ: (Typ.t => Typ.t, Typ.t) => Typ.t=?, + ~f_tpat: (TPat.t => TPat.t, TPat.t) => TPat.t=?, + ~f_rul: (Rul.t => Rul.t, Rul.t) => Rul.t=?, + ~f_any: (Any.t => Any.t, Any.t) => Any.t=?, + t + ) => + t; + + let tyvar_of_utpat: t => option(string); + + let fast_equal: (t, t) => bool; } = { [@deriving (show({with_path: false}), sexp, yojson)] type term = | Invalid(string) | EmptyHole | MultiHole(list(Any.t)) - | Var(TypVar.t) - and t = { - ids: list(Id.t), - term, + | Var(string) + and t = IdTagged.t(term); + + let map_term = + ( + ~f_exp=continue, + ~f_pat=continue, + ~f_typ=continue, + ~f_tpat=continue, + ~f_rul=continue, + ~f_any=continue, + x, + ) => { + let any_map_term = + Any.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let rec_call = ({term, _} as exp: t) => { + ...exp, + term: + switch (term) { + | EmptyHole + | Invalid(_) + | Var(_) => term + | MultiHole(things) => MultiHole(List.map(any_map_term, things)) + }, + }; + x |> f_tpat(rec_call); }; + + let tyvar_of_utpat = ({term, _}: t) => + switch (term) { + | Var(x) => Some(x) + | _ => None + }; + + let fast_equal = (tp1: t, tp2: t) => + switch (tp1 |> IdTagged.term_of, tp2 |> IdTagged.term_of) { + | (EmptyHole, EmptyHole) => true + | (Invalid(s1), Invalid(s2)) => s1 == s2 + | (MultiHole(xs), MultiHole(ys)) => + List.length(xs) == List.length(ys) + && List.equal(Any.fast_equal, xs, ys) + | (Var(x), Var(y)) => x == y + | (EmptyHole, _) + | (Invalid(_), _) + | (MultiHole(_), _) + | (Var(_), _) => false + }; } -and URul: { +and Rul: { [@deriving (show({with_path: false}), sexp, yojson)] type term = | Invalid(string) | Hole(list(Any.t)) - | Rules(UExp.t, list((UPat.t, UExp.t))) - and t = { - ids: list(Id.t), - term, - }; + | Rules(Exp.t, list((Pat.t, Exp.t))) + and t = IdTagged.t(term); + + let map_term: + ( + ~f_exp: (Exp.t => Exp.t, Exp.t) => Exp.t=?, + ~f_pat: (Pat.t => Pat.t, Pat.t) => Pat.t=?, + ~f_typ: (Typ.t => Typ.t, Typ.t) => Typ.t=?, + ~f_tpat: (TPat.t => TPat.t, TPat.t) => TPat.t=?, + ~f_rul: (Rul.t => Rul.t, Rul.t) => Rul.t=?, + ~f_any: (Any.t => Any.t, Any.t) => Any.t=?, + t + ) => + t; + + let fast_equal: (t, t) => bool; } = { [@deriving (show({with_path: false}), sexp, yojson)] type term = | Invalid(string) | Hole(list(Any.t)) - | Rules(UExp.t, list((UPat.t, UExp.t))) - and t = { - ids: list(Id.t), - term, + | Rules(Exp.t, list((Pat.t, Exp.t))) + and t = IdTagged.t(term); + + let map_term = + ( + ~f_exp=continue, + ~f_pat=continue, + ~f_typ=continue, + ~f_tpat=continue, + ~f_rul=continue, + ~f_any=continue, + x, + ) => { + let exp_map_term = + Exp.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let pat_map_term = + Pat.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let any_map_term = + Any.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + let rec_call = ({term, _} as exp: t) => { + ...exp, + term: + switch (term) { + | Invalid(_) => term + | Hole(things) => Hole(List.map(any_map_term, things)) + | Rules(e, rls) => + Rules( + exp_map_term(e), + List.map( + ((p, e)) => (pat_map_term(p), exp_map_term(e)), + rls, + ), + ) + }, + }; + x |> f_rul(rec_call); + }; + + let fast_equal = (r1: t, r2: t) => + switch (r1 |> IdTagged.term_of, r2 |> IdTagged.term_of) { + | (Invalid(s1), Invalid(s2)) => s1 == s2 + | (Hole(xs), Hole(ys)) => + List.length(xs) == List.length(ys) + && List.equal(Any.fast_equal, xs, ys) + | (Rules(e1, rls1), Rules(e2, rls2)) => + Exp.fast_equal(e1, e2) + && List.length(rls1) == List.length(rls2) + && List.for_all2( + ((p1, e1), (p2, e2)) => + Pat.fast_equal(p1, p2) && Exp.fast_equal(e1, e2), + rls1, + rls2, + ) + | (Invalid(_), _) + | (Hole(_), _) + | (Rules(_), _) => false + }; +} + +and Environment: { + include + (module type of VarBstMap.Ordered) with + type t_('a) = VarBstMap.Ordered.t_('a); + + [@deriving (show({with_path: false}), sexp, yojson)] + type t = t_(Exp.t); +} = { + include VarBstMap.Ordered; + + [@deriving (show({with_path: false}), sexp, yojson)] + type t = t_(Exp.t); +} + +and ClosureEnvironment: { + [@deriving (show({with_path: false}), sexp, yojson)] + type t; + + let wrap: (Id.t, Environment.t) => t; + + let id_of: t => Id.t; + let map_of: t => Environment.t; + + let to_list: t => list((Var.t, Exp.t)); + + let of_environment: Environment.t => t; + + let id_equal: (t, t) => bool; + + let empty: t; + let is_empty: t => bool; + let length: t => int; + + let lookup: (t, Var.t) => option(Exp.t); + let contains: (t, Var.t) => bool; + let update: (Environment.t => Environment.t, t) => t; + let update_keep_id: (Environment.t => Environment.t, t) => t; + let extend: (t, (Var.t, Exp.t)) => t; + let extend_keep_id: (t, (Var.t, Exp.t)) => t; + let union: (t, t) => t; + let union_keep_id: (t, t) => t; + let map: (((Var.t, Exp.t)) => Exp.t, t) => t; + let map_keep_id: (((Var.t, Exp.t)) => Exp.t, t) => t; + let filter: (((Var.t, Exp.t)) => bool, t) => t; + let filter_keep_id: (((Var.t, Exp.t)) => bool, t) => t; + let fold: (((Var.t, Exp.t), 'b) => 'b, 'b, t) => 'b; + + let without_keys: (list(Var.t), t) => t; + + let placeholder: t; +} = { + module Inner: { + [@deriving (show({with_path: false}), sexp, yojson)] + type t; + + let wrap: (Id.t, Environment.t) => t; + + let id_of: t => Id.t; + let map_of: t => Environment.t; + } = { + [@deriving (show({with_path: false}), sexp, yojson)] + type t = (Id.t, Environment.t); + + let wrap = (ei, map): t => (ei, map); + + let id_of = ((ei, _)) => ei; + let map_of = ((_, map)) => map; + let (sexp_of_t, t_of_sexp) = + StructureShareSexp.structure_share_here(id_of, sexp_of_t, t_of_sexp); + }; + include Inner; + + let to_list = env => env |> map_of |> Environment.to_listo; + + let of_environment = map => { + let ei = Id.mk(); + wrap(ei, map); + }; + + /* Equals only needs to check environment id's (faster than structural equality + * checking.) */ + let id_equal = (env1, env2) => id_of(env1) == id_of(env2); + + let empty = Environment.empty |> of_environment; + + let is_empty = env => env |> map_of |> Environment.is_empty; + + let length = env => Environment.length(map_of(env)); + + let lookup = (env, x) => + env |> map_of |> (map => Environment.lookup(map, x)); + + let contains = (env, x) => + env |> map_of |> (map => Environment.contains(map, x)); + + let update = (f, env) => env |> map_of |> f |> of_environment; + + let update_keep_id = (f, env) => env |> map_of |> f |> wrap(env |> id_of); + + let extend = (env, xr) => + env |> update(map => Environment.extend(map, xr)); + + let extend_keep_id = (env, xr) => + env |> update_keep_id(map => Environment.extend(map, xr)); + + let union = (env1, env2) => + env2 |> update(map2 => Environment.union(env1 |> map_of, map2)); + + let union_keep_id = (env1, env2) => + env2 |> update_keep_id(map2 => Environment.union(env1 |> map_of, map2)); + + let map = (f, env) => env |> update(Environment.mapo(f)); + + let map_keep_id = (f, env) => env |> update_keep_id(Environment.mapo(f)); + + let filter = (f, env) => env |> update(Environment.filtero(f)); + + let filter_keep_id = (f, env) => + env |> update_keep_id(Environment.filtero(f)); + + let fold = (f, init, env) => env |> map_of |> Environment.foldo(f, init); + + let placeholder = wrap(Id.invalid, Environment.empty); + + let without_keys = keys => update(Environment.without_keys(keys)); +} +and StepperFilterKind: { + [@deriving (show({with_path: false}), sexp, yojson)] + type filter = { + pat: Exp.t, + act: FilterAction.t, }; + + [@deriving (show({with_path: false}), sexp, yojson)] + type t = + | Filter(filter) + | Residue(int, FilterAction.t); + + let map_term: + ( + ~f_exp: (Exp.t => Exp.t, Exp.t) => Exp.t=?, + ~f_pat: (Pat.t => Pat.t, Pat.t) => Pat.t=?, + ~f_typ: (Typ.t => Typ.t, Typ.t) => Typ.t=?, + ~f_tpat: (TPat.t => TPat.t, TPat.t) => TPat.t=?, + ~f_rul: (Rul.t => Rul.t, Rul.t) => Rul.t=?, + ~f_any: (Any.t => Any.t, Any.t) => Any.t=?, + t + ) => + t; + + let map: (Exp.t => Exp.t, t) => t; + + let fast_equal: (t, t) => bool; +} = { + [@deriving (show({with_path: false}), sexp, yojson)] + type filter = { + pat: Exp.t, + act: FilterAction.t, + }; + + [@deriving (show({with_path: false}), sexp, yojson)] + type t = + | Filter(filter) + | Residue(int, FilterAction.t); + + let map = (mapper, filter) => { + switch (filter) { + | Filter({act, pat}) => Filter({act, pat: mapper(pat)}) + | Residue(idx, act) => Residue(idx, act) + }; + }; + + let map_term = + ( + ~f_exp=continue, + ~f_pat=continue, + ~f_typ=continue, + ~f_tpat=continue, + ~f_rul=continue, + ~f_any=continue, + ) => { + let exp_map_term = + Exp.map_term(~f_exp, ~f_pat, ~f_typ, ~f_tpat, ~f_rul, ~f_any); + fun + | Filter({pat: e, act}) => Filter({pat: exp_map_term(e), act}) + | Residue(i, a) => Residue(i, a); + }; + + let fast_equal = (f1, f2) => + switch (f1, f2) { + | (Filter({pat: e1, act: a1}), Filter({pat: e2, act: a2})) => + Exp.fast_equal(e1, e2) && a1 == a2 + | (Residue(i1, a1), Residue(i2, a2)) => i1 == i2 && a1 == a2 + | (Filter(_), _) + | (Residue(_), _) => false + }; }; diff --git a/src/haz3lcore/statics/Typ.re b/src/haz3lcore/statics/Typ.re deleted file mode 100644 index 9b6c4033a5..0000000000 --- a/src/haz3lcore/statics/Typ.re +++ /dev/null @@ -1,4 +0,0 @@ -include TypBase.Typ; - -/* Due to otherwise cyclic dependencies, Typ and Ctx - are jointly located in the TypBase module */ diff --git a/src/haz3lcore/statics/TypBase.re b/src/haz3lcore/statics/TypBase.re deleted file mode 100644 index d5ad13c0d3..0000000000 --- a/src/haz3lcore/statics/TypBase.re +++ /dev/null @@ -1,981 +0,0 @@ -open Sexplib.Std; -open Util; -open OptUtil.Syntax; - -let precedence_Prod = 1; -let precedence_Arrow = 2; -let precedence_Sum = 3; -let precedence_Const = 4; - -module rec Typ: { - /* TYPE_PROVENANCE: From whence does an unknown type originate? - Is it generated from an unannotated pattern variable (SynSwitch), - a pattern variable annotated with a type hole (TypeHole), or - generated by an internal judgement (Internal)? */ - [@deriving (show({with_path: false}), sexp, yojson)] - type type_provenance = - | SynSwitch - | TypeHole - | Free(TypVar.t) - | Internal; - - type module_typ = { - inner_ctx: Ctx.t, - incomplete: bool, - }; - - /* TYP.T: Hazel types */ - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - | Unknown(type_provenance) - | Int - | Float - | Bool - | String - | Var(TypVar.t) - | List(t) - | Arrow(t, t) - | Sum(sum_map) - | Prod(list(t)) - | Module(module_typ) - | Member(Token.t, t) - | Rec(TypVar.t, t) - | Forall(TypVar.t, t) - and sum_map = ConstructorMap.t(option(t)); - - [@deriving (show({with_path: false}), sexp, yojson)] - type sum_entry = ConstructorMap.binding(option(t)); - - /* Hazel type annotated with a relevant source location. - Currently used to track match branches for inconsistent - branches errors, but could perhaps be used more broadly - for type debugging UI. */ - [@deriving (show({with_path: false}), sexp, yojson)] - type source = { - id: Id.t, - ty: t, - }; - - let of_source: list(source) => list(t); - let join_type_provenance: - (type_provenance, type_provenance) => type_provenance; - let matched_arrow: (Ctx.t, t) => (t, t); - let matched_forall: (Ctx.t, t) => (option(string), t); - let matched_prod: (Ctx.t, int, t) => list(t); - let matched_list: (Ctx.t, t) => t; - let matched_args: (Ctx.t, int, t) => list(t); - let precedence: t => int; - let subst: (t, TypVar.t, t) => t; - let unroll: t => t; - let eq: (t, t) => bool; - let free_vars: (~bound: list(Var.t)=?, t) => list(Var.t); - let join: (~resolve: bool=?, ~fix: bool, Ctx.t, t, t) => option(t); - let join_fix: (~resolve: bool=?, Ctx.t, t, t) => option(t); - let join_all: (~empty: t, Ctx.t, list(t)) => option(t); - let is_consistent: (Ctx.t, t, t) => bool; - let weak_head_normalize: (Ctx.t, t) => t; - let normalize: (Ctx.t, t) => t; - let sum_entry: (Constructor.t, sum_map) => option(sum_entry); - let get_sum_constructors: (Ctx.t, t) => option(sum_map); - let is_unknown: t => bool; - let needs_parens: t => bool; - let pretty_print: t => string; -} = { - [@deriving (show({with_path: false}), sexp, yojson)] - type type_provenance = - | SynSwitch - | TypeHole - | Free(TypVar.t) - | Internal; - - [@deriving (show({with_path: false}), sexp, yojson)] - type module_typ = { - inner_ctx: Ctx.t, - incomplete: bool, - }; - /* TYP.T: Hazel types */ - - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - | Unknown(type_provenance) - | Int - | Float - | Bool - | String - | Var(TypVar.t) - | List(t) - | Arrow(t, t) - | Sum(sum_map) - | Prod(list(t)) - | Module(module_typ) - | Member(Token.t, t) - | Rec(TypVar.t, t) - | Forall(TypVar.t, t) - and sum_map = ConstructorMap.t(option(t)); - - [@deriving (show({with_path: false}), sexp, yojson)] - type sum_entry = ConstructorMap.binding(option(t)); - - [@deriving (show({with_path: false}), sexp, yojson)] - type source = { - id: Id.t, - ty: t, - }; - - /* Strip location information from a list of sources */ - let of_source = List.map((source: source) => source.ty); - - /* How type provenance information should be collated when - joining unknown types. This probably requires more thought, - but right now TypeHole strictly predominates over Internal - which strictly predominates over SynSwitch. */ - let join_type_provenance = - (p1: type_provenance, p2: type_provenance): type_provenance => - switch (p1, p2) { - | (Free(tv1), Free(tv2)) when TypVar.eq(tv1, tv2) => Free(tv1) - | (TypeHole, TypeHole | SynSwitch) - | (SynSwitch, TypeHole) => TypeHole - | (SynSwitch, Internal) - | (Internal, SynSwitch) => SynSwitch - | (Internal | Free(_), _) - | (_, Internal | Free(_)) => Internal - | (SynSwitch, SynSwitch) => SynSwitch - }; - - let precedence = (ty: t): int => - switch (ty) { - | Int - | Float - | Bool - | String - | Unknown(_) - | Var(_) - | Module(_) - | Member(_) - | Rec(_) - | Forall(_) - | Sum(_) => precedence_Sum - | List(_) => precedence_Const - | Prod(_) => precedence_Prod - | Arrow(_, _) => precedence_Arrow - }; - - let rec free_vars = (~bound=[], ty: t): list(Var.t) => - switch (ty) { - | Unknown(_) - | Int - | Float - | Bool - | String => [] - | Var(v) => List.mem(v, bound) ? [] : [v] - | List(ty) => free_vars(~bound, ty) - | Arrow(t1, t2) => free_vars(~bound, t1) @ free_vars(~bound, t2) - | Sum(sm) => - ListUtil.flat_map( - fun - | None => [] - | Some(typ) => free_vars(~bound, typ), - List.map(snd, sm), - ) - | Prod(tys) => ListUtil.flat_map(free_vars(~bound), tys) - | Module({inner_ctx, _}) => - let ctx_entry_subst = (l: list(Token.t), e: Ctx.entry): list(Token.t) => { - switch (e) { - | VarEntry(t) - | ConstructorEntry(t) => l @ free_vars(t.typ) - | TVarEntry(_) => l - }; - }; - List.fold_left(ctx_entry_subst, [], inner_ctx); - | Member(_, ty) => free_vars(ty) - | Rec(x, ty) => free_vars(~bound=[x, ...bound], ty) - | Forall(x, ty) => free_vars(~bound=[x, ...bound], ty) - }; - - let var_count = ref(0); - let fresh_var = (var_name: string) => { - let x = var_count^; - var_count := x + 1; - var_name ++ "_α" ++ string_of_int(x); - }; - - let rec subst = (s: t, x: TypVar.t, ty: t) => { - switch (ty) { - | Int => Int - | Float => Float - | Bool => Bool - | String => String - | Unknown(prov) => Unknown(prov) - | Arrow(ty1, ty2) => Arrow(subst(s, x, ty1), subst(s, x, ty2)) - | Prod(tys) => Prod(List.map(subst(s, x), tys)) - | Sum(sm) => Sum(ConstructorMap.map(Option.map(subst(s, x)), sm)) - | Rec(y, ty) when TypVar.eq(x, y) => Rec(y, ty) - | Rec(y, ty) when List.mem(y, free_vars(s)) => - let fresh = fresh_var(y); - Rec(fresh, subst(s, x, subst(Var(fresh), y, ty))); - | Rec(y, ty) => Rec(y, subst(s, x, ty)) - | Forall(y, ty) when TypVar.eq(x, y) => Forall(y, ty) - | Forall(y, ty) when List.mem(y, free_vars(s)) => - let fresh = fresh_var(y); - Forall(fresh, subst(s, x, subst(Var(fresh), y, ty))); - | Forall(y, ty) => Forall(y, subst(s, x, ty)) - | List(ty) => List(subst(s, x, ty)) - | Var(y) => TypVar.eq(x, y) ? s : Var(y) - | Module({inner_ctx, incomplete}) => - let ctx_entry_subst = (e: Ctx.entry): Ctx.entry => { - switch (e) { - | VarEntry(t) => VarEntry({...t, typ: subst(s, x, t.typ)}) - | ConstructorEntry(t) => - ConstructorEntry({...t, typ: subst(s, x, t.typ)}) - | TVarEntry(_) => e - }; - }; - Module({inner_ctx: List.map(ctx_entry_subst, inner_ctx), incomplete}); - | Member(name, ty) => Member(name, subst(s, x, ty)) - }; - }; - - let unroll = (ty: t): t => - switch (ty) { - | Rec(x, ty_body) => subst(ty, x, ty_body) - | _ => ty - }; - - /* Type Equality: This coincides with alpha equivalence for normalized types. - Other types may be equivalent but this will not detect so if they are not normalized. */ - let rec eq_internal = (n: int, t1: t, t2: t) => { - switch (t1, t2) { - | (Member(_, ty1), ty2) => eq_internal(n, ty1, ty2) - | (ty1, Member(_, ty2)) => eq_internal(n, ty1, ty2) - | (Module(ctx1), Module(ctx2)) => - let entry_equal = (e1: Ctx.entry, e2: Ctx.entry) => { - switch (e1, e2) { - | ( - VarEntry({typ: t1, name: n1, _}), - VarEntry({typ: t2, name: n2, _}), - ) => - eq_internal(n, t1, t2) && n1 == n2 - | ( - TVarEntry({kind: t1, name: n1, _}), - TVarEntry({kind: t2, name: n2, _}), - ) => - t1 == t2 && n1 == n2 - | ( - ConstructorEntry({typ: t1, name: n1, _}), - ConstructorEntry({typ: t2, name: n2, _}), - ) => - eq_internal(n, t1, t2) && n1 == n2 - | _ => false - }; - }; - List.equal(entry_equal, ctx1.inner_ctx, ctx2.inner_ctx) - && ctx1.incomplete == ctx2.incomplete; - | (Module(_), _) => false - | (Rec(x1, t1), Rec(x2, t2)) - | (Forall(x1, t1), Forall(x2, t2)) => - eq_internal( - n + 1, - subst(Var("=" ++ string_of_int(n)), x1, t1), - subst(Var("=" ++ string_of_int(n)), x2, t2), - ) - | (Rec(_), _) => false - | (Forall(_), _) => false - | (Int, Int) => true - | (Int, _) => false - | (Float, Float) => true - | (Float, _) => false - | (Bool, Bool) => true - | (Bool, _) => false - | (String, String) => true - | (String, _) => false - | (Unknown(_), Unknown(_)) => true - | (Unknown(_), _) => false - | (Arrow(t1, t2), Arrow(t1', t2')) => - eq_internal(n, t1, t1') && eq_internal(n, t2, t2') - | (Arrow(_), _) => false - | (Prod(tys1), Prod(tys2)) => List.equal(eq_internal(n), tys1, tys2) - | (Prod(_), _) => false - | (List(t1), List(t2)) => eq_internal(n, t1, t2) - | (List(_), _) => false - | (Sum(sm1), Sum(sm2)) => - /* Does not normalize the types. */ - ConstructorMap.equal(Option.equal(eq_internal(n)), sm1, sm2) - | (Sum(_), _) => false - | (Var(n1), Var(n2)) => n1 == n2 - | (Var(_), _) => false - }; - }; - - let eq = (t1: t, t2: t): bool => eq_internal(0, t1, t2); - - /* Lattice join on types. This is a LUB join in the hazel2 - sense in that any type dominates Unknown. The optional - resolve parameter specifies whether, in the case of a type - variable and a succesful join, to return the resolved join type, - or to return the (first) type variable for readability */ - let rec join = - (~resolve=false, ~fix, ctx: Ctx.t, ty1: t, ty2: t): option(t) => { - let join' = join(~resolve, ~fix, ctx); - switch (ty1, ty2) { - | (Member(_, Unknown(Internal)), ty) - | (ty, Member(_, Unknown(Internal))) => Some(ty) - | (Member(n1, ty1), Member(n2, ty2)) => - if (n1 == n2) { - let* ty = join'(ty1, ty2); - Some(Member(n1, ty)); - } else { - let+ ty_join = join'(ty1, ty2); - resolve ? ty_join : Member(n1, ty_join); - } - | (Member(name, ty1), ty2) - | (ty2, Member(name, ty1)) => - let+ ty_join = join'(ty1, ty2); - resolve ? ty_join : Member(name, ty_join); - | (_, Unknown(TypeHole | Free(_)) as ty) when fix => - /* NOTE(andrew): This is load bearing - for ensuring that function literals get appropriate - casts. Documentation/Dynamics has regression tests */ - Some(ty) - | (Unknown(p1), Unknown(p2)) => - Some(Unknown(join_type_provenance(p1, p2))) - | (Unknown(_), ty) - | (ty, Unknown(_)) => Some(ty) - | (Var(n1), Var(n2)) => - if (n1 == n2) { - Some(Var(n1)); - } else { - let* ty1 = Ctx.lookup_alias(ctx, n1); - let* ty2 = Ctx.lookup_alias(ctx, n2); - let+ ty_join = join'(ty1, ty2); - !resolve && eq(ty1, ty_join) ? Var(n1) : ty_join; - } - | (Var(name), ty) - | (ty, Var(name)) => - let* ty_name = Ctx.lookup_alias(ctx, name); - let+ ty_join = join'(ty_name, ty); - !resolve && eq(ty_name, ty_join) ? Var(name) : ty_join; - /* Note: Ordering of Unknown, Var, and Rec above is load-bearing! */ - | (Rec(x1, ty1), Rec(x2, ty2)) => - let ctx = Ctx.extend_dummy_tvar(ctx, x1); - let+ ty_body = - join(~resolve, ~fix, ctx, subst(Var(x2), x1, ty1), ty2); - Rec(x1, ty_body); - | (Forall(x1, ty1), Forall(x2, ty2)) => - let ctx = Ctx.extend_dummy_tvar(ctx, x1); - let+ ty_body = - join(~resolve, ~fix, ctx, subst(Var(x2), x1, ty1), ty2); - Forall(x1, ty_body); - /* Note for above: there is no danger of free variable capture as - subst itself performs capture avoiding substitution. However this - may generate internal type variable names that in corner cases can - be exposed to the user. We preserve the variable name of the - second type to preserve synthesized type variable names, which - come from user annotations. */ - | (Rec(_), _) => None - | (Forall(_), _) => None - | (Int, Int) => Some(Int) - | (Int, _) => None - | (Float, Float) => Some(Float) - | (Float, _) => None - | (Bool, Bool) => Some(Bool) - | (Bool, _) => None - | (String, String) => Some(String) - | (String, _) => None - | (Arrow(ty1, ty2), Arrow(ty1', ty2')) => - let* ty1 = join'(ty1, ty1'); - let+ ty2 = join'(ty2, ty2'); - Arrow(ty1, ty2); - | (Arrow(_), _) => None - | (Prod(tys1), Prod(tys2)) => - let* tys = ListUtil.map2_opt(join', tys1, tys2); - let+ tys = OptUtil.sequence(tys); - Prod(tys); - | (Prod(_), _) => None - | (Sum(sm1), Sum(sm2)) => - let (sorted1, sorted2) = - /* If same order, retain order for UI */ - ConstructorMap.same_constructors_same_order(sm1, sm2) - ? (sm1, sm2) - : (ConstructorMap.sort(sm1), ConstructorMap.sort(sm2)); - let* ty = - ListUtil.map2_opt( - join_sum_entries(~resolve, ~fix, ctx), - sorted1, - sorted2, - ); - let+ ty = OptUtil.sequence(ty); - Sum(ty); - | (Sum(_), _) => None - | (List(ty1), List(ty2)) => - let+ ty = join'(ty1, ty2); - List(ty); - | (List(_), _) => None - | (Module(ctx1), Module(ctx2)) => - /* Module types can join if and only if for every variable, - Either: it appears in both ctxs and the types can join, - Or: it appears only in one ctx and the other ctx is incomplete */ - let join_entry = - ( - {inner_ctx, incomplete}: module_typ, - ctx_joined: option(Ctx.t), - ctx1_entry: Ctx.entry, - ) - : option(Ctx.t) => { - let do_incomplete = (entry1: 'a, entry2: option('a)): option('a) => - if (incomplete && entry2 == None) { - Some(entry1); - } else { - entry2; - }; - let* ctx_joined = ctx_joined; - switch (ctx1_entry) { - | VarEntry({name, typ, id} as entry1) => - let* entry2 = - Ctx.lookup_var(inner_ctx, name) |> do_incomplete(entry1); - let+ typ_joined = join'(typ, entry2.typ); - Ctx.extend(ctx_joined, VarEntry({name, typ: typ_joined, id})); - | ConstructorEntry({name, typ, id} as entry1) => - let* entry2 = - Ctx.lookup_ctr(inner_ctx, name) |> do_incomplete(entry1); - let+ typ_joined = join'(typ, entry2.typ); - Ctx.extend( - ctx_joined, - ConstructorEntry({name, typ: typ_joined, id}), - ); - | TVarEntry({name, kind, id}) => - let* entry2 = Ctx.lookup_tvar(inner_ctx, name); - let+ kind_joined = - switch (kind, entry2.kind) { - | (Abstract, Abstract) => Some(Kind.Abstract) - | (Singleton(ty1), Singleton(ty2)) => - let+ typ_joined = join'(ty1, ty2); - Kind.Singleton(typ_joined); - | _ => None - }; - Ctx.extend(ctx_joined, TVarEntry({name, kind: kind_joined, id})); - }; - }; - let* ctx = List.fold_left(join_entry(ctx2), Some([]), ctx1.inner_ctx); - let* ctx = - List.fold_left(join_entry(ctx1), Some(ctx), ctx2.inner_ctx); - Some( - Module({ - inner_ctx: ctx |> Ctx.filter_duplicates, - incomplete: ctx1.incomplete && ctx2.incomplete, - }), - ); - | (Module(_), _) => None - }; - } - and join_sum_entries = - ( - ~resolve, - ~fix, - ctx: Ctx.t, - (ctr1, ty1): sum_entry, - (ctr2, ty2): sum_entry, - ) - : option(sum_entry) => - switch (ty1, ty2) { - | (None, None) when ctr1 == ctr2 => Some((ctr1, None)) - | (Some(ty1), Some(ty2)) when ctr1 == ctr2 => - let+ ty_join = join(~resolve, ~fix, ctx, ty1, ty2); - (ctr1, Some(ty_join)); - | _ => None - }; - - let join_fix = join(~fix=true); - - let join_all = (~empty: t, ctx: Ctx.t, ts: list(t)): option(t) => - List.fold_left( - (acc, ty) => OptUtil.and_then(join(~fix=false, ctx, ty), acc), - Some(empty), - ts, - ); - - let is_consistent = (ctx: Ctx.t, ty1: t, ty2: t): bool => - join(~fix=false, ctx, ty1, ty2) != None; - - let rec weak_head_normalize = (ctx: Ctx.t, ty: t): t => - switch (ty) { - | Var(x) => - switch (Ctx.lookup_alias(ctx, x)) { - | Some(ty) => weak_head_normalize(ctx, ty) - | None => ty - } - | _ => ty - }; - - let rec normalize = (ctx: Ctx.t, ty: t): t => { - switch (ty) { - | Var(x) => - switch (Ctx.lookup_alias(ctx, x)) { - | Some(ty) => normalize(ctx, ty) - | None => ty - } - | Unknown(_) - | Int - | Float - | Bool - | String => ty - | List(t) => List(normalize(ctx, t)) - | Arrow(t1, t2) => Arrow(normalize(ctx, t1), normalize(ctx, t2)) - | Prod(ts) => Prod(List.map(normalize(ctx), ts)) - | Sum(ts) => Sum(ConstructorMap.map(Option.map(normalize(ctx)), ts)) - | Module({inner_ctx, incomplete}) => - let ctx_entry_subst = (e: Ctx.entry): Ctx.entry => { - switch (e) { - | VarEntry(t) => VarEntry({...t, typ: normalize(ctx, t.typ)}) - | ConstructorEntry(t) => - ConstructorEntry({...t, typ: normalize(ctx, t.typ)}) - | TVarEntry(_) => e - }; - }; - Module({inner_ctx: List.map(ctx_entry_subst, inner_ctx), incomplete}); - | Member(name, ty) => Member(name, normalize(ctx, ty)) - | Rec(name, ty) => - /* NOTE: Dummy tvar added has fake id but shouldn't matter - as in current implementation Recs do not occur in the - surface syntax, so we won't try to jump to them. */ - Rec(name, normalize(Ctx.extend_dummy_tvar(ctx, name), ty)) - | Forall(name, ty) => - Forall(name, normalize(Ctx.extend_dummy_tvar(ctx, name), ty)) - }; - }; - - let matched_arrow = (ctx, ty) => - switch (weak_head_normalize(ctx, ty)) { - | Arrow(ty_in, ty_out) => (ty_in, ty_out) - | Unknown(SynSwitch) => (Unknown(SynSwitch), Unknown(SynSwitch)) - | _ => (Unknown(Internal), Unknown(Internal)) - }; - - let matched_forall = (ctx, ty) => - switch (weak_head_normalize(ctx, ty)) { - | Forall(t, ty) => (Some(t), ty) - | Unknown(SynSwitch) => (None, Unknown(SynSwitch)) - | _ => (None, Unknown(Internal)) - }; - - let matched_prod = (ctx, length, ty) => - switch (weak_head_normalize(ctx, ty)) { - | Prod(tys) when List.length(tys) == length => tys - | Unknown(SynSwitch) => List.init(length, _ => Unknown(SynSwitch)) - | _ => List.init(length, _ => Unknown(Internal)) - }; - - let matched_list = (ctx, ty) => - switch (weak_head_normalize(ctx, ty)) { - | List(ty) => ty - | Unknown(SynSwitch) => Unknown(SynSwitch) - | _ => Unknown(Internal) - }; - - let matched_args = (ctx, default_arity, ty) => - switch (weak_head_normalize(ctx, ty)) { - | Prod([_, ..._] as tys) => tys - | Unknown(_) as ty_unknown => List.init(default_arity, _ => ty_unknown) - | _ as ty => [ty] - }; - - let sum_entry = (ctr: Constructor.t, ctrs: sum_map): option(sum_entry) => - List.find_map( - fun - | (t, typ) when Constructor.equal(t, ctr) => Some((t, typ)) - | _ => None, - ctrs, - ); - - let rec get_sum_constructors = (ctx: Ctx.t, ty: t): option(sum_map) => { - let ty = weak_head_normalize(ctx, ty); - switch (ty) { - | Member(_, ty) => get_sum_constructors(ctx, ty) - | Sum(sm) => Some(sm) - | Rec(_) => - /* Note: We must unroll here to get right ctr types; - otherwise the rec parameter will leak. However, seeing - as substitution is too expensive to be used here, we - currently making the optimization that, since all - recursive types are type alises which use the alias name - as the recursive parameter, and type aliases cannot be - shadowed, it is safe to simply remove the Rec constructor, - provided we haven't escaped the context in which the alias - is bound. If either of the above assumptions become invalid, - the below code will be incorrect! */ - let ty = - switch (ty) { - | Rec(x, ty_body) => - switch (Ctx.lookup_alias(ctx, x)) { - | None => unroll(ty) - | Some(_) => ty_body - } - | _ => ty - }; - switch (ty) { - | Sum(sm) => Some(sm) - | _ => None - }; - | _ => None - }; - }; - - let is_unknown = (ty: t): bool => - switch (ty) { - | Unknown(_) => true - | _ => false - }; - - /* Does the type require parentheses when on the left of an arrow for printing? */ - let needs_parens = (ty: t): bool => - switch (ty) { - | Unknown(_) - | Int - | Float - | String - | Bool - | Module(_) - | Member(_) - | Var(_) => false - | Rec(_, _) - | Forall(_, _) => true - | List(_) => false /* is already wrapped in [] */ - | Arrow(_, _) => true - | Prod(_) - | Sum(_) => true /* disambiguate between (A + B) -> C and A + (B -> C) */ - }; - - /* Essentially recreates haz3lweb/view/Type.re's view_ty but with string output */ - let rec pretty_print = (ty: t): string => - switch (ty) { - | Unknown(_) => "?" - | Int => "Int" - | Float => "Float" - | Bool => "Bool" - | String => "String" - | Var(tvar) => tvar - | List(t) => "[" ++ pretty_print(t) ++ "]" - | Arrow(t1, t2) => paren_pretty_print(t1) ++ "->" ++ pretty_print(t2) - | Sum(sm) => - switch (sm) { - | [] => "+?" - | [t0] => "+" ++ ctr_pretty_print(t0) - | [t0, ...ts] => - List.fold_left( - (acc, t) => acc ++ "+" ++ ctr_pretty_print(t), - ctr_pretty_print(t0), - ts, - ) - } - | Prod([]) => "()" - | Prod([t0, ...ts]) => - "(" - ++ List.fold_left( - (acc, t) => acc ++ ", " ++ pretty_print(t), - pretty_print(t0), - ts, - ) - ++ ")" - | Module({inner_ctx: [], incomplete: false}) => "Module" - | Module({inner_ctx: [], incomplete: true}) => "Module{...}" - | Module({inner_ctx: [e, ...es], incomplete}) => - let view_entry = (m: Ctx.entry): string => { - switch (m) { - | VarEntry({name: n0, typ: t0, _}) - | ConstructorEntry({name: n0, typ: t0, _}) => - n0 ++ ":" ++ pretty_print(t0) - - | TVarEntry({name: n0, kind: Singleton(t0), _}) => - "Type " ++ n0 ++ "=" ++ pretty_print(t0) - - | TVarEntry({name: n0, _}) => - "Type " ++ n0 ++ "=" ++ pretty_print(Unknown(Internal)) - }; - }; - "Module{" - ++ List.fold_left( - (acc, t) => acc ++ ", " ++ view_entry(t), - view_entry(e), - es, - ) - ++ view_entry(e) - ++ (incomplete ? ",..." : "") - ++ "}"; - | Member(name, _) => name - | Rec(tv, t) => "rec " ++ tv ++ "->" ++ pretty_print(t) - | Forall(tv, t) => "forall " ++ tv ++ "->" ++ pretty_print(t) - } - and ctr_pretty_print = ((ctr, typ)) => - switch (typ) { - | None => ctr - | Some(typ) => ctr ++ "(" ++ pretty_print(typ) ++ ")" - } - and paren_pretty_print = typ => - if (needs_parens(typ)) { - "(" ++ pretty_print(typ) ++ ")"; - } else { - pretty_print(typ); - }; -} - -and Ctx: { - [@deriving (show({with_path: false}), sexp, yojson)] - type var_entry = { - name: Var.t, - id: Id.t, - typ: Typ.t, - }; - - [@deriving (show({with_path: false}), sexp, yojson)] - type tvar_entry = { - name: TypVar.t, - id: Id.t, - kind: Kind.t, - }; - - [@deriving (show({with_path: false}), sexp, yojson)] - type entry = - | VarEntry(var_entry) - | ConstructorEntry(var_entry) - | TVarEntry(tvar_entry); - - [@deriving (show({with_path: false}), sexp, yojson)] - type t = list(entry); - - let extend: (t, entry) => t; - let extend_tvar: (t, tvar_entry) => t; - let extend_alias: (t, TypVar.t, Id.t, Typ.t) => t; - let extend_dummy_tvar: (t, TypVar.t) => t; - let lookup_tvar: (t, TypVar.t) => option(tvar_entry); - let lookup_alias: (t, TypVar.t) => option(Typ.t); - let get_id: entry => Id.t; - let lookup_var: (t, string) => option(var_entry); - let lookup_ctr: (t, string) => option(var_entry); - let is_alias: (t, TypVar.t) => bool; - let is_abstract: (t, TypVar.t) => bool; - let add_ctrs: (t, TypVar.t, Id.t, Typ.sum_map) => t; - let subtract_prefix: (t, t) => option(t); - let added_bindings: (t, t) => t; - let filter_duplicates: t => t; - let modulize: (Typ.t, string) => Typ.t; - let shadows_typ: (t, TypVar.t) => bool; -} = { - [@deriving (show({with_path: false}), sexp, yojson)] - type var_entry = { - name: Var.t, - id: Id.t, - typ: Typ.t, - }; - - [@deriving (show({with_path: false}), sexp, yojson)] - type tvar_entry = { - name: TypVar.t, - id: Id.t, - kind: Kind.t, - }; - - [@deriving (show({with_path: false}), sexp, yojson)] - type entry = - | VarEntry(var_entry) - | ConstructorEntry(var_entry) - | TVarEntry(tvar_entry); - - [@deriving (show({with_path: false}), sexp, yojson)] - type t = list(entry); - - let extend = (ctx, entry) => List.cons(entry, ctx); - - let extend_tvar = (ctx: t, tvar_entry: tvar_entry): t => - extend(ctx, TVarEntry(tvar_entry)); - - let extend_alias = (ctx: t, name: TypVar.t, id: Id.t, ty: Typ.t): t => - extend_tvar(ctx, {name, id, kind: Singleton(ty)}); - - let extend_dummy_tvar = (ctx: t, name: TypVar.t) => - extend_tvar(ctx, {kind: Abstract, name, id: Id.invalid}); - - let lookup_tvar = (ctx: t, name: TypVar.t): option(tvar_entry) => - List.find_map( - fun - | TVarEntry(v) when v.name == name => Some(v) - | _ => None, - ctx, - ); - - let lookup_alias = (ctx: t, t: TypVar.t): option(Typ.t) => - switch (lookup_tvar(ctx, t)) { - | Some({kind: Singleton(ty), _}) => Some(ty) - | Some({kind: Abstract, _}) - | None => None - }; - - let get_id: entry => Id.t = - fun - | VarEntry({id, _}) - | ConstructorEntry({id, _}) - | TVarEntry({id, _}) => id; - - let lookup_var = (ctx: t, name: string): option(var_entry) => - List.find_map( - fun - | VarEntry(v) when v.name == name => Some(v) - | _ => None, - ctx, - ); - - let lookup_ctr = (ctx: t, name: string): option(var_entry) => - List.find_map( - fun - | ConstructorEntry(t) when t.name == name => Some(t) - | _ => None, - ctx, - ); - - let is_alias = (ctx: t, name: TypVar.t): bool => - switch (lookup_alias(ctx, name)) { - | Some(_) => true - | None => false - }; - - let is_abstract = (ctx: t, name: TypVar.t): bool => - switch (lookup_tvar(ctx, name)) { - | Some({kind: Abstract, _}) => true - | _ => false - }; - - let add_ctrs = (ctx: t, name: TypVar.t, id: Id.t, ctrs: Typ.sum_map): t => - List.map( - ((ctr, typ)) => - ConstructorEntry({ - name: ctr, - id, - typ: - switch (typ) { - | None => Var(name) - | Some(typ) => Arrow(typ, Var(name)) - }, - }), - ctrs, - ) - @ ctx; - - let subtract_prefix = (ctx: t, prefix_ctx: t): option(t) => { - // NOTE: does not check that the prefix is an actual prefix - let prefix_length = List.length(prefix_ctx); - let ctx_length = List.length(ctx); - if (prefix_length > ctx_length) { - None; - } else { - Some( - List.rev( - ListUtil.sublist((prefix_length, ctx_length), List.rev(ctx)), - ), - ); - }; - }; - - let added_bindings = (ctx_after: t, ctx_before: t): t => { - /* Precondition: new_ctx is old_ctx plus some new bindings */ - let new_count = List.length(ctx_after) - List.length(ctx_before); - switch (ListUtil.split_n_opt(new_count, ctx_after)) { - | Some((ctx, _)) => ctx - | _ => [] - }; - }; - - module VarSet = Set.Make(Var); - - // Note: filter out duplicates when rendering - let filter_duplicates = (ctx: t): t => - ctx - |> List.fold_left( - ((ctx, term_set, typ_set), entry) => { - switch (entry) { - | VarEntry({name, _}) - | ConstructorEntry({name, _}) => - VarSet.mem(name, term_set) - ? (ctx, term_set, typ_set) - : ([entry, ...ctx], VarSet.add(name, term_set), typ_set) - | TVarEntry({name, _}) => - VarSet.mem(name, typ_set) - ? (ctx, term_set, typ_set) - : ([entry, ...ctx], term_set, VarSet.add(name, typ_set)) - } - }, - ([], VarSet.empty, VarSet.empty), - ) - |> (((ctx, _, _)) => List.rev(ctx)); - let rec modulize_item = (ctx: t, x: Token.t, ty: Typ.t): Typ.t => { - switch (ty) { - | Int => Int - | Float => Float - | Bool => Bool - | String => String - | Member(name, ty1) => Member(x ++ "." ++ name, ty1) - | Unknown(prov) => Unknown(prov) - | Arrow(ty1, ty2) => - Arrow(modulize_item(ctx, x, ty1), modulize_item(ctx, x, ty2)) - | Prod(tys) => Prod(List.map(modulize_item(ctx, x), tys)) - | Sum(sm) => - Sum(ConstructorMap.map(Option.map(modulize_item(ctx, x)), sm)) - | Rec(y, ty) => Rec(y, modulize_item(ctx, x, ty)) - | List(ty) => List(modulize_item(ctx, x, ty)) - | Var(n) => - x == n - ? Var(n) : Member(x ++ "." ++ n, Typ.weak_head_normalize(ctx, ty)) - | Module({inner_ctx, incomplete}) => - let ctx_entry_modulize = (e: entry): entry => { - switch (e) { - | VarEntry(t) => VarEntry({...t, typ: modulize_item(ctx, x, t.typ)}) - | ConstructorEntry(t) => - ConstructorEntry({...t, typ: modulize_item(ctx, x, t.typ)}) - | TVarEntry(_) => e - }; - }; - Module({ - inner_ctx: List.map(ctx_entry_modulize, inner_ctx), - incomplete, - }); - | Forall(_, t) => modulize_item(ctx, x, t) - }; - }; - - let modulize = (ty: Typ.t, x: string): Typ.t => { - switch (ty) { - | Module({inner_ctx, incomplete}) => - Module({ - inner_ctx: - List.map( - (e: entry): entry => { - switch (e) { - | VarEntry(t) => - VarEntry({...t, typ: modulize_item(inner_ctx, x, t.typ)}) - | ConstructorEntry(t) => - ConstructorEntry({ - ...t, - typ: modulize_item(inner_ctx, x, t.typ), - }) - | TVarEntry(_) => e - } - }, - inner_ctx, - ), - incomplete, - }) - | _ => ty - }; - }; - - let shadows_typ = (ctx: t, name: TypVar.t): bool => - Form.is_base_typ(name) || is_alias(ctx, name) || is_abstract(ctx, name); -} -and Kind: { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - | Singleton(Typ.t) - | Abstract; -} = { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - | Singleton(Typ.t) - | Abstract; -}; diff --git a/src/haz3lcore/statics/TypVar.re b/src/haz3lcore/statics/TypVar.re deleted file mode 100644 index 7b4f4d4ef2..0000000000 --- a/src/haz3lcore/statics/TypVar.re +++ /dev/null @@ -1,6 +0,0 @@ -open Sexplib.Std; - -[@deriving (show({with_path: false}), sexp, yojson)] -type t = string; - -let eq = String.equal; diff --git a/src/haz3lcore/statics/Var.re b/src/haz3lcore/statics/Var.re index f684dacfe5..68c3d9d1b3 100644 --- a/src/haz3lcore/statics/Var.re +++ b/src/haz3lcore/statics/Var.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type t = string; @@ -7,18 +7,6 @@ let eq = String.equal; let length = String.length; -let valid_regex = - Re.Str.regexp("^\\([a-zA-Z]\\|_[_a-zA-Z0-9]\\)[_a-zA-Z0-9']*$"); -let is_valid = s => Re.Str.string_match(valid_regex, s, 0); - -/* helper function for guarding options with is_valid */ -let check_valid = (s, result) => - if (is_valid(s)) { - result; - } else { - None; - }; - let is_true = eq("true"); let is_false = eq("false"); diff --git a/src/haz3lcore/statics/uterm/UExp.re b/src/haz3lcore/statics/uterm/UExp.re new file mode 100644 index 0000000000..16d6db0412 --- /dev/null +++ b/src/haz3lcore/statics/uterm/UExp.re @@ -0,0 +1 @@ +include Exp; diff --git a/src/haz3lcore/statics/uterm/UPat.re b/src/haz3lcore/statics/uterm/UPat.re new file mode 100644 index 0000000000..9bd15c6ba8 --- /dev/null +++ b/src/haz3lcore/statics/uterm/UPat.re @@ -0,0 +1 @@ +include Pat; diff --git a/src/haz3lcore/statics/uterm/UTyp.re b/src/haz3lcore/statics/uterm/UTyp.re new file mode 100644 index 0000000000..7dcfba5350 --- /dev/null +++ b/src/haz3lcore/statics/uterm/UTyp.re @@ -0,0 +1 @@ +include Typ; diff --git a/src/haz3lcore/tiles/Base.re b/src/haz3lcore/tiles/Base.re index 29f3d64e6f..8c127d83ba 100644 --- a/src/haz3lcore/tiles/Base.re +++ b/src/haz3lcore/tiles/Base.re @@ -1,4 +1,16 @@ -open Sexplib.Std; +open Util; + +/* The different kinds of projector. New projectors + * types need to be registered here in order to be + * able to create and update their instances */ +[@deriving (show({with_path: false}), sexp, yojson)] +type kind = + | Fold + | Info + | Checkbox + | Slider + | SliderF + | TextArea; [@deriving (show({with_path: false}), sexp, yojson)] type segment = list(piece) @@ -6,6 +18,7 @@ and piece = | Tile(tile) | Grout(Grout.t) | Secondary(Secondary.t) + | Projector(projector) and tile = { // invariants: // - length(mold.in_) + 1 == length(label) @@ -17,6 +30,12 @@ and tile = { mold: Mold.t, shards: list(int), children: list(segment), +} +and projector = { + id: Id.t, + kind, + syntax: piece, + model: string, }; // This is for comment insertion diff --git a/src/haz3lcore/tiles/Id.re b/src/haz3lcore/tiles/Id.re index b377ca02b0..5046dd63c5 100644 --- a/src/haz3lcore/tiles/Id.re +++ b/src/haz3lcore/tiles/Id.re @@ -1,3 +1,5 @@ +open Util; + /* ID FAQ WHATS AN ID? diff --git a/src/haz3lcore/tiles/Label.re b/src/haz3lcore/tiles/Label.re index 146521afa5..e26eeaa5a8 100644 --- a/src/haz3lcore/tiles/Label.re +++ b/src/haz3lcore/tiles/Label.re @@ -1,16 +1,6 @@ -open Sexplib.Std; +open Util; /* A label is the textual expression of a form's delimiters */ [@deriving (show({with_path: false}), sexp, yojson)] type t = list(Token.t); exception Empty_label; - -let length: t => int = List.length; - -let rev: t => t = List.rev; - -let hd_tl = (lbl: t): (Token.t, list(Token.t)) => - switch (lbl) { - | [] => raise(Empty_label) - | [hd, ...tl] => (hd, tl) - }; diff --git a/src/haz3lcore/tiles/Mold.re b/src/haz3lcore/tiles/Mold.re index d9a497e20c..743fcb0d18 100644 --- a/src/haz3lcore/tiles/Mold.re +++ b/src/haz3lcore/tiles/Mold.re @@ -1,4 +1,3 @@ -open Sexplib.Std; open Util; [@deriving (show({with_path: false}), sexp, yojson)] @@ -67,12 +66,6 @@ let nib_shapes = (~index=?, mold: t): Nibs.shapes => { (nib_l.shape, nib_r.shape); }; -module Map = { - type mold = t; - include Id.Map; - type nonrec t = Id.Map.t(list(mold)); -}; - let of_grout: (Grout.t, Sort.t) => t = (g, sort) => { nibs: @@ -95,17 +88,6 @@ let of_secondary = (l: Nib.t) => { in_: [], }; -let fits_shape = (d: Direction.t, s: Nib.Shape.t, m: t): bool => { - let s' = Direction.choose(d, nib_shapes(m)); - Nib.Shape.fits(s, s'); -}; - -let consistent_shapes = (ms: list(t)) => - ms - |> List.map(nib_shapes) - |> List.split - |> TupleUtil.map2(ListUtil.single_elem); - let is_infix_op = (mold: t): bool => switch (mold.nibs, mold.in_) { | (({shape: Concave(_), _}, {shape: Concave(_), _}), []) => true diff --git a/src/haz3lcore/tiles/Nib.re b/src/haz3lcore/tiles/Nib.re index 04b4c940d3..863ea9bd9f 100644 --- a/src/haz3lcore/tiles/Nib.re +++ b/src/haz3lcore/tiles/Nib.re @@ -1,3 +1,5 @@ +open Util; + module Shape = { [@deriving (show({with_path: false}), sexp, yojson)] type t = @@ -21,25 +23,26 @@ module Shape = { | (Concave(_), Concave(_)) => false }; - let fitting = - fun - | Convex => concave() - | Concave(_) => Convex; - let flip = fun | Convex => concave() | Concave(_) => Convex; - let absolute = (d: Util.Direction.t, s: t): Util.Direction.t => + let absolute = (d: Direction.t, s: t): Direction.t => /* The direction an s-shaped nib on the d-hand side is facing */ switch (s) { | Convex => d - | Concave(_) => Util.Direction.toggle(d) + | Concave(_) => Direction.toggle(d) }; - let relative = (nib: Util.Direction.t, side: Util.Direction.t): t => + let relative = (nib: Direction.t, side: Direction.t): t => nib == side ? Convex : concave(); + + let direction_of = (d: Direction.t, shape: t): Direction.t => + switch (shape) { + | Convex => d + | Concave(_) => Direction.toggle(d) + }; }; [@deriving (show({with_path: false}), sexp, yojson)] @@ -50,21 +53,4 @@ type t = { let shape = n => n.shape; -let fits = (l: t, r: t): bool => - l.sort == r.sort && Shape.fits(l.shape, r.shape); - -let fitting = (nib: t): t => {...nib, shape: Shape.fitting(nib.shape)}; - let flip = (nib: t) => {...nib, shape: Shape.flip(nib.shape)}; - -// let toggle = (nib: t) => { -// ...nib, -// orientation: Direction.toggle(nib.orientation), -// }; - -// let sort_consistent = (nib: t, nib': t) => nib.sort == nib'.sort; - -// let of_sort = sort => [ -// {sort, orientation: Left}, -// {sort, orientation: Right}, -// ]; diff --git a/src/haz3lcore/tiles/Nibs.re b/src/haz3lcore/tiles/Nibs.re index ec0d943dfc..0c4225a279 100644 --- a/src/haz3lcore/tiles/Nibs.re +++ b/src/haz3lcore/tiles/Nibs.re @@ -5,7 +5,3 @@ type t = (Nib.t, Nib.t); type shapes = (Nib.Shape.t, Nib.Shape.t); let flip = ((l, r): t) => (r, l); - -let of_hole = sort => Nib.({sort, shape: Convex}, {sort, shape: Convex}); - -let fitting = ((l, r): t) => (Nib.fitting(l), Nib.fitting(r)); diff --git a/src/haz3lcore/tiles/Piece.re b/src/haz3lcore/tiles/Piece.re index aafeef4a5b..fc6207a979 100644 --- a/src/haz3lcore/tiles/Piece.re +++ b/src/haz3lcore/tiles/Piece.re @@ -1,4 +1,3 @@ -// open Util; include Base; [@deriving (show({with_path: false}), sexp, yojson)] @@ -8,20 +7,23 @@ let secondary = w => Secondary(w); let grout = g => Grout(g); let tile = t => Tile(t); -let get = (f_w, f_g, f_t, p: t) => +let get = (f_w, f_g, f_t: tile => _, f_p: projector => _, p: t) => switch (p) { | Secondary(w) => f_w(w) | Grout(g) => f_g(g) | Tile(t) => f_t(t) + | Projector(p) => f_p(p) }; -let id = get(Secondary.id, Grout.id, Tile.id); +let proj_id = projector => projector.id; +let id = get(Secondary.id, Grout.id, tile => tile.id, proj_id); let sort = get( _ => (Sort.Any, []), _ => (Sort.Any, []), t => (t.mold.out, t.mold.in_), + _ => (Sort.Any, []), ); let nibs = @@ -32,6 +34,10 @@ let nibs = Some(Nib.({shape: l, sort: Any}, {shape: r, sort: Any})); }, t => Some(Tile.nibs(t)), + p => { + let (l, r) = ProjectorBase.shapes(p); + Some(Nib.({shape: l, sort: Any}, {shape: r, sort: Any})); + }, ); let nib_sorts = @@ -42,47 +48,47 @@ let nib_sorts = let (l, r) = Tile.nibs(t); (l.sort, r.sort); }, + _ => (Sort.Any, Sort.Any), ); -let sorted_children = get(_ => [], _ => [], Tile.sorted_children); -let children = p => sorted_children(p) |> List.split |> snd; - -// let is_balanced = -// fun -// | Shard(_) => false -// | Secondary(_) -// | Grout(_) -// | Tile(_) => true; +let sorted_children = get(_ => [], _ => [], Tile.sorted_children, _ => []); let pop_l = (p: t): (t, segment) => switch (p) { | Tile(t) => Tile.pop_l(t) | Grout(_) - | Secondary(_) => (p, []) + | Secondary(_) + | Projector(_) => (p, []) }; let pop_r = (p: t): (segment, t) => switch (p) { | Tile(t) => Tile.pop_r(t) | Grout(_) - | Secondary(_) => ([], p) + | Secondary(_) + | Projector(_) => ([], p) }; let disassemble = (p: t): segment => switch (p) { | Grout(_) - | Secondary(_) => [p] + | Secondary(_) + | Projector(_) => [p] | Tile(t) => Tile.disassemble(t) }; -// let remold = (p: t) => -// switch (p) { -// | Grout(_) -// | Secondary(_) => [p] -// | Tile(t) => List.map(tile, Tile.remold(t)) -// }; - let shapes = - get(_ => None, g => Some(Grout.shapes(g)), t => Some(Tile.shapes(t))); + get( + _ => None, + g => Some(Grout.shapes(g)), + t => Some(Tile.shapes(t)), + p => Some(ProjectorBase.shapes(p)), + ); + +let is_convex = (p: t): bool => + switch (shapes(p)) { + | Some((Convex, Convex)) => true + | _ => false + }; let is_grout: t => bool = fun @@ -99,6 +105,11 @@ let is_tile: t => option(Tile.t) = | Tile(t) => Some(t) | _ => None; +let is_projector: t => option(projector) = + fun + | Projector(p) => Some(p) + | _ => None; + let label: t => option(Label.t) = fun | Tile({label, _}) => Some(label) @@ -111,37 +122,67 @@ let monotile: t => option(Token.t) = Some(Secondary.get_string(w.content)) | _ => None; -let has_ends = get(_ => true, _ => true, Tile.has_ends); - let is_complete: t => bool = fun | Tile(t) => Tile.is_complete(t) | _ => true; -let get_outside_sorts = (~default_sort=Sort.Any, p: t): list(Sort.t) => - //TODO: David please review this +let replace_id = (id: Id.t, p: t): t => + switch (p) { + | Tile(t) => Tile({...t, id}) + | Grout(g) => Grout({...g, id}) + | Secondary(w) => Secondary({...w, id}) + | Projector(p) => Projector({...p, id}) + }; + +let mk_tile: (Form.t, list(list(t))) => t = + (form, children) => + Tile({ + id: Id.mk(), + label: form.label, + mold: form.mold, + shards: List.mapi((i, _) => i, form.label), + children, + }); + +let mk_mono = (sort: Sort.t, string: string): t => + string |> Form.mk_atomic(sort) |> mk_tile(_, []); + +let of_mono = (syntax: t): option(string) => + switch (syntax) { + | Tile({label: [l], _}) => Some(l) + | _ => None + }; + +let is_case_or_rule = (p: t) => + switch (p) { + | Tile({label: ["case", "end"], _}) => true + | Tile({label: ["|", "=>"], _}) => true + | _ => false + }; +let is_not_case_or_rule_or_space = (p: t) => switch (p) { - | Secondary(_) => [] - | Grout({shape: Convex, _}) => [] - | Grout({shape: Concave, _}) => [default_sort, default_sort] - | Tile({shards: _, _} as t) when !Tile.is_complete(t) => - // TODO(andrew): better incomplete tile handling - // Need to figure out what shape of incomplete tile is - [] - | Tile(t) => - let (sort_l, sort_r) = nib_sorts(p); - switch ((t.mold.nibs |> fst).shape, (t.mold.nibs |> snd).shape) { - | (Convex, Convex) => [] - | (Convex, Concave(_)) => [sort_r] - | (Concave(_), Convex) => [sort_l] - | (Concave(_), Concave(_)) => [sort_l, sort_r] - }; + | Tile({label: ["case", "end"], _}) => false + | Tile({label: ["|", "=>"], _}) => false + | Secondary(_) => false + | _ => true + }; +let not_comment_or_space = (p: t) => + switch (p) { + | Secondary(s) => Secondary.is_linebreak(s) + | _ => true }; -let mold_of = (~shape=Nib.Shape.Convex, p: t) => - // TODO(d) fix sorts +let is_term = (p: t) => switch (p) { - | Tile(t) => t.mold - | Grout(g) => Mold.of_grout(g, Any) - | Secondary(_) => Mold.of_secondary({sort: Any, shape}) + | Grout(_) + | Projector(_) + | Tile({ + label: [_], + mold: {nibs: ({shape: Convex, _}, {shape: Convex, _}), _}, + _, + }) => + true + | Secondary(_) => false // debatable + | _ => false }; diff --git a/src/haz3lcore/tiles/Secondary.re b/src/haz3lcore/tiles/Secondary.re index 7ef17b16a1..c973469254 100644 --- a/src/haz3lcore/tiles/Secondary.re +++ b/src/haz3lcore/tiles/Secondary.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type cls = diff --git a/src/haz3lcore/tiles/Segment.re b/src/haz3lcore/tiles/Segment.re index fc1c54e2f4..de8689f08a 100644 --- a/src/haz3lcore/tiles/Segment.re +++ b/src/haz3lcore/tiles/Segment.re @@ -13,13 +13,6 @@ let rev = List.rev; let of_tile = t => [Tile.to_piece(t)]; -let nibs = tiles => - switch (tiles, ListUtil.split_last_opt(tiles)) { - | ([], _) - | (_, None) => None - | ([_first, ..._], Some((_, _last))) => failwith("todo Tiles.nibs") - }; - let incomplete_tiles = List.filter_map( fun @@ -56,8 +49,6 @@ let remove_matching = (t: Tile.t) => let snoc = (tiles, tile) => tiles @ [tile]; -// let is_balanced = List.for_all(Piece.is_balanced); - let shape_affix = (d: Direction.t, affix: t, r: Nib.Shape.t) : (Aba.t(list(Secondary.t), Grout.t), Nib.Shape.t, t) => { @@ -73,6 +64,10 @@ let shape_affix = let (ws, wss) = ListUtil.split_first(wss); (([[w, ...ws], ...wss], gs), s, tl); | Grout(g) => (Aba.cons([], g, wgw), s, tl) + | Projector(p) => + let (l, _) = + ProjectorBase.shapes(p) |> (d == Left ? TupleUtil.swap : Fun.id); + (empty_wgw, l, tl); | Tile(t) => let (l, _) = Tile.shapes(t) |> (d == Left ? TupleUtil.swap : Fun.id); (empty_wgw, l, tl); @@ -80,39 +75,6 @@ let shape_affix = }; go((d == Left ? List.rev : Fun.id)(affix), r); }; -let shape = shape_affix(Right); - -let rec convex = seg => { - open OptUtil.Syntax; - let l = - fold_right( - (p: Piece.t, shape) => { - let* s = shape; - switch (p) { - | Secondary(_) => shape - | Grout(g) => - Grout.fits_shape(g, s) ? Some(fst(Grout.shapes(g))) : None - | Tile(t) => - let (l, r) = Tile.shapes(t); - List.for_all(convex, t.children) && Nib.Shape.fits(r, s) - ? Some(l) : None; - }; - }, - seg, - Some(Nib.Shape.concave()), - ); - switch (l) { - | None => false - | Some(l) => Nib.Shape.fits(Nib.Shape.concave(), l) - }; -}; - -let split_by_grout: t => Aba.t(t, Grout.t) = - Aba.split( - fun - | Piece.Grout(g) => Either.R(g) - | p => L(p), - ); let rec remold = (~shape=Nib.Shape.concave(), seg: t, s: Sort.t) => switch (s) { @@ -143,10 +105,7 @@ and remold_tile = (s: Sort.t, shape, t: Tile.t): option(Tile.t) => { let child = if (l + 1 == r - && ( - List.nth(remolded.mold.in_, l) != List.nth(t.mold.in_, l) - || Effect.s_touched(remolded.id) - )) { + && List.nth(remolded.mold.in_, l) != List.nth(t.mold.in_, l)) { remold(child, List.nth(remolded.mold.in_, l)); } else { child; @@ -164,7 +123,8 @@ and remold_typ = (shape, seg: t): t => | [hd, ...tl] => switch (hd) { | Secondary(_) - | Grout(_) => [hd, ...remold_typ(shape, tl)] + | Grout(_) + | Projector(_) => [hd, ...remold_typ(shape, tl)] | Tile(t) => switch (remold_tile(Typ, shape, t)) { | None => [Tile(t), ...remold_typ(snd(Tile.shapes(t)), tl)] @@ -178,7 +138,8 @@ and remold_typ_uni = (shape, seg: t): (t, Nib.Shape.t, t) => | [hd, ...tl] => switch (hd) { | Secondary(_) - | Grout(_) => + | Grout(_) + | Projector(_) => let (remolded, shape, rest) = remold_typ_uni(shape, tl); ([hd, ...remolded], shape, rest); | Tile(t) => @@ -207,7 +168,8 @@ and remold_pat_uni = (shape, seg: t): (t, Nib.Shape.t, t) => | [hd, ...tl] => switch (hd) { | Secondary(_) - | Grout(_) => + | Grout(_) + | Projector(_) => let (remolded, shape, rest) = remold_pat_uni(shape, tl); ([hd, ...remolded], shape, rest); | Tile(t) => @@ -238,7 +200,8 @@ and remold_pat = (shape, seg: t): t => | [hd, ...tl] => switch (hd) { | Secondary(_) - | Grout(_) => [hd, ...remold_pat(shape, tl)] + | Grout(_) + | Projector(_) => [hd, ...remold_pat(shape, tl)] | Tile(t) => switch (remold_tile(Pat, shape, t)) { | None => [Tile(t), ...remold_pat(snd(Tile.shapes(t)), tl)] @@ -258,7 +221,8 @@ and remold_tpat_uni = (shape, seg: t): (t, Nib.Shape.t, t) => | [hd, ...tl] => switch (hd) { | Secondary(_) - | Grout(_) => + | Grout(_) + | Projector(_) => let (remolded, shape, rest) = remold_tpat_uni(shape, tl); ([hd, ...remolded], shape, rest); | Tile(t) => @@ -285,7 +249,8 @@ and remold_tpat = (shape, seg: t): t => | [hd, ...tl] => switch (hd) { | Secondary(_) - | Grout(_) => [hd, ...remold_tpat(shape, tl)] + | Grout(_) + | Projector(_) => [hd, ...remold_tpat(shape, tl)] | Tile(t) => switch (remold_tile(TPat, shape, t)) { | None => [Tile(t), ...remold_tpat(snd(Tile.shapes(t)), tl)] @@ -305,7 +270,8 @@ and remold_exp_uni = (shape, seg: t): (t, Nib.Shape.t, t) => | [hd, ...tl] => switch (hd) { | Secondary(_) - | Grout(_) => + | Grout(_) + | Projector(_) => let (remolded, shape, rest) = remold_exp_uni(shape, tl); ([hd, ...remolded], shape, rest); | Tile(t) => @@ -347,7 +313,8 @@ and remold_rul = (shape, seg: t): t => | [hd, ...tl] => switch (hd) { | Secondary(_) - | Grout(_) => [hd, ...remold_rul(shape, tl)] + | Grout(_) + | Projector(_) => [hd, ...remold_rul(shape, tl)] | Tile(t) => switch (remold_tile(Rul, shape, t)) { | Some(t) => @@ -376,7 +343,8 @@ and remold_exp = (shape, seg: t): t => | [hd, ...tl] => switch (hd) { | Secondary(_) - | Grout(_) => [hd, ...remold_exp(shape, tl)] + | Grout(_) + | Projector(_) => [hd, ...remold_exp(shape, tl)] | Tile(t) => switch (remold_tile(Exp, shape, t)) { | None => [Tile(t), ...remold_exp(snd(Tile.shapes(t)), tl)] @@ -436,15 +404,7 @@ module Trim = { Aba.mk([ws, List.concat(wss)], [g]); }; }; - // same as merge but type encodes postcond - // let merged = (trim: t): (list(Secondary.t), option((Grout.t, list(Secondary.t)))) => { - // let (wss, gs) = merge(trim); - // let (ws, wss) = ListUtil.split_first(wss); - // switch (gs) { - // | [] => (ws, None) - // | [g, ..._] => (ws, Some((g, List.concat(wss)))) - // }; - // }; + let rec rm_up_to_one_space = (wss: list(list(Secondary.t))): list(list(Secondary.t)) => switch (wss) { @@ -541,6 +501,12 @@ and regrout_affix = switch (p) { | Secondary(w) => (Trim.cons_w(w, trim), r, tl) | Grout(g) => (Trim.(merge(cons_g(g, trim))), r, tl) + | Projector(pr) => + let p = Piece.Projector(pr); + let (l', r') = + ProjectorBase.shapes(pr) |> (d == Left ? TupleUtil.swap : Fun.id); + let trim = Trim.regrout(d, (r', r), trim); + (Trim.empty, l', [p, ...Trim.to_seg(trim)] @ tl); | Tile(t) => let children = List.fold_right( @@ -565,14 +531,6 @@ and regrout_affix = d == Left ? (Trim.rev(trim), s, rev(affix)) : (trim, s, affix); }; -// for internal use when dealing with segments in reverse order (eg Affix.re) -// let flip_nibs = -// List.map( -// fun -// | (Piece.Secondary(_) | Grout(_)) as p => p -// | Tile(t) => Tile({...t, mold: Mold.flip_nibs(t.mold)}), -// ); - let split_by_matching = (id: Id.t): (t => Aba.t(t, Tile.t)) => Aba.split( fun @@ -580,7 +538,6 @@ let split_by_matching = (id: Id.t): (t => Aba.t(t, Tile.t)) => | p => L(p), ); -// module Match = Tile.Match.Make(Orientation.R); let rec reassemble = (seg: t): t => switch (incomplete_tiles(seg)) { | [] => seg @@ -615,33 +572,6 @@ let trim_secondary: (Direction.t, t) => t = trim_f(trim_l, d, ps); }; -let trim_grout: (Direction.t, t) => t = - (d, ps) => { - /* Trims leading/trailing grout */ - let rec trim_l: list(Base.piece) => list(Base.piece) = - xs => - switch (xs) { - | [] => [] - | [Grout(_), ...xs] => trim_l(xs) - | [_, ..._] => xs - }; - trim_f(trim_l, d, ps); - }; - -let trim_secondary_and_grout: (Direction.t, t) => t = - (d, ps) => { - /* Trims leading/trailing secondary, continuing - to trim around grout until first Tile is reached */ - let rec trim_l: list(Base.piece) => list(Base.piece) = - xs => - switch (xs) { - | [] => [] - | [Secondary(_) | Grout(_), ...xs] => trim_l(xs) - | [_, ..._] => xs - }; - trim_f(trim_l, d, ps); - }; - let trim_grout_around_secondary: (Direction.t, t) => t = (d, ps) => { /* Trims leading/trailing grout, skipping over secondary, @@ -669,26 +599,6 @@ let edge_shape_of = (d: Direction.t, ps: t): option(Nib.Shape.t) => { let edge_direction_of = (d: Direction.t, ps: t): option(Direction.t) => Option.map(Nib.Shape.absolute(d), edge_shape_of(d, ps)); -let rec serialize = (seg: t) => - seg - |> List.concat_map( - fun - | (Piece.Secondary(_) | Grout(_) | Tile({shards: [_], _})) as p => [ - p, - ] - | Tile(t) => { - let shards = - List.map( - Tile.to_piece, - Tile.split_shards(t.id, t.label, t.mold, t.shards), - ); - let children = List.map(serialize, t.children); - Aba.mk(shards, children) - |> Aba.join(s => [s], Fun.id) - |> List.concat; - }, - ); - let sameline_secondary = List.for_all( fun @@ -728,7 +638,8 @@ let expected_sorts = (sort: Sort.t, seg: t): list((int, Sort.t)) => { let rec holes = (segment: t): list(Grout.t) => List.concat_map( fun - | Piece.Secondary(_) => [] + | Piece.Secondary(_) + | Projector(_) => [] | Tile(t) => List.concat_map(holes, t.children) | Grout(g) => [g], segment, @@ -754,3 +665,12 @@ let rec get_incomplete_ids = (seg: t): list(Id.t) => let ids_of_incomplete_tiles_in_bidelimiteds = (seg: t): list(Id.t) => get_childrens(seg) |> List.concat |> get_incomplete_ids; + +let rec ids = (s: t): list(Id.t) => List.concat_map(ids_of_piece, s) +and ids_of_piece = (p: Piece.t): list(Id.t) => + switch (p) { + | Tile(t) => [Piece.id(p), ...ids(List.concat(t.children))] + | Grout(_) + | Secondary(_) + | Projector(_) => [Piece.id(p)] + }; diff --git a/src/haz3lcore/tiles/Shard.re b/src/haz3lcore/tiles/Shard.re deleted file mode 100644 index 63784705cd..0000000000 --- a/src/haz3lcore/tiles/Shard.re +++ /dev/null @@ -1,42 +0,0 @@ -// open Util; -// include Base.Shard; -// module Label = { -// include Label; -// let token = ((n, lbl)) => { -// assert(n >= 0 && n < List.length(lbl)); -// List.nth(lbl, n); -// }; -// let is_next = (d: Direction.t, (n, lbl), (n', lbl')) => -// lbl == lbl' && (d == Right ? n + 1 == n' : n == 1 + n'); -// }; -// let mk = (tile_id: Id.t, label: Label.t, nibs: Nibs.t) => { -// tile_id, -// label, -// nibs, -// }; -// let mk_s = (tile_id: Id.t, label: Base.Tile.Label.t, mold: Mold.t): list(t) => -// label -// |> List.mapi((i, _) => -// mk(tile_id, (i, label), Mold.nibs(~index=i, mold)) -// ); -// let to_piece = s => Base.Piece.Shard(s); -// let tile_label = s => snd(s.label); -// let is_next = (d: Direction.t, l: t, r: t) => -// Label.is_next(d, l.label, r.label); -// let id = s => s.tile_id; -// let index = s => fst(s.label); -// let remold = (s: t) => -// Molds.get(tile_label(s)) -// |> List.map(mold => {...s, nibs: Mold.nibs(~index=index(s), mold)}) -// |> ListUtil.dedup; -// let consistent_molds = (shards: list(t)): list(Mold.t) => -// switch (shards) { -// | [] => raise(Invalid_argument("Shard.consistent")) -// | [s, ..._] => -// Molds.get(tile_label(s)) -// |> List.filter(mold => -// shards -// |> List.for_all(s => s.nibs == Mold.nibs(~index=index(s), mold)) -// ) -// }; -// let shapes = ({nibs: (l, r), _}: t) => (l.shape, r.shape); diff --git a/src/haz3lcore/tiles/Skel.re b/src/haz3lcore/tiles/Skel.re index 8d11c40961..a00f6b1dfd 100644 --- a/src/haz3lcore/tiles/Skel.re +++ b/src/haz3lcore/tiles/Skel.re @@ -1,5 +1,4 @@ open Util; -open Sexplib.Std; [@deriving (show({with_path: false}), sexp, yojson)] type t = @@ -9,13 +8,6 @@ type t = | Bin(t, root, t) and root = Aba.t(int, t); -// let rec size = -// fun -// | Op(_) => 1 -// | Pre(_, r) => 1 + size(r) -// | Post(l, _) => size(l) + 1 -// | Bin(l, _, r) => size(l) + 1 + size(r); - // TODO(d): rename to reflect aba let root = fun @@ -24,36 +16,6 @@ let root = | Post(_, r) | Bin(_, r, _) => r; -// let children = -// fun -// | Op(_) => [] -// | Pre(_, skel) => [(Direction.Right, skel)] -// | Post(skel, _) => [(Left, skel)] -// | Bin(l, _, r) => [(Left, l), (Right, r)]; - -// returns inclusive lower bound, exclusive upper bound -// let rec range = -// fun -// | Op(n) => (n, n + 1) -// | Pre(n, r) => (n, snd(range(r))) -// | Post(l, n) => (fst(range(l)), n + 1) -// | Bin(l, _, r) => (fst(range(l)), snd(range(r))); - -// let rec skel_at = (n, skel) => -// switch (skel) { -// | Op(m) => n == m ? skel : raise(Invalid_argument("Skel.skel_at")) -// | Pre(m, r) => n == m ? skel : skel_at(n, r) -// | Post(l, m) => n == m ? skel : skel_at(n, l) -// | Bin(l, m, r) => -// if (n < m) { -// skel_at(n, l); -// } else if (n > m) { -// skel_at(n, r); -// } else { -// skel; -// } -// }; - exception Input_contains_secondary; exception Nonconvex_segment; @@ -79,6 +41,8 @@ let rel = (p1: Piece.t, p2: Piece.t): option(rel) => | Convex => Some(Lt) | Concave => Some(Gt) } + | (Projector(_), _) => None + | (_, Projector(_)) => None | (Tile(t1), Tile(t2)) => open Labels; let lbl1 = (==)(t1.label); diff --git a/src/haz3lcore/tiles/Tile.re b/src/haz3lcore/tiles/Tile.re index 10c7c41e42..df9350c4ff 100644 --- a/src/haz3lcore/tiles/Tile.re +++ b/src/haz3lcore/tiles/Tile.re @@ -22,7 +22,6 @@ let has_end = (d: Direction.t, t) => | Left => l_shard(t) == 0 | Right => r_shard(t) == List.length(t.label) - 1 }; -let has_ends = t => has_end(Left, t) && has_end(Right, t); let nibs = (t: t) => { let (l, _) = Mold.nibs(~index=l_shard(t), t.mold); @@ -55,9 +54,6 @@ let contained_children = (t: t): list((t, Base.segment, t)) => (l, child, r); }); -// let remold = (t: t): list(t) => -// Molds.get(t.label) |> List.map(mold => {...t, mold}); - let split_shards = (id, label, mold, shards) => shards |> List.map(i => {id, label, mold, shards: [i], children: []}); @@ -105,54 +101,3 @@ let pop_r = (tile: t): (segment, piece) => disassemble(tile) |> ListUtil.split_last_opt |> OptUtil.get_or_raise(Empty_tile); - -// let unique_mold = _ => failwith("todo unique_mold"); - -// module Match = { -// type tile = t; - -// module Make = (O: Orientation.S) => { -// [@deriving (show({with_path: false}), sexp, yojson)] -// type t = Aba.t(Shard.t, segment); - -// let id = (m: t) => Aba.hd(m).tile_id; - -// let label = (m: t) => snd(Aba.hd(m).label); - -// let shards: t => list(Shard.t) = Aba.get_as; -// // let children: t => list(segment) = Aba.get_bs; - -// let length = (m: t) => List.length(shards(m)); - -// let mold = (m: t) => { -// let molds = -// switch (Shard.consistent_molds(shards(m))) { -// | [] => -// // this should only happen upon construct/destruct, -// // in which case everything will be subsequently remolded -// Molds.get(label(m)) -// | [_, ..._] as molds => molds -// }; -// assert(molds != []); -// List.hd(molds); -// }; - -// let children = m => -// List.map(ListUtil.rev_if(O.d == Left), Aba.get_bs(m)); - -// let join = (m: t): segment => -// m |> Aba.join(s => [Shard.to_piece(s)], Fun.id) |> List.flatten; - -// let complete = (m: t): option(tile) => { -// let id = id(m); -// let label = label(m); -// let mold = mold(m); -// length(m) == Label.length(label) -// ? { -// let children = ListUtil.rev_if(O.d == Left, children(m)); -// Some(Base.Tile.{id, label, mold, children}); -// } -// : None; -// }; -// }; -// }; diff --git a/src/haz3lcore/tiles/Token.re b/src/haz3lcore/tiles/Token.re index 907f1bbcd3..8b68de1eb3 100644 --- a/src/haz3lcore/tiles/Token.re +++ b/src/haz3lcore/tiles/Token.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; // make an enum [@deriving (show({with_path: false}), sexp, yojson)] diff --git a/src/haz3lcore/zipper/Ancestor.re b/src/haz3lcore/zipper/Ancestor.re index c0342da0c8..498b18b93e 100644 --- a/src/haz3lcore/zipper/Ancestor.re +++ b/src/haz3lcore/zipper/Ancestor.re @@ -1,4 +1,3 @@ -open Sexplib.Std; open Util; exception Empty_shard_affix; @@ -47,19 +46,9 @@ let sorted_children = (a: t) => { (l, r); }; -// TODO flatten with shard indices -// let step = (frame: t): step => { -// let (prefix, _) = frame.children; -// List.length(prefix); -// }; - let remold = (a: t): list(t) => Molds.get(a.label) |> List.map(mold => {...a, mold}); -// let sort = (frame: t): Sort.t => { -// assert(step(frame) >= 0 && step(frame) < List.length(frame.mold.in_)); -// List.nth(frame.mold.in_, step(frame)); -// }; let sort = (a: t): Sort.t => { let (pre, suf) = a.shards; switch (ListUtil.split_last_opt(pre), suf) { @@ -107,48 +96,3 @@ let reassemble = (match_l: Aba.t(Tile.t, Segment.t) as 'm, match_r: 'm): t => { children: (t_l.children, t_r.children), }; }; - -// module Match = { -// module Prefix = Tile.Match.Make(Orientation.L); -// module Suffix = Tile.Match.Make(Orientation.R); - -// type ancestor = t; -// type t = (Prefix.t, Suffix.t); - -// let id = ((pre, _): t) => Prefix.id(pre); - -// let shards = ((pre, suf): t) => -// List.rev(Prefix.shards(pre)) @ Suffix.shards(suf); - -// let label = ((_, suf)) => Suffix.label(suf); - -// let length = ((pre, suf)) => Prefix.length(pre) + Suffix.length(suf); - -// let children = ((pre, suf)) => ( -// Prefix.children(pre), -// Suffix.children(suf), -// ); - -// let mold = (m: t) => { -// let molds = -// switch (Shard.consistent_molds(shards(m))) { -// | [] => -// // this should only happen upon construct/destruct, -// // in which case everything will be subsequently remolded -// Molds.get(label(m)) -// | [_, ..._] as molds => molds -// }; -// assert(molds != []); -// List.hd(molds); -// }; - -// let join = ((pre, suf): t) => (Prefix.join(pre), Suffix.join(suf)); - -// let complete = (m: t): option(ancestor) => { -// let id = id(m); -// let label = label(m); -// let mold = mold(m); -// length(m) == Tile.Label.length(label) -// ? Some({id, label, mold, children: children(m)}) : None; -// }; -// }; diff --git a/src/haz3lcore/zipper/Ancestors.re b/src/haz3lcore/zipper/Ancestors.re index 84f209fe34..2acc7d0838 100644 --- a/src/haz3lcore/zipper/Ancestors.re +++ b/src/haz3lcore/zipper/Ancestors.re @@ -1,4 +1,3 @@ -open Sexplib.Std; open Util; [@deriving (show({with_path: false}), sexp, yojson)] @@ -23,55 +22,6 @@ let zip_gen = (seg: Segment.t, (a, (pre, suf)): generation): Segment.t => pre @ [Piece.Tile(Ancestor.zip(seg, a)), ...suf]; let zip = (seg: Segment.t, ancs: t) => ancs |> List.fold_left(zip_gen, seg); -let disassemble = ancs => - ancs - |> List.map(((a, sibs)) => - Siblings.concat([Ancestor.disassemble(a), sibs]) - ) - |> Siblings.concat; - -// let remold = (ancestors: t): list(t) => -// List.fold_right( -// ((a, sibs), remolded) => { -// open ListUtil.Syntax; -// let+ ancestors = remolded -// and+ sibs = Siblings.remold(sibs) -// and+ a = Ancestor.remold(a); -// [(a, sibs), ...ancestors]; -// }, -// ancestors, -// [empty], -// ); - -let skel = ((a, (pre, suf)): generation): Skel.t => { - let n = List.length(pre); - let a = (n, Piece.Tile(Ancestor.zip(Segment.empty, a))); - let pre = - pre - |> List.mapi((i, p) => (i, p)) - |> List.filter(((_, p)) => !Piece.is_secondary(p)); - let suf = - suf - |> List.mapi((i, p) => (n + 1 + i, p)) - |> List.filter(((_, p)) => !Piece.is_secondary(p)); - Skel.mk(pre @ [a, ...suf]); -}; - -// let sorts = (i, (a, (pre, suf)): generation) => { -// let n = List.length(pre); -// if (i < List.length(pre)) { -// List.nth_opt(pre, i) -// |> Option.map(Piece.sort) -// |> OptUtil.get_or_raise(Invalid_argument("Ancestors.sort_out")) -// } else if (i > n) { -// List.nth_opt(suf, i - 1 - n) -// |> Option.map(Piece.sort) -// |> OptUtil.get_or_raise(Invalid_argument("Ancestors.sort_out")) -// } else { -// a.mold.out; -// }; -// }; - let regrout = (ancs: t) => List.fold_right( ((a, sibs): generation, regrouted) => { diff --git a/src/haz3lcore/zipper/Backpack.re b/src/haz3lcore/zipper/Backpack.re index fe73d401fa..b704e36721 100644 --- a/src/haz3lcore/zipper/Backpack.re +++ b/src/haz3lcore/zipper/Backpack.re @@ -1,4 +1,3 @@ -open Sexplib.Std; open Util; module ShardInfo = { diff --git a/src/haz3lcore/zipper/Editor.re b/src/haz3lcore/zipper/Editor.re index 1ee7c9fd3b..cd05476fd9 100644 --- a/src/haz3lcore/zipper/Editor.re +++ b/src/haz3lcore/zipper/Editor.re @@ -1,41 +1,102 @@ -open Sexplib.Std; open Util; -module Meta = { +module CachedStatics = { + type t = { + term: UExp.t, + info_map: Statics.Map.t, + error_ids: list(Id.t), + }; + + let empty: t = { + term: UExp.{ids: [Id.invalid], copied: false, term: Tuple([])}, + info_map: Id.Map.empty, + error_ids: [], + }; + + let init = (~settings: CoreSettings.t, z: Zipper.t): t => { + // Modify here to allow passing in an initial context + let ctx_init = Builtins.ctx_init; + let term = MakeTerm.from_zip_for_sem(z).term; + let info_map = Statics.mk(settings, ctx_init, term); + let error_ids = Statics.Map.error_ids(info_map); + {term, info_map, error_ids}; + }; + + let init = (~settings: CoreSettings.t, z: Zipper.t) => + settings.statics ? init(~settings, z) : empty; + + let next = + (~settings: CoreSettings.t, a: Action.t, z: Zipper.t, old_statics: t): t => + if (!settings.statics) { + empty; + } else if (!Action.is_edit(a)) { + old_statics; + } else { + init(~settings, z); + }; +}; + +module CachedSyntax = { type t = { - col_target: int, - touched: Touched.t, - measured: Measured.t, - term_ranges: TermRanges.t, - unselected: Segment.t, segment: Segment.t, - view_term: Term.UExp.t, - terms: TermMap.t, + measured: Measured.t, tiles: TileMap.t, holes: list(Grout.t), - buffer_ids: list(Id.t), + selection_ids: list(Id.t), + term: UExp.t, + /* This term, and the term-derived data structured below, may differ + * from the term used for semantics. These terms are identical when + * the backpack is empty. If the backpack is non-empty, then when we + * make the term for semantics, we attempt to empty the backpack + * according to some simple heuristics (~ try to empty it greedily + * while moving rightwards from the current caret position). + * this is currently necessary to have the cursorinfo/completion + * workwhen the backpack is nonempty. + * + * This is a brittle part of the current implementation. there are + * some other comments at some of the weakest joints; the biggest + * issue is that dropping the backpack can add/remove grout, causing + * certain ids to be present/non-present unexpectedly. */ + term_ranges: TermRanges.t, + terms: TermMap.t, + projectors: Id.Map.t(Base.projector), }; - let init = (z: Zipper.t) => { - let unselected = Zipper.unselect_and_zip(z); - let (view_term, terms) = MakeTerm.go(unselected); + let init = (z, info_map): t => { + let segment = Zipper.unselect_and_zip(z); + let MakeTerm.{term, terms, projectors} = MakeTerm.go(segment); { - col_target: 0, - touched: Touched.empty, - measured: Measured.of_segment(unselected), - unselected, - term_ranges: TermRanges.mk(unselected), - segment: Zipper.zip(z), - tiles: TileMap.mk(unselected), - view_term, + segment, + term_ranges: TermRanges.mk(segment), + tiles: TileMap.mk(segment), + holes: Segment.holes(segment), + measured: Measured.of_segment(segment, info_map), + selection_ids: Selection.selection_ids(z.selection), + term, terms, - holes: Segment.holes(unselected), - buffer_ids: Selection.buffer_ids(z.selection), + projectors, }; }; + let next = (a: Action.t, z: Zipper.t, info_map, old: t) => + Action.is_edit(a) + ? init(z, info_map) + : {...old, selection_ids: Selection.selection_ids(z.selection)}; +}; + +module Meta = { + type t = { + col_target: int, + statics: CachedStatics.t, + syntax: CachedSyntax.t, + }; + + let init = (~settings: CoreSettings.t, z: Zipper.t) => { + let statics = CachedStatics.init(~settings, z); + {col_target: 0, statics, syntax: CachedSyntax.init(z, statics.info_map)}; + }; + module type S = { - let touched: Touched.t; let measured: Measured.t; let term_ranges: TermRanges.t; let col_target: int; @@ -43,9 +104,8 @@ module Meta = { let module_of_t = (m: t): (module S) => (module { - let touched = m.touched; - let measured = m.measured; - let term_ranges = m.term_ranges; + let measured = m.syntax.measured; + let term_ranges = m.syntax.term_ranges; let col_target = m.col_target; }); @@ -55,36 +115,16 @@ module Meta = { let yojson_of_t = _ => failwith("Editor.Meta.yojson_of_t"); let t_of_yojson = _ => failwith("Editor.Meta.t_of_yojson"); - let next = - (~effects: list(Effect.t)=[], a: Action.t, z: Zipper.t, meta: t): t => { - let {touched, measured, col_target, _} = meta; - let touched = Touched.update(Time.tick(), effects, touched); - let is_edit = Action.is_edit(a); - let unselected = is_edit ? Zipper.unselect_and_zip(z) : meta.unselected; - let measured = - is_edit - ? Measured.of_segment(~touched, ~old=measured, unselected) : measured; + let next = (~settings: CoreSettings.t, a: Action.t, z: Zipper.t, meta: t): t => { + let syntax = CachedSyntax.next(a, z, meta.statics.info_map, meta.syntax); + let statics = CachedStatics.next(~settings, a, z, meta.statics); let col_target = switch (a) { | Move(Local(Up | Down)) - | Select(Resize(Local(Up | Down))) => col_target - | _ => Zipper.caret_point(measured, z).col + | Select(Resize(Local(Up | Down))) => meta.col_target + | _ => (Zipper.caret_point(syntax.measured))(. z).col }; - let (view_term, terms) = - is_edit ? MakeTerm.go(unselected) : (meta.view_term, meta.terms); - { - col_target, - touched, - measured, - unselected, - term_ranges: is_edit ? TermRanges.mk(unselected) : meta.term_ranges, - segment: Zipper.zip(z), - tiles: is_edit ? TileMap.mk(unselected) : meta.tiles, - view_term, - terms, - holes: is_edit ? Segment.holes(unselected) : meta.holes, - buffer_ids: Selection.buffer_ids(z.selection), - }; + {col_target, syntax, statics}; }; }; @@ -96,11 +136,14 @@ module State = { meta: Meta.t, }; - let init = zipper => {zipper, meta: Meta.init(zipper)}; + let init = (zipper, ~settings: CoreSettings.t) => { + zipper, + meta: Meta.init(zipper, ~settings), + }; - let next = (~effects: list(Effect.t)=[], a: Action.t, z: Zipper.t, state) => { + let next = (~settings: CoreSettings.t, a: Action.t, z: Zipper.t, state) => { zipper: z, - meta: Meta.next(~effects, a, z, state.meta), + meta: Meta.next(~settings, a, z, state.meta), }; }; @@ -125,38 +168,35 @@ type t = { read_only: bool, }; -let init = (~read_only=false, z) => { - state: State.init(z), +let init = (~read_only=false, z, ~settings: CoreSettings.t) => { + state: State.init(z, ~settings), history: History.empty, read_only, }; -let empty = id => init(~read_only=false, Zipper.init(id)); - -let update_z = (f: Zipper.t => Zipper.t, ed: t) => { - ...ed, - state: { - ...ed.state, - zipper: f(ed.state.zipper), - }, -}; -let put_z = (z: Zipper.t) => update_z(_ => z); - -let update_z_opt = (f: Zipper.t => option(Zipper.t), ed: t) => { - open OptUtil.Syntax; - let+ z = f(ed.state.zipper); - put_z(z, ed); -}; let new_state = - (~effects: list(Effect.t)=[], a: Action.t, z: Zipper.t, ed: t): t => { - let state = State.next(~effects, a, z, ed.state); - let history = History.add(a, ed.state, ed.history); + (~settings: CoreSettings.t, a: Action.t, z: Zipper.t, ed: t): t => { + let state = State.next(~settings, a, z, ed.state); + let history = + Action.is_historic(a) + ? History.add(a, ed.state, ed.history) : ed.history; {state, history, read_only: ed.read_only}; }; -let caret_point = (ed: t): Measured.Point.t => { - let State.{zipper, meta} = ed.state; - Zipper.caret_point(meta.measured, zipper); +let update_statics = (~settings: CoreSettings.t, ed: t): t => { + /* Use this function to force a statics update when (for example) + * changing the statics settings */ + let statics = CachedStatics.init(~settings, ed.state.zipper); + { + ...ed, + state: { + ...ed.state, + meta: { + ...ed.state.meta, + statics, + }, + }, + }; }; let undo = (ed: t) => @@ -201,3 +241,6 @@ let trailing_hole_ctx = (ed: t, info_map: Statics.Map.t) => { }; }; }; + +let indicated_projector = (editor: t) => + Projector.indicated(editor.state.zipper); diff --git a/src/haz3lcore/zipper/EditorUtil.re b/src/haz3lcore/zipper/EditorUtil.re index 838287010a..f8761a6ba1 100644 --- a/src/haz3lcore/zipper/EditorUtil.re +++ b/src/haz3lcore/zipper/EditorUtil.re @@ -1,90 +1,51 @@ -let editor_of_code = (~read_only=false, code: CodeString.t) => { - switch (Printer.zipper_of_string(code)) { - | None => None - | Some(z) => Some(Editor.init(~read_only, z)) - }; -}; - -let editors_for = - (~read_only=false, xs: list('a), f: 'a => option(string)) - : (int, list(('a, option(Editor.t)))) => { - let zs = - List.fold_left( - (acc_zs, a) => { - switch (f(a)) { - | Some(str) => - switch (Printer.zipper_of_string(str)) { - | None => acc_zs @ [(a, Some(Zipper.init()))] - | Some(z) => acc_zs @ [(a, Some(z))] - } - | None => acc_zs @ [(a, None)] - } - }, - [], - xs, - ); - ( - 0, - List.map( - ((a, sz)) => - switch (sz) { - | Some(z) => (a, Some(Editor.init(z, ~read_only))) - | None => (a, None) - }, - zs, - ), +let rec append_exp = (e1: Exp.t, e2: Exp.t): Exp.t => { + Exp.( + switch (e1.term) { + | EmptyHole + | Invalid(_) + | MultiHole(_) + | DynamicErrorHole(_) + | FailedCast(_) + | Undefined + | Deferral(_) + | Bool(_) + | Int(_) + | Float(_) + | String(_) + | ListLit(_) + | Constructor(_) + | Closure(_) + | Fun(_) + | TypFun(_) + | FixF(_) + | Tuple(_) + | Var(_) + | Ap(_) + | TypAp(_) + | DeferredAp(_) + | If(_) + | Test(_) + | Parens(_) + | Cons(_) + | ListConcat(_) + | UnOp(_) + | BinOp(_) + | BuiltinFun(_) + | Cast(_) + | Dot(_) + | Match(_) => Exp.{ids: [Id.mk()], copied: false, term: Seq(e1, e2)} + | Seq(e11, e12) => + let e12' = append_exp(e12, e2); + {ids: e1.ids, copied: false, term: Seq(e11, e12')}; + | Filter(kind, ebody) => + let ebody' = append_exp(ebody, e2); + {ids: e1.ids, copied: false, term: Filter(kind, ebody')}; + | Let(p, edef, ebody) => + let ebody' = append_exp(ebody, e2); + {ids: e1.ids, copied: false, term: Let(p, edef, ebody')}; + | TyAlias(tp, tdef, ebody) => + let ebody' = append_exp(ebody, e2); + {ids: e1.ids, copied: false, term: TyAlias(tp, tdef, ebody')}; + } ); }; - -let editors_of_strings = (~read_only=false, xs: list(string)) => { - let (i, aes) = editors_for(xs, x => Some(x), ~read_only); - (i, List.map(((_, oe)) => Option.get(oe), aes)); -}; - -let rec append_exp = (e1: TermBase.UExp.t, e2: TermBase.UExp.t) => { - switch (e1.term) { - | EmptyHole - | Invalid(_) - | MultiHole(_) - | Triv - | Deferral(_) - | Bool(_) - | Int(_) - | Float(_) - | String(_) - | ListLit(_) - | Constructor(_) - | Fun(_) - | TypFun(_) - | Tuple(_) - | Var(_) - | Ap(_) - | TypAp(_) - | DeferredAp(_) - | Pipeline(_) - | If(_) - | Test(_) - | Parens(_) - | Cons(_) - | ListConcat(_) - | UnOp(_) - | BinOp(_) - | Dot(_) - | Match(_) => TermBase.UExp.{ids: [Id.mk()], term: Seq(e1, e2)} - | Seq(e11, e12) => - let e12' = append_exp(e12, e2); - TermBase.UExp.{ids: e1.ids, term: Seq(e11, e12')}; - | Filter(act, econd, ebody) => - let ebody' = append_exp(ebody, e2); - TermBase.UExp.{ids: e1.ids, term: Filter(act, econd, ebody')}; - | Let(p, edef, ebody) => - let ebody' = append_exp(ebody, e2); - TermBase.UExp.{ids: e1.ids, term: Let(p, edef, ebody')}; - | Module(p, edef, ebody) => - let ebody' = append_exp(ebody, e2); - TermBase.UExp.{ids: e1.ids, term: Module(p, edef, ebody')}; - | TyAlias(tp, tdef, ebody) => - let ebody' = append_exp(ebody, e2); - TermBase.UExp.{ids: e1.ids, term: TyAlias(tp, tdef, ebody')}; - }; -}; diff --git a/src/haz3lcore/zipper/IncompleteBidelim.re b/src/haz3lcore/zipper/IncompleteBidelim.re deleted file mode 100644 index 1ffd1f16c2..0000000000 --- a/src/haz3lcore/zipper/IncompleteBidelim.re +++ /dev/null @@ -1,32 +0,0 @@ -type t = Id.Map.t(list(int)); - -let t = ref(Id.Map.empty); - -let contains = (id, i): bool => - switch (Id.Map.find_opt(id, t^)) { - | None => false - | Some(is) => List.mem(i, is) - }; - -let clear = () => { - t := Id.Map.empty; -}; - -// assumes seg is fully assembled -let set = (seg: Base.segment): unit => - t := - seg - |> List.filter_map( - fun - | Piece.Tile(t) => { - let (l_shard, r_shard) = Tile.(l_shard(t), r_shard(t)); - let l = l_shard == 0 ? [] : [l_shard - 1]; - let r = r_shard == List.length(t.label) - 1 ? [] : [r_shard]; - let lr = l @ r; - lr == [] ? None : Some((t.id, l @ r)); - } - | Grout(_) - | Secondary(_) => None, - ) - |> List.to_seq - |> Id.Map.of_seq; diff --git a/src/haz3lcore/zipper/Orientation.re b/src/haz3lcore/zipper/Orientation.re deleted file mode 100644 index e832d697bc..0000000000 --- a/src/haz3lcore/zipper/Orientation.re +++ /dev/null @@ -1,15 +0,0 @@ -open Util; - -module type S = { - let d: Direction.t; - let orient: (('a, 'a)) => ('a, 'a); -}; - -module L: S = { - let d = Direction.Left; - let orient = ((l, r)) => (l, r); -}; -module R: S = { - let d = Direction.Right; - let orient = ((l, r)) => (r, l); -}; diff --git a/src/haz3lcore/zipper/PersistentZipper.re b/src/haz3lcore/zipper/PersistentZipper.re index 423bc7a5f9..a1bbc094d2 100644 --- a/src/haz3lcore/zipper/PersistentZipper.re +++ b/src/haz3lcore/zipper/PersistentZipper.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type t = { diff --git a/src/haz3lcore/zipper/Printer.re b/src/haz3lcore/zipper/Printer.re index 70ea237eea..e6af6911ec 100644 --- a/src/haz3lcore/zipper/Printer.re +++ b/src/haz3lcore/zipper/Printer.re @@ -1,13 +1,6 @@ open Util; open Util.OptUtil.Syntax; -[@deriving (show({with_path: false}), yojson)] -type t = { - code: list(string), - selection: list(string), - backpack: list(list(string)), -}; - let seg_of_zip = Zipper.seg_without_buffer; let rec of_segment = (~holes, seg: Segment.t): string => @@ -20,6 +13,7 @@ and of_piece = (~holes, p: Piece.t): string => | Grout({shape: Convex, _}) => " " | Secondary(w) => Secondary.is_linebreak(w) ? "\n" : Secondary.get_string(w.content) + | Projector(p) => of_piece(~holes, p.syntax) } and of_tile = (~holes, t: Tile.t): string => Aba.mk(t.shards, t.children) @@ -39,7 +33,7 @@ let to_rows = ( ~holes: option(string), ~measured: Measured.t, - ~caret: option(Measured.Point.t), + ~caret: option(Point.t), ~indent: string, ~segment: Segment.t, ) @@ -60,30 +54,33 @@ let to_rows = }; }; -let pretty_print = (~measured: Measured.t, z: Zipper.t): string => +let measured = z => + z |> Zipper.seg_without_buffer |> Measured.of_segment(_, Id.Map.empty); + +let pretty_print = (~holes: option(string)=Some(""), z: Zipper.t): string => to_rows( - ~holes=None, - ~measured, + ~holes, + ~measured=measured(z), ~caret=None, ~indent=" ", ~segment=seg_of_zip(z), ) |> String.concat("\n"); -let to_string_editor = - (~holes: option(string)=Some(""), editor: Editor.t): string => +let zipper_to_string = + (~holes: option(string)=Some(""), z: Zipper.t): string => to_rows( ~holes, - ~measured=editor.state.meta.measured, + ~measured=measured(z), ~caret=None, ~indent="", - ~segment=seg_of_zip(editor.state.zipper), + ~segment=seg_of_zip(z), ) |> String.concat("\n"); let to_string_selection = (editor: Editor.t): string => to_rows( - ~measured=editor.state.meta.measured, + ~measured=measured(editor.state.zipper), ~caret=None, ~indent=" ", ~holes=None, @@ -91,43 +88,11 @@ let to_string_selection = (editor: Editor.t): string => ) |> String.concat("\n"); -let to_log = (~measured: Measured.t, z: Zipper.t): t => { - code: - to_rows( - ~holes=None, - ~measured, - ~caret=Some(Zipper.caret_point(measured, z)), - ~indent=" ", - ~segment=seg_of_zip(z), - ), - selection: z.selection.content |> of_segment(~holes=None) |> lines_to_list, - backpack: - List.map( - (s: Selection.t) => - s.content |> of_segment(~holes=None) |> lines_to_list, - z.backpack, - ), -}; - -let to_log_flat = (~measured, z: Zipper.t): string => { - let {code, selection, backpack} = to_log(~measured, z); - Printf.sprintf( - "CODE:\n%s\nSELECTION:\n%s\n%s\n", - String.concat("\n", code), - String.concat("\n", selection), - backpack - |> List.mapi((i, b) => - Printf.sprintf("BP(%d):\n %s\n", i, String.concat("\n", b)) - ) - |> String.concat(""), - ); -}; - let zipper_of_string = (~zipper_init=Zipper.init(), str: string): option(Zipper.t) => { let insert = (z: option(Zipper.t), c: string): option(Zipper.t) => { let* z = z; - try(c == "\r" ? Some(z) : Insert.go(c == "\n" ? Form.linebreak : c, z)) { + try(c == "\r" ? Some(z) : Insert.go(c, z)) { | exn => print_endline("WARN: zipper_of_string: " ++ Printexc.to_string(exn)); None; @@ -136,19 +101,8 @@ let zipper_of_string = str |> Util.StringUtil.to_list |> List.fold_left(insert, Some(zipper_init)); }; -let paste_into_zip = (z: Zipper.t, str: string): option(Zipper.t) => { - /* HACK(andrew): These two perform calls are a hack to - deal with the fact that pasting something like "let a = b in" - won't trigger the barfing of the "in"; to trigger this, we - insert a space, and then we immediately delete it. */ - let settings = CoreSettings.off; - let* z = zipper_of_string(~zipper_init=z, str); - switch (Perform.go_z(~settings, Insert(" "), z)) { - | Error(_) => None - | Ok(z) => - switch (Perform.go_z(~settings, Destruct(Left), z)) { - | Error(_) => None - | Ok(z) => Some(z) - } - }; -}; +/* This serializes the current editor to text, resets the current + editor, and then deserializes. It is intended as a (tactical) + nuclear option for weird backpack states */ +let reparse = z => + zipper_of_string(~zipper_init=Zipper.init(), zipper_to_string(z)); diff --git a/src/haz3lcore/zipper/Projector.re b/src/haz3lcore/zipper/Projector.re new file mode 100644 index 0000000000..82b036b821 --- /dev/null +++ b/src/haz3lcore/zipper/Projector.re @@ -0,0 +1,49 @@ +open ProjectorBase; + +/* After adding a new projector module, add it here so that + * it can be instantiated. The first-class module created by + * this function must be reified whenever projector methods + * are to be called; see `shape` below for an example */ +let to_module = (kind: Base.kind): (module Cooked) => + switch (kind) { + | Fold => (module Cook(FoldProj.M)) + | Info => (module Cook(InfoProj.M)) + | Slider => (module Cook(SliderProj.M)) + | SliderF => (module Cook(SliderFProj.M)) + | Checkbox => (module Cook(CheckboxProj.M)) + | TextArea => (module Cook(TextAreaProj.M)) + }; + +let shape = (p: Base.projector, info: info): shape => { + let (module P) = to_module(p.kind); + P.placeholder(p.model, info); +}; + +/* A projector is replaced by a placeholder in the underlying + * editor for view purposes. This projector is an all-whitespace + * monotile. Currently there is no explicit notion of placeholders + * in the zipper; a tile consisting of any number of whitespaces + * is considered a placeholder. This could be made more principled. + * Note that a placeholder retains the UUID of the underlying. */ +let placeholder = (p: Base.projector, ci: option(Info.t)): string => + switch (shape(p, {id: p.id, syntax: p.syntax, ci})) { + | Inline(width) => String.make(width, ' ') + | Block({row, col}) => String.make(row - 1, '\n') ++ String.make(col, ' ') + }; + +/* Currently projection is limited to convex pieces */ +let minimum_projection_condition = (syntax: syntax): bool => + Piece.is_convex(syntax); + +/* Returns the projector at the caret, if any */ +let indicated = (z: ZipperBase.t) => { + open Util.OptUtil.Syntax; + let* id = Indicated.index(z); + let* (p, _, _) = Indicated.piece(z); + let+ projector = + switch (p) { + | Projector(pr) => Some(pr) + | _ => None + }; + (id, projector); +}; diff --git a/src/haz3lcore/zipper/ProjectorBase.re b/src/haz3lcore/zipper/ProjectorBase.re new file mode 100644 index 0000000000..5abe811d76 --- /dev/null +++ b/src/haz3lcore/zipper/ProjectorBase.re @@ -0,0 +1,153 @@ +open Util; +open Virtual_dom.Vdom; + +[@deriving (show({with_path: false}), sexp, yojson)] +type t = Base.kind; + +/* Projectors currently have two options for placeholder + * shapes: A inline display of a given length, or a block + * display with given length & height. Both of these can + * depend on the projector model and info package */ +[@deriving (show({with_path: false}), sexp, yojson)] +type shape = + | Inline(int) + | Block(Point.t); + +/* The type of syntax which a projector can replace. + * Right now projectors can replace a single piece */ +[@deriving (show({with_path: false}), sexp, yojson)] +type syntax = Base.piece; + +/* Global actions available to handlers in all projectors */ +type external_action = + | Remove /* Remove projector entirely */ + | Escape(Util.Direction.t) /* Pass focus to parent editor */ + | SetSyntax(syntax); /* Set underlying syntax */ + +/* External info fed to all projectors. Eventually + * dynamic information will be added here. Projector + * position and dimensions in base editor could be + * added here if needed */ +[@deriving (show({with_path: false}), sexp, yojson)] +type info = { + id: Id.t, + syntax, + ci: option(Info.t), +}; + +/* To add a new projector: + * 1. Create a new module implementing Projector (e.g. FoldCore) + * 2. Add an entry for it in Base.projector_kind + * 3. Register the module in Projector.to_module + * 4. If you want to expose the projector via a keyboard + * shortcut, see the existing entry for Fold in Keyboard + * 5. If you want to expose the projector in the projector + * panel bottom bar UI, update ProjectorView.name, + * ProjectorView.of_name, and ProjectorView.applicable_projectors + * 6. If you want to manually manage the projector as part of + * the update cycle, see the implementations of the SetIndicated + * and Remove actions in ProjectorPerform for how to manually + * add/remove projectors from an editor */ +module type Projector = { + /* The internal model type of the projector which will + * be serialized and persisted. Use `unit` if you don't + * need other state beyond the underlying syntax */ + [@deriving (show({with_path: false}), sexp, yojson)] + type model; + /* An internal action type to be used in actions which + * update the model. Use `unit` if the basic projector + * actions (type `action`) above suffice */ + [@deriving (show({with_path: false}), sexp, yojson)] + type action; + /* Initial state of the model */ + let init: model; + /* A predicate determining if the given underlying + * syntax (currently limited to convex pieces) is + * supported by this projector. This is used to gate + * adding the projector */ + let can_project: Base.piece => bool; + /* Does this projector have internal position states, + * overriding the editor caret & keyboard handlers? + * If yes, the focus method will be called when this + * projector is either clicked on or if left/right + * is pressed when the caret is to the immediate + * right/left of the projector */ + let can_focus: bool; + /* Renders a DOM view for the projector, given the + * model, an info packet (see info type for details), + * and has two callbacks: ~parent for parent editor + * actions(see external_action type above), and ~local + * for this projector's local update function. */ + let view: + ( + model, + ~info: info, + ~local: action => Ui_effect.t(unit), + ~parent: external_action => Ui_effect.t(unit) + ) => + Node.t; + /* How much space should be left in the code view for + * this projector? This determines how the base code + * view is laid out, including how movement around the + * projector works. In principle this could be derived + * from the view, but this is awkward to do so for now + * projector writers are responsible for keeping these + * in sync with each other. */ + let placeholder: (model, info) => shape; + /* Update the local projector model given an action */ + let update: (model, action) => model; + /* Does whatever needs to be done to give a projector + * keyboard focus. Right now this is only for side + * effects but could be extended in the future to + * take/return the model if the projector needs to + * maintain a complex internal position state */ + let focus: ((Id.t, option(Direction.t))) => unit; +}; + +/* A cooked projector is the same as the base module + * signature except model & action are serialized so + * they may be used by the Editor without it having + * specialized knowledge of projector internals */ +module type Cooked = + Projector with type model = string and type action = string; + +module Cook = (C: Projector) : Cooked => { + [@deriving (show({with_path: false}), sexp, yojson)] + type model = string; + [@deriving (show({with_path: false}), sexp, yojson)] + type action = string; + let serialize_m = m => m |> C.sexp_of_model |> Sexplib.Sexp.to_string; + let deserialize_m = s => s |> Sexplib.Sexp.of_string |> C.model_of_sexp; + let serialize_a = a => a |> C.sexp_of_action |> Sexplib.Sexp.to_string; + let deserialize_a = s => s |> Sexplib.Sexp.of_string |> C.action_of_sexp; + let init = C.init |> serialize_m; + let can_project = C.can_project; + let can_focus = C.can_focus; + let view = (m, ~info, ~local, ~parent) => + C.view( + deserialize_m(m), + ~info, + ~local=a => local(serialize_a(a)), + ~parent, + ); + let placeholder = m => + m |> Sexplib.Sexp.of_string |> C.model_of_sexp |> C.placeholder; + let update = (m, a) => + C.update(m |> deserialize_m, a |> deserialize_a) |> serialize_m; + let focus = C.focus; +}; + +/* Projectors currently are all convex */ +let shapes = (_: Base.projector) => Nib.Shape.(Convex, Convex); + +/* Projectors currently have a unique molding */ +let mold_of = (p, sort: Sort.t): Mold.t => { + let (l, r) = shapes(p); + { + nibs: { + ({shape: l, sort}, {shape: r, sort}); + }, + out: sort, + in_: [], + }; +}; diff --git a/src/haz3lcore/zipper/Relatives.re b/src/haz3lcore/zipper/Relatives.re index 04a9740130..251cdbc4e9 100644 --- a/src/haz3lcore/zipper/Relatives.re +++ b/src/haz3lcore/zipper/Relatives.re @@ -64,9 +64,6 @@ let delete_parent = ({siblings, ancestors}: t): t => { }; }; -let disassemble = ({siblings, ancestors}: t): Siblings.t => - Siblings.concat([siblings, Ancestors.disassemble(ancestors)]); - let remold = ({siblings, ancestors}: t): t => { let s = Ancestors.sort(ancestors); let siblings = Siblings.remold(siblings, s); @@ -120,24 +117,6 @@ let regrout = (d: Direction.t, {siblings, ancestors}: t): t => { {siblings, ancestors}; }; -let prepend_generation = ((a, sibs): Ancestors.generation, rs: t): t => { - siblings: Siblings.empty, - ancestors: [(a, Siblings.concat([sibs, rs.siblings])), ...rs.ancestors], -}; -let prepend_siblings = (sibs: Siblings.t, rs: t): t => { - ...rs, - siblings: Siblings.concat([sibs, rs.siblings]), -}; - -let concat = (rss: list(t)): t => - List.fold_right( - (rs: t, cat: t) => - List.fold_right(prepend_generation, rs.ancestors, cat) - |> prepend_siblings(rs.siblings), - rss, - empty, - ); - let reassemble_parent = (rs: t): t => switch (rs.ancestors) { | [] => rs @@ -220,58 +199,3 @@ let reassemble = (rs: t): t => { }; rs |> reassemble_siblings |> reassemble_parent |> go; }; - -// let rec reassemble = (rs: t): t => { -// let siblings = Siblings.reassemble(rs.siblings); -// switch (Siblings.incomplete_tiles(siblings)) { -// | ([], _) -// | (_, []) => {...rs, siblings} -// | ([_, ..._], [t, ..._]) => -// switch ( -// siblings -// |> Siblings.split_by_matching(t.id) -// |> TupleUtil.map2(Aba.trim) -// ) { -// | (None, None) => {...rs, siblings} -// | (None, Some((inner_r, match_r, outer_r))) => -// let {siblings: (l, r), ancestors} = -// reassemble({...rs, siblings: (fst(siblings), outer_r)}); -// { -// siblings: ( -// l, -// Segment.concat([inner_r, Ancestor.Match.Suffix.join(match_r), r]), -// ), -// ancestors, -// }; -// | (Some((inner_l, match_l, outer_l)), None) => -// let {siblings: (l, r), ancestors} = -// reassemble({...rs, siblings: (outer_l, snd(rs.siblings))}); -// { -// siblings: ( -// Segment.concat([inner_l, Ancestor.Match.Suffix.join(match_l), l]), -// r, -// ), -// ancestors, -// }; -// | (Some((inner_l, match_l, outer_l)), Some((inner_r, match_r, outer_r))) => -// let match = (match_l, match_r); -// let rs_inner = -// switch (Ancestor.Match.complete(match)) { -// | None => { -// siblings: -// Siblings.concat([ -// (inner_l, inner_r), -// Ancestor.Match.join(match), -// ]), -// ancestors: Ancestors.empty, -// } -// | Some(a) => { -// siblings: (inner_l, inner_r), -// ancestors: [(a, Siblings.empty)], -// } -// }; -// let rs_outer = reassemble({...rs, siblings: (outer_l, outer_r)}); -// concat([rs_inner, rs_outer]); -// } -// }; -// }; diff --git a/src/haz3lcore/zipper/Selection.re b/src/haz3lcore/zipper/Selection.re index e89aba3a99..92d6509fb8 100644 --- a/src/haz3lcore/zipper/Selection.re +++ b/src/haz3lcore/zipper/Selection.re @@ -2,8 +2,8 @@ open Util; [@deriving (show({with_path: false}), sexp, yojson)] type buffer = - | Unparsed - | Parsed; + //| Parsed + | Unparsed; [@deriving (show({with_path: false}), sexp, yojson)] type mode = @@ -31,13 +31,7 @@ let is_buffer: t => bool = | {mode: Buffer(_), _} => true | _ => false; -let buffer_ids = (sel: t): list(Id.t) => { - /* Collect ids of tokens in buffer for styling purposes. This is - * currently necessary as the selection is not persisted through - * unzipping for display */ - let buffer = is_buffer(sel) ? sel.content : []; - Id.Map.bindings(Measured.of_segment(buffer).tiles) |> List.map(fst); -}; +let selection_ids = (sel: t): list(Id.t) => Segment.ids(sel.content); let empty = mk(Segment.empty); @@ -72,5 +66,3 @@ let pop = (sel: t): option((Piece.t, t)) => let (rest, p) = Piece.pop_r(p); Some((p, {...sel, content: content @ rest})); }; - -let split_piece = _: option((Piece.t, t)) => failwith("todo split_piece"); diff --git a/src/haz3lcore/zipper/Siblings.re b/src/haz3lcore/zipper/Siblings.re index 96d254e31e..332b63f8df 100644 --- a/src/haz3lcore/zipper/Siblings.re +++ b/src/haz3lcore/zipper/Siblings.re @@ -1,8 +1,5 @@ open Util; -// module Prefix = Affix.Make(Orientation.L); -// module Suffix = Affix.Make(Orientation.R); - [@deriving (show({with_path: false}), sexp, yojson)] type t = (Segment.t, Segment.t); @@ -27,13 +24,6 @@ let concat = (sibss: list(t)): t => |> PairUtil.map_fst(List.concat) |> PairUtil.map_snd(List.concat); -// let consistent_shards = ((pre, suf): t): bool => { -// let shards_pre = Prefix.shards(pre); -// let shards_suf = Suffix.shards(suf); -// ListUtil.group_by(Shard.id, shards_pre @ shards_suf) -// |> List.for_all(((_, shards)) => Shard.consistent_molds(shards) != []); -// }; - let remold = ((pre, _) as sibs: t, s: Sort.t): t => Segment.remold(zip(sibs), s) |> unzip(List.length(pre)); @@ -44,15 +34,6 @@ let shapes = ((pre, suf): t) => { (l, r); }; -let is_mismatch = ((l, r): t): bool => { - /* predicts if grout is neccessary between siblings */ - switch (Segment.edge_shape_of(Left, r), Segment.edge_shape_of(Right, l)) { - | (None, _) - | (_, None) => false - | (s1, s2) => s1 == s2 - }; -}; - let contains_matching = (t: Tile.t, (pre, suf): t) => Segment.(contains_matching(t, pre) || contains_matching(t, suf)); @@ -103,16 +84,6 @@ let trim_secondary = ((l_sibs, r_sibs): t) => ( Segment.trim_secondary(Left, r_sibs), ); -let trim_grout = ((l_sibs, r_sibs): t) => ( - Segment.trim_grout(Right, l_sibs), - Segment.trim_grout(Left, r_sibs), -); - -let trim_secondary_and_grout = ((l_sibs, r_sibs): t) => ( - Segment.trim_secondary_and_grout(Right, l_sibs), - Segment.trim_secondary_and_grout(Left, r_sibs), -); - let direction_between = ((l, r): t): option(Direction.t) => /* Facing direction of the shared nib between l & r */ switch (Segment.edge_direction_of(Left, r)) { @@ -125,5 +96,3 @@ let mold_fitting_between = (sort: Sort.t, p: Precedence.t, sibs: t): Mold.t => | Some(d) => Mold.chevron(sort, p, d) | None => Mold.mk_op(sort, []) }; - -let sorted_children = TupleUtil.map2(Segment.sorted_children); diff --git a/src/haz3lcore/zipper/Time.re b/src/haz3lcore/zipper/Time.re deleted file mode 100644 index 34a363f279..0000000000 --- a/src/haz3lcore/zipper/Time.re +++ /dev/null @@ -1,15 +0,0 @@ -type t = int; -let t = ref(0); - -let tick = (): t => { - let time = t^; - t := time + 1; - time; -}; - -let lt = (<); - -let min = min; -let max = max; - -let max_time = Int.max_int; diff --git a/src/haz3lcore/zipper/Touched.re b/src/haz3lcore/zipper/Touched.re deleted file mode 100644 index 2a428deb28..0000000000 --- a/src/haz3lcore/zipper/Touched.re +++ /dev/null @@ -1,24 +0,0 @@ -include Id.Map; -type t = Id.Map.t(Time.t); - -module type S = { - let touched: t; -}; - -let update = (t: Time.t, es: list(Effect.t), td: t) => - es - |> List.fold_left( - (td, e: Effect.t) => - switch (e) { - | Delete(id) => td |> remove(id) - | Touch(id) => - td - |> update( - id, - fun - | None => Some(t) - | Some(t') => Some(Time.max(t, t')), - ) - }, - td, - ); diff --git a/src/haz3lcore/zipper/Zipper.re b/src/haz3lcore/zipper/Zipper.re index 61e1cbe04d..f87fb964e6 100644 --- a/src/haz3lcore/zipper/Zipper.re +++ b/src/haz3lcore/zipper/Zipper.re @@ -1,34 +1,6 @@ -open Sexplib.Std; open Util; open OptUtil.Syntax; - -module Caret = { - [@deriving (show({with_path: false}), sexp, yojson)] - type t = - | Outer - | Inner(int, int); - - let decrement: t => t = - fun - | Outer - | Inner(_, 0) => Outer - | Inner(d, c) => Inner(d, c - 1); - - let offset: t => int = - fun - | Outer => 0 - | Inner(_, c) => c + 1; -}; - -// assuming single backpack, shards may appear in selection, backpack, or siblings -[@deriving (show({with_path: false}), sexp, yojson)] -type t = { - selection: Selection.t, - backpack: Backpack.t, - relatives: Relatives.t, - caret: Caret.t, - // col_target: int, -}; +include ZipperBase; let init: unit => t = () => { @@ -39,7 +11,6 @@ let init: unit => t = ancestors: [], }, caret: Outer, - // col_target: 0, }; let next_blank = _ => Id.mk(); @@ -70,17 +41,6 @@ let update_caret = (f: Caret.t => Caret.t, z: t): t => { }; let set_caret = (caret: Caret.t): (t => t) => update_caret(_ => caret); -let update_relatives = (f: Relatives.t => Relatives.t, z: t): t => { - ...z, - relatives: f(z.relatives), -}; - -let update_siblings: (Siblings.t => Siblings.t, t) => t = - f => update_relatives(rs => {...rs, siblings: f(rs.siblings)}); - -let parent = (z: t): option(Piece.t) => - Relatives.parent(~sel=z.selection.content, z.relatives); - let delete_parent = (z: t): t => { ...z, relatives: Relatives.delete_parent(z.relatives), @@ -99,20 +59,6 @@ let unzip = (seg: Segment.t): t => { caret: Outer, }; -let sibs_with_sel = - ( - { - selection: {content, focus, _}, - relatives: {siblings: (l_sibs, r_sibs), _}, - _, - }: t, - ) - : Siblings.t => - switch (focus) { - | Left => (l_sibs, content @ r_sibs) - | Right => (l_sibs @ content, r_sibs) - }; - let pop_backpack = (z: t) => Backpack.pop(Relatives.local_incomplete_tiles(z.relatives), z.backpack); @@ -147,7 +93,7 @@ let clear_unparsed_buffer = (z: t) => let unselect = (~erase_buffer=false, z: t): t => { /* NOTE(andrew): Erase buffer flag only applies to unparsed buffer, * that is, the buffer style that just contains a single flat token. - * Erasing a buffer the contains arbitrary tiles would be more complex + * Erasing a buffer that contains arbitrary tiles would be more complex * as we can't just empty the selection without regrouting */ let z = erase_buffer ? clear_unparsed_buffer(z) : z; let relatives = @@ -205,7 +151,6 @@ let directional_unselect = (d: Direction.t, z: t): t => { let move = (d: Direction.t, z: t): option(t) => if (Selection.is_empty(z.selection)) { - // let balanced = !Backpack.is_balanced(z.backpack); let+ (p, relatives) = Relatives.pop(d, z.relatives); let relatives = relatives @@ -226,9 +171,6 @@ let pick_up = (z: t): t => { |> Segment.trim_grout_around_secondary(Left) |> Segment.trim_grout_around_secondary(Right) |> Selection.mk; - Segment.tiles(selection.content) - |> List.map((t: Tile.t) => t.id) - |> Effect.s_touch; let backpack = Backpack.push(selection, z.backpack); {...z, backpack}; }; @@ -247,7 +189,6 @@ let destruct = (~destroy_kids=true, z: t): t => { let to_pick_up = destroy_kids ? List.map(Tile.disintegrate, to_pick_up) |> List.flatten : to_pick_up; - Effect.s_touch(List.map((t: Tile.t) => t.id, to_pick_up)); let backpack = backpack |> Backpack.remove_matching(to_remove) @@ -263,9 +204,6 @@ let delete = (d: Direction.t, z: t): option(t) => let put_down = (d: Direction.t, z: t): option(t) => { let z = destruct(z); let* (_, popped, backpack) = pop_backpack(z); - Segment.tiles(popped.content) - |> List.map((t: Tile.t) => t.id) - |> Effect.s_touch; let z = {...z, backpack} |> put_selection(popped) |> unselect; switch (d) { | Left => Some(z) @@ -284,7 +222,6 @@ let rec construct = /* Special case for comments, can't rely on the last branch to construct */ let content = Secondary.construct_comment(content); let id = Id.mk(); - Effect.s_touch([id]); let z = destruct(z); let selections = [Selection.mk(Base.mk_secondary(id, content))]; let backpack = Backpack.push_s(selections, z.backpack); @@ -293,7 +230,6 @@ let rec construct = | [content] when Form.is_secondary(content) => let content = Secondary.Whitespace(content); let id = Id.mk(); - Effect.s_touch([id]); z |> update_siblings(((l, r)) => (l @ [Secondary({id, content})], r)); | _ => let z = destruct(z); @@ -302,7 +238,6 @@ let rec construct = // initial mold to typecheck, will be remolded let mold = List.hd(molds); let id = Id.mk(); - Effect.s_touch([id]); let selections = Tile.split_shards(id, label, mold, List.mapi((i, _) => i, label)) |> List.map(Segment.of_tile) @@ -340,31 +275,35 @@ let caret_direction = (z: t): option(Direction.t) => | Inner(_) => None | Outer => switch (Siblings.neighbors(sibs_with_sel(z))) { - | (Some(l), Some(r)) when Piece.is_secondary(l) && Piece.is_secondary(r) => + | (Some(l), Some(r)) + when + Piece.is_secondary(l) + && Piece.is_secondary(r) + && Selection.is_empty(z.selection) => None | _ => Siblings.direction_between(sibs_with_sel(z)) } }; -let base_point = (measured: Measured.t, z: t): Measured.Point.t => { +let base_point = (measured: Measured.t, z: t): Point.t => { switch (representative_piece(z)) { | Some((p, d)) => let seg = Piece.disassemble(p); switch (d) { | Left => let p = ListUtil.last(seg); - let m = Measured.find_p(p, measured); + let m = Measured.find_p(~msg="base_point", p, measured); m.last; | Right => let p = List.hd(seg); - let m = Measured.find_p(p, measured); + let m = Measured.find_p(~msg="base_point", p, measured); m.origin; }; | None => {row: 0, col: 0} }; }; -let caret_point = (measured, z: t): Measured.Point.t => { - let Measured.Point.{row, col} = base_point(measured, z); +let caret_point = (measured, z: t): Point.t => { + let Point.{row, col} = base_point(measured, z); {row, col: col + Caret.offset(z.caret)}; }; diff --git a/src/haz3lcore/zipper/ZipperBase.re b/src/haz3lcore/zipper/ZipperBase.re new file mode 100644 index 0000000000..cb6311a4b8 --- /dev/null +++ b/src/haz3lcore/zipper/ZipperBase.re @@ -0,0 +1,162 @@ +open Util; + +module Caret = { + [@deriving (show({with_path: false}), sexp, yojson)] + type t = + | Outer + | Inner(int, int); + + let decrement: t => t = + fun + | Outer + | Inner(_, 0) => Outer + | Inner(d, c) => Inner(d, c - 1); + + let offset: t => int = + fun + | Outer => 0 + | Inner(_, c) => c + 1; +}; + +// assuming single backpack, shards may appear in selection, backpack, or siblings +[@deriving (show({with_path: false}), sexp, yojson)] +type t = { + selection: Selection.t, + backpack: Backpack.t, + relatives: Relatives.t, + caret: Caret.t, +}; + +let update_relatives = (f: Relatives.t => Relatives.t, z: t): t => { + ...z, + relatives: f(z.relatives), +}; + +let update_siblings: (Siblings.t => Siblings.t, t) => t = + f => update_relatives(rs => {...rs, siblings: f(rs.siblings)}); + +let put_siblings = (siblings, z: t): t => update_siblings(_ => siblings, z); + +let put_selection_content = (content: Segment.t, z): t => { + ...z, + selection: { + ...z.selection, + content, + }, +}; + +let parent = (z: t): option(Piece.t) => + Relatives.parent(~sel=z.selection.content, z.relatives); + +let sibs_with_sel = + ( + { + selection: {content, focus, _}, + relatives: {siblings: (l_sibs, r_sibs), _}, + _, + }: t, + ) + : Siblings.t => + switch (focus) { + | Left => (l_sibs, content @ r_sibs) + | Right => (l_sibs @ content, r_sibs) + }; + +module MapPiece = { + type updater = Piece.t => Piece.t; + + let rec of_segment = (f: updater, seg: Segment.t): Segment.t => { + seg |> List.map(p => f(p)) |> List.map(of_piece(f)); + } + and of_piece = (f: updater, piece: Piece.t): Piece.t => { + switch (piece) { + | Tile(t) => Tile(of_tile(f, t)) + | Grout(_) + | Projector(_) + | Secondary(_) => piece + }; + } + and of_tile = (f: updater, t: Tile.t): Tile.t => { + {...t, children: List.map(of_segment(f), t.children)}; + }; + + let of_siblings = (f: updater, sibs: Siblings.t): Siblings.t => ( + of_segment(f, fst(sibs)), + of_segment(f, snd(sibs)), + ); + + let of_ancestor = (f: updater, ancestor: Ancestor.t): Ancestor.t => { + { + ...ancestor, + children: ( + List.map(of_segment(f), fst(ancestor.children)), + List.map(of_segment(f), snd(ancestor.children)), + ), + }; + }; + + let of_generation = + (f: updater, generation: Ancestors.generation): Ancestors.generation => ( + of_ancestor(f, fst(generation)), + of_siblings(f, snd(generation)), + ); + + let of_ancestors = (f: updater, ancestors: Ancestors.t): Ancestors.t => + List.map(of_generation(f), ancestors); + + let of_selection = (f: updater, selection: Selection.t): Selection.t => { + {...selection, content: of_segment(f, selection.content)}; + }; + + /* Maps the updater over all pieces in the zipper + * (that are not currently unzipped) */ + let go = (f: updater, z: t): t => { + ...z, + selection: of_selection(f, z.selection), + relatives: { + ancestors: of_ancestors(f, z.relatives.ancestors), + siblings: of_siblings(f, z.relatives.siblings), + }, + }; + + let sib_has_id = (get, z: t, id: Id.t): bool => { + switch (z.relatives.siblings |> get) { + | Some(l) => Piece.id(l) == id + | _ => false + }; + }; + + let left_sib_has_id = sib_has_id(Siblings.left_neighbor); + + let right_sib_has_id = sib_has_id(Siblings.right_neighbor); + + let update_left_sib = (f: Piece.t => Piece.t, z: t) => { + let (l, r) = z.relatives.siblings; + let sibs = (List.map(f, l), List.map(f, r)); + put_siblings(sibs, z); + }; + + let update_right_sib = (f: Piece.t => Piece.t, z: t) => { + let sibs = + switch (z.relatives.siblings) { + | (l, [hd, ...tl]) => (l, [f(hd), ...tl]) + | sibs => sibs + }; + put_siblings(sibs, z); + }; + + let fast_local = (f: Piece.t => Piece.t, id: Id.t, z: t): t => + /* This applies the function to the piece in the zipper having id id, and + * then replaces the id of the resulting piece with the idea of the old + * piece, ensuring that the root id remains stable. This function assumes + * the cursor is not inside the piece to be updated. This is optimized to + * be O(1) when the piece is directly to the left or right of the cursor, + * otherwise it is O(|zipper|) */ + if (left_sib_has_id(z, id)) { + update_left_sib(f, z); + } else if (right_sib_has_id(z, id)) { + update_right_sib(f, z); + } else { + go(f, z); + }; +}; diff --git a/src/haz3lcore/zipper/action/Action.re b/src/haz3lcore/zipper/action/Action.re index 272570169a..85b24be4f1 100644 --- a/src/haz3lcore/zipper/action/Action.re +++ b/src/haz3lcore/zipper/action/Action.re @@ -1,5 +1,5 @@ open Util; -open Sexplib.Std; + open Zipper; [@deriving (show({with_path: false}), sexp, yojson)] @@ -16,7 +16,7 @@ let of_piece_goal = [@deriving (show({with_path: false}), sexp, yojson)] type goal = - | Point(Measured.Point.t) + | Point(Point.t) | Piece(piece_goal, Direction.t); [@deriving (show({with_path: false}), sexp, yojson)] @@ -39,14 +39,43 @@ type rel = type select = | All | Resize(move) - | Smart + | Smart(int) | Tile(rel) | Term(rel); +/* This type defines the top-level actions used to manage + * projectors,as distinguished from external_action, + * which defines the actions available internally to all projectors, + * and from each projector's own internal action type */ +[@deriving (show({with_path: false}), sexp, yojson)] +type project = + | SetIndicated(Base.kind) /* Project syntax at caret */ + | ToggleIndicated(Base.kind) /* Un/Project syntax at caret */ + | Remove(Id.t) /* Remove projector at Id */ + | SetSyntax(Id.t, Piece.t) /* Set underlying syntax */ + | SetModel(Id.t, string) /* Set serialized projector model */ + | Focus(Id.t, option(Util.Direction.t)) /* Pass control to projector */ + | Escape(Id.t, Direction.t); /* Pass control to parent editor */ + +[@deriving (show({with_path: false}), sexp, yojson)] +type agent = + | TyDi; + +[@deriving (show({with_path: false}), sexp, yojson)] +type buffer = + | Set(agent) + | Clear + | Accept; + [@deriving (show({with_path: false}), sexp, yojson)] type t = + | Reparse + | Buffer(buffer) + | Paste(string) + | Copy + | Cut + | Project(project) | Move(move) - | MoveToNextHole(Direction.t) | Jump(jump_target) | Select(select) | Unselect(option(Direction.t)) @@ -64,7 +93,11 @@ module Failure = { | Cant_insert | Cant_destruct | Cant_select - | Cant_put_down; + | Cant_put_down + | Cant_project + | CantPaste + | CantReparse + | CantAccept; }; module Result = { @@ -74,8 +107,88 @@ module Result = { let is_edit: t => bool = fun + | Paste(_) + | Cut + | Reparse + | Insert(_) + | Destruct(_) + | Pick_up + | Put_down + | Buffer(Accept | Clear | Set(_)) => true + | Copy + | Move(_) + | Jump(_) + | Select(_) + | Unselect(_) + | RotateBackpack + | MoveToBackpackTarget(_) => false + | Project(p) => + switch (p) { + | SetSyntax(_) + | SetModel(_) + | SetIndicated(_) + | ToggleIndicated(_) + | Remove(_) => true + | Focus(_) + | Escape(_) => false + }; + +/* Determines whether undo/redo skips action */ +let is_historic: t => bool = + fun + | Buffer(Set(_) | Clear) + | Copy + | Move(_) + | Jump(_) + | Select(_) + | Unselect(_) + | RotateBackpack + | MoveToBackpackTarget(_) => false + | Cut + | Buffer(Accept) + | Paste(_) + | Reparse | Insert(_) | Destruct(_) | Pick_up | Put_down => true - | _ => false; + | Project(p) => + switch (p) { + | SetSyntax(_) + | SetModel(_) + | SetIndicated(_) + | ToggleIndicated(_) + | Remove(_) => true + | Focus(_) + | Escape(_) => false + }; + +let prevent_in_read_only_editor = (a: t) => { + switch (a) { + | Copy + | Move(_) + | Unselect(_) + | Jump(_) + | Select(_) => false + | Buffer(Set(_) | Accept | Clear) + | Cut + | Paste(_) + | Reparse + | Destruct(_) + | Insert(_) + | Pick_up + | Put_down + | RotateBackpack + | MoveToBackpackTarget(_) => true + | Project(p) => + switch (p) { + | SetSyntax(_) => true + | SetModel(_) + | SetIndicated(_) + | ToggleIndicated(_) + | Remove(_) + | Focus(_) + | Escape(_) => false + } + }; +}; diff --git a/src/haz3lcore/zipper/action/Effect.re b/src/haz3lcore/zipper/action/Effect.re deleted file mode 100644 index 8567cb44d1..0000000000 --- a/src/haz3lcore/zipper/action/Effect.re +++ /dev/null @@ -1,12 +0,0 @@ -[@deriving (show({with_path: false}), sexp, yojson)] -type t = - | Touch(Id.t) - | Delete(Id.t); - -// used to record effects over the course of a single action -let s: ref(list(t)) = ref([]); -let s_clear = () => s := []; -let s_touch = (ids: list(Id.t)) => - s := List.map(id => Touch(id), ids) @ s^; - -let s_touched = (id: Id.t): bool => List.mem(Touch(id), s^); diff --git a/src/haz3lcore/zipper/action/Indicated.re b/src/haz3lcore/zipper/action/Indicated.re index 3df1f3cb5c..6cfbc5f997 100644 --- a/src/haz3lcore/zipper/action/Indicated.re +++ b/src/haz3lcore/zipper/action/Indicated.re @@ -1,5 +1,4 @@ open Util; -open Zipper; open OptUtil.Syntax; type relation = @@ -7,20 +6,18 @@ type relation = | Sibling; let piece' = - (~no_ws: bool, ~ign: Piece.t => bool, ~trim_secondary=false, z: Zipper.t) + (~no_ws: bool, ~ign: Piece.t => bool, z: ZipperBase.t) : option((Piece.t, Direction.t, relation)) => { - let sibs = - trim_secondary - ? sibs_with_sel(z) |> Siblings.trim_secondary : sibs_with_sel(z); /* Returns the piece currently indicated (if any) and which side of that piece the caret is on. We favor indicating the piece to the (R)ight, but may end up indicating the (P)arent or the (L)eft. We don't indicate secondary tiles. This function ignores whether or not there is a selection so this can be used to get the caret direction, but the caller shouldn't indicate if there's a selection */ - switch (Siblings.neighbors(sibs), parent(z)) { - /* Non-empty selection => no indication */ - //| _ when z.selection.content != [] => None + switch ( + Siblings.neighbors(ZipperBase.sibs_with_sel(z)), + ZipperBase.parent(z), + ) { /* Empty syntax => no indication */ | ((None, None), None) => None /* L not secondary, R is secondary => indicate L */ @@ -57,7 +54,7 @@ let piece' = let piece = piece'(~no_ws=true, ~ign=p => Piece.(is_secondary(p) || is_grout(p))); -let shard_index = (z: Zipper.t): option(int) => +let shard_index = (z: ZipperBase.t): option(int) => switch (piece(z)) { | None => None | Some((p, side, relation)) => @@ -75,7 +72,8 @@ let shard_index = (z: Zipper.t): option(int) => | Sibling => switch (p) { | Secondary(_) - | Grout(_) => Some(0) + | Grout(_) + | Projector(_) => Some(0) | Tile(t) => switch (side) { | Left => Some(List.length(t.children)) @@ -85,27 +83,28 @@ let shard_index = (z: Zipper.t): option(int) => } }; -let index = (z: Zipper.t): option(Id.t) => - switch ( - piece'(~no_ws=false, ~ign=Piece.is_secondary, ~trim_secondary=false, z) - ) { +let for_index = piece'(~no_ws=false, ~ign=Piece.is_secondary); + +let index = (z: ZipperBase.t): option(Id.t) => + switch (for_index(z)) { | None => None | Some((p, _, _)) => Some(Piece.id(p)) }; -let ci_of = (z: Zipper.t, info_map: Statics.Map.t): option(Statics.Info.t) => +let piece'' = piece'(~no_ws=true, ~ign=Piece.is_secondary); + +let ci_of = + (z: ZipperBase.t, info_map: Statics.Map.t): option(Statics.Info.t) => /* This version takes into accounts Secondary, while accounting for the - * fact that Secondary is not currently added to the infomap. First we + * fact that Secondary is not currently added to the info_map. First we * try the basic indication function, specifying that we do not want * Secondary. But if this doesn't succeed, then we create a 'virtual' * info map entry representing the Secondary notation, which takes on * some of the semantic context of a nearby 'proxy' term */ - switch ( - piece'(~no_ws=true, ~ign=Piece.is_secondary, ~trim_secondary=false, z) - ) { + switch (piece''(z)) { | Some((p, _, _)) => Id.Map.find_opt(Piece.id(p), info_map) | None => - let sibs = sibs_with_sel(z); + let sibs = ZipperBase.sibs_with_sel(z); let* cls = switch (Siblings.neighbors(sibs)) { /* If on side of comment, say we're on comment */ diff --git a/src/haz3lcore/zipper/action/Move.re b/src/haz3lcore/zipper/action/Move.re index 1f19f0441e..afc46ca152 100644 --- a/src/haz3lcore/zipper/action/Move.re +++ b/src/haz3lcore/zipper/action/Move.re @@ -1,7 +1,6 @@ open Zipper; open Util; open OptUtil.Syntax; -open Sexplib.Std; [@deriving (show({with_path: false}), sexp, yojson)] type movability = @@ -44,8 +43,8 @@ let neighbor_movability = Unicode.length(content_string) - 1, Unicode.length(content_string) - 2, ); - | Some(_) => CanPass - | _ => supernhbr_l + | Some(Secondary(_) | Grout(_) | Projector(_)) => CanPass + | None => supernhbr_l }; let r = switch (r_nhbr) { @@ -54,8 +53,8 @@ let neighbor_movability = // Comments are always length >= 2 let content_string = Secondary.get_string(w.content); CanEnter(0, Unicode.length(content_string) - 2); - | Some(_) => CanPass - | _ => supernhbr_r + | Some(Secondary(_) | Grout(_) | Projector(_)) => CanPass + | None => supernhbr_r }; (l, r); }; @@ -94,66 +93,90 @@ module Make = (M: Editor.Meta.S) => { }; let is_at_side_of_row = (d: Direction.t, z: Zipper.t) => { - let Measured.Point.{row, col} = caret_point(z); + let Point.{row, col} = caret_point(z); switch (Zipper.move(d, z)) { | None => true | Some(z) => - let Measured.Point.{row: rowp, col: colp} = caret_point(z); + let Point.{row: rowp, col: colp} = caret_point(z); row != rowp || col == colp; }; }; + let direction_to_from = (p1: Point.t, p2: Point.t): Direction.t => { + let before_row = p1.row < p2.row; + let at_row = p1.row == p2.row; + let before_col = p1.col < p2.col; + before_row || at_row && before_col ? Left : Right; + }; + + let closer_to_prev = (curr, prev, goal: Point.t) => + /* Default to true if equal */ + abs(caret_point(prev).col - goal.col) + < abs(caret_point(curr).col - goal.col); + let do_towards = ( ~anchor: option(Measured.Point.t)=?, + ~force_progress: bool=false, f: (Direction.t, t) => option(t), goal: Measured.Point.t, z: t, ) : option(t) => { let init = caret_point(z); - let d = - goal.row < init.row || goal.row == init.row && goal.col < init.col - ? Direction.Left : Right; + let d_to_goal = direction_to_from(goal, init); let rec go = (prev: t, curr: t) => { let curr_p = caret_point(curr); - switch ( - Measured.Point.dcomp(d, curr_p.col, goal.col), - Measured.Point.dcomp(d, curr_p.row, goal.row), - ) { - | (Exact, Exact) => curr - | (_, Over) => prev - | (_, Under) - | (Under, Exact) => - switch (f(d, curr)) { - | None => curr + let x_progress = Point.dcomp(d_to_goal, curr_p.col, goal.col); + let y_progress = Point.dcomp(d_to_goal, curr_p.row, goal.row); + switch (y_progress, x_progress) { + /* If we're not there yet, keep going */ + | (Under, Over | Exact | Under) + | (Exact, Under) => + switch (f(d_to_goal, curr)) { | Some(next) => go(curr, next) + | None => curr /* Should only occur at start/end of program */ + } + /* If we're there, stop */ + | (Exact, Exact) => curr + /* If we've overshot, meaning the exact goal is inaccessible, + * we choose between current and previous (undershot) positions */ + | (Over, Over | Exact | Under) => + switch (force_progress) { + | false => + /* Ideally we would use the same logic as from the below + * anchor case here; however that results in strange + * behavior when accidentally starting a drag at the end + * of a line, which triggers the (invisible) selection of + * a linebreak, making it appear that the caret has jumped + * to the next line. The downside of leaving this as-is is + * that multiline tokens (projectors) do not become part of + * the selection when dragging until you're all the way + * over them, which is slightly visually jarring */ + prev + | true => + /* Up/down kb movement works by setting a goal one row + * below the current. When adjacent to a multiline token, + * the nearest next caret position may be multiple lines down. + * We must allow this overshoot in order to make progress. */ + caret_point(prev) == init ? curr : prev } - | (Over, Exact) => + | (Exact, Over) => switch (anchor) { | None => - /* Special case for when you're (eg) you're trying - to move down, but you're at the right end of a row - and the first position of the next row is further - right than the current row's end. In this case we - want to progress regardless of whether the new - position would be closer or futher from the - goal col */ - is_at_side_of_row(Direction.toggle(d), curr) - ? curr - : { - let d_curr = abs(curr_p.col - goal.col); - let d_prev = abs(caret_point(prev).col - goal.col); - // default to going over when equal - d_prev < d_curr ? prev : curr; - } + /* If you're trying to (eg) move down at the end of a row + * but the first position of the next row is further right + * than the currentrow's end, we want to make progress + * regardless of whether the new position would be closer + * or further from the goal. Otherwise, we try to just + * get as close as we can */ + is_at_side_of_row(Direction.toggle(d_to_goal), curr) + ? curr : closer_to_prev(curr, prev, goal) ? prev : curr | Some(anchor) => - let anchor_d = - goal.row < anchor.row - || goal.row == anchor.row - && goal.col < anchor.col - ? Direction.Left : Right; - anchor_d == d ? curr : prev; + /* If we're dragging to make a selection, decide whether or + * not to force progress based on the relative position of the + * anchor (the position where the drag was started) */ + direction_to_from(goal, anchor) == d_to_goal ? curr : prev } }; }; @@ -168,17 +191,14 @@ module Make = (M: Editor.Meta.S) => { caret position to a target derived from the initial position */ let cur_p = caret_point(z); let goal = - Measured.Point.{ - col: M.col_target, - row: cur_p.row + (d == Right ? 1 : (-1)), - }; - do_towards(f, goal, z); + Point.{col: M.col_target, row: cur_p.row + (d == Right ? 1 : (-1))}; + do_towards(~force_progress=true, f, goal, z); }; let do_extreme = (f: (Direction.t, t) => option(t), d: planar, z: t): option(t) => { let cur_p = caret_point(z); - let goal: Measured.Point.t = + let goal: Point.t = switch (d) { | Right(_) => {col: Int.max_int, row: cur_p.row} | Left(_) => {col: 0, row: cur_p.row} @@ -227,6 +247,14 @@ module Make = (M: Editor.Meta.S) => { | Some(z) => Some(z) }; + /* Jump to id moves the caret to the leftmost edge of + * the piece with the target id. Note that this may not + * mean that the piece at that id will be considered + * indicate from the point of view of the code decorations + * and cursor info display, since for example in the + * expression with (caret "|") "true && !|flag", the + * caret is at the leftmost edge of flag, but the not + * operator ("!") is indicated */ let jump_to_id = (z: t, id: Id.t): option(t) => { let* {origin, _} = Measured.find_by_id(id, M.measured); let z = @@ -240,6 +268,47 @@ module Make = (M: Editor.Meta.S) => { }; }; + let jump_to_side_of_id = (d: Direction.t, z, id) => { + let z = + switch (jump_to_id(z, id)) { + | Some(z) => z /* Move to left of id */ + | None => z + }; + switch (d) { + | Left => z + | Right => + switch (primary(ByToken, Right, z)) { + | Some(z) => z + | None => z + } + }; + }; + + /* Same as jump to id, but if the end position doesn't + * indicate the target id, move one token to the right. + * This is an approximate solution (that I believe works + * for all current cases) */ + let jump_to_id_indicated = (z: t, id: Id.t): option(t) => { + let* {origin, _} = Measured.find_by_id(id, M.measured); + let z = + switch (to_start(z)) { + | None => z + | Some(z) => z + }; + switch (do_towards(primary(ByChar), origin, z)) { + | None => Some(z) + | Some(z) => + switch (Indicated.index(z)) { + | Some(indicated_id) when id == indicated_id => Some(z) + | _ => + switch (primary(ByToken, Right, z)) { + | Some(z) => Some(z) + | None => Some(z) + } + } + }; + }; + let vertical = (d: Direction.t, z: t): option(t) => z.selection.content == [] ? do_vertical(primary(ByChar), d, z) @@ -316,12 +385,14 @@ module Make = (M: Editor.Meta.S) => { }; }; - let go = (d: Action.move, z: Zipper.t): option(Zipper.t) => + let move_dispatch = (d: Action.move, z: Zipper.t): option(Zipper.t) => switch (d) { | Goal(Piece(p, d)) => do_until_wrap(Action.of_piece_goal(p), d, z) | Goal(Point(goal)) => - let z = Zipper.unselect(z); - do_towards(primary(ByChar), goal, z); + switch (do_towards(primary(ByChar), goal, z)) { + | None => Some(z) + | Some(z) => Some(z) + } | Extreme(d) => do_extreme(primary(ByToken), d, z) | Local(d) => z @@ -334,4 +405,27 @@ module Make = (M: Editor.Meta.S) => { } ) }; + + let go = (d: Action.move, z: Zipper.t): option(Zipper.t) => + if (Selection.is_empty(z.selection)) { + move_dispatch(d, z); + } else { + /* Always empty selection on move action, + * even if we don't actually move */ + let z = Zipper.unselect(z); + switch (move_dispatch(d, z)) { + | Some(z) => Some(z) + | None => Some(z) + }; + }; + + let left_until_case_or_rule = + do_until(go(Local(Left(ByToken))), Piece.is_case_or_rule); + + let left_until_not_comment_or_space = (~move_first) => + do_until( + ~move_first, + go(Local(Left(ByToken))), + Piece.not_comment_or_space, + ); }; diff --git a/src/haz3lcore/zipper/action/Perform.re b/src/haz3lcore/zipper/action/Perform.re index 58bc516123..5a3b90c245 100644 --- a/src/haz3lcore/zipper/action/Perform.re +++ b/src/haz3lcore/zipper/action/Perform.re @@ -1,21 +1,17 @@ open Util; open Zipper; -let is_write_action = (a: Action.t) => { - switch (a) { - | Move(_) - | MoveToNextHole(_) - | Unselect(_) - | Jump(_) - | Select(_) => false - | Destruct(_) - | Insert(_) - | Pick_up - | Put_down - | RotateBackpack - | MoveToBackpackTarget(_) => true +let buffer_clear = (z: t): t => + switch (z.selection.mode) { + | Buffer(_) => {...z, selection: Selection.mk([])} + | _ => z + }; + +let set_buffer = (info_map: Statics.Map.t, z: t): t => + switch (TyDi.set_buffer(~info_map, z)) { + | None => z + | Some(z) => z }; -}; let go_z = ( @@ -28,49 +24,114 @@ let go_z = let meta = switch (meta) { | Some(m) => m - | None => Editor.Meta.init(z) + | None => Editor.Meta.init(z, ~settings) }; module M = (val Editor.Meta.module_of_t(meta)); module Move = Move.Make(M); module Select = Select.Make(M); - let select_term_current = z => - switch (Indicated.index(z)) { - | None => Error(Action.Failure.Cant_select) - | Some(id) => - switch (Select.term(id, z)) { - | Some(z) => Ok(z) - | None => Error(Action.Failure.Cant_select) + let paste = (z: Zipper.t, str: string): option(Zipper.t) => { + open Util.OptUtil.Syntax; + let* z = Printer.zipper_of_string(~zipper_init=z, str); + /* HACK(andrew): Insert/Destruct below is a hack to deal + with the fact that pasting something like "let a = b in" + won't trigger the barfing of the "in"; to trigger this, + we insert a space, and then we immediately delete it */ + let* z = Insert.go(" ", z); + let+ z = Destruct.go(Left, z); + remold_regrout(Left, z); + }; + + let buffer_accept = (z): option(Zipper.t) => + switch (z.selection.mode) { + | Normal => None + | Buffer(Unparsed) => + switch (TyDi.get_buffer(z)) { + | None => None + | Some(completion) + when StringUtil.match(StringUtil.regexp(".*\\)::$"), completion) => + /* Slightly hacky. There's currently only one genre of completion + * that creates more than one hole on intial expansion: when on eg + * 1 :: a|, we suggest "abs( )::" via lookahead. In such a case we + * want the caret to end up to the left of the first hole, whereas + * pasting would leave it to the left of the second. Thus we move + * left to the previous hole. */ + let z = { + open OptUtil.Syntax; + let* z = paste(z, completion); + let* z = Move.go(Goal(Piece(Grout, Left)), z); + Move.go(Local(Left(ByToken)), z); + }; + z; + | Some(completion) => paste(z, completion) } }; + let smart_select = (n, z): option(Zipper.t) => { + switch (n) { + | 2 => Select.indicated_token(z) + | 3 => + open OptUtil.Syntax; + /* For things where triple-clicking would otherwise have + * no additional effect, select the parent term instead */ + let* (p, _, _) = Indicated.piece''(z); + Piece.is_term(p) + ? Select.parent_of_indicated(z, meta.statics.info_map) + : Select.nice_term(z); + | _ => None + }; + }; + switch (a) { + | Paste(clipboard) => + switch (paste(z, clipboard)) { + | None => Error(CantPaste) + | Some(z) => Ok(z) + } + | Cut => + /* System clipboard handling is done in Page.view handlers */ + switch (Destruct.go(Left, z)) { + | None => Error(Cant_destruct) + | Some(z) => Ok(z) + } + | Copy => + /* System clipboard handling itself is done in Page.view handlers. + * This doesn't change state but is included here for logging purposes */ + Ok(z) + | Reparse => + switch (Printer.reparse(z)) { + | None => Error(CantReparse) + | Some(z) => Ok(z) + } + | Buffer(Set(TyDi)) => Ok(set_buffer(meta.statics.info_map, z)) + | Buffer(Accept) => + switch (buffer_accept(z)) { + | None => Error(CantAccept) + | Some(z) => Ok(z) + } + | Buffer(Clear) => Ok(buffer_clear(z)) + | Project(a) => + ProjectorPerform.go( + Move.jump_to_id_indicated, + Move.jump_to_side_of_id, + a, + z, + ) | Move(d) => Move.go(d, z) |> Result.of_option(~error=Action.Failure.Cant_move) - | MoveToNextHole(d) => - Move.go(Goal(Piece(Grout, d)), z) - |> Result.of_option(~error=Action.Failure.Cant_move) | Jump(jump_target) => - open OptUtil.Syntax; - - let idx = Indicated.index(z); - let (term, _) = - Util.TimeUtil.measure_time("Perform.go_z => MakeTerm.from_zip", true, () => - MakeTerm.from_zip_for_view(z) - ); - let statics = Interface.Statics.mk_map(settings, term); - ( switch (jump_target) { | BindingSiteOfIndicatedVar => - let* idx = idx; - let* ci = Id.Map.find_opt(idx, statics); + open OptUtil.Syntax; + let* idx = Indicated.index(z); + let* ci = Id.Map.find_opt(idx, meta.statics.info_map); let* binding_id = Info.get_binding_site(ci); Move.jump_to_id(z, binding_id); | TileId(id) => Move.jump_to_id(z, id) } ) - |> Result.of_option(~error=Action.Failure.Cant_move); + |> Result.of_option(~error=Action.Failure.Cant_move) | Unselect(Some(d)) => Ok(Zipper.directional_unselect(d, z)) | Unselect(None) => let z = Zipper.directional_unselect(z.selection.focus, z); @@ -84,42 +145,16 @@ let go_z = } | None => Error(Action.Failure.Cant_select) } - | Select(Term(Current)) => select_term_current(z) - | Select(Smart) => - /* If the current tile is not coincident with the term, - select the term. Otherwise, select the parent term. */ - let tile_is_term = - switch (Indicated.index(z)) { - | None => false - | Some(id) => Select.tile(id, z) == Select.term(id, z) - }; - if (!tile_is_term) { - select_term_current(z); - } else { - //PERF: this is expensive - let (term, _) = MakeTerm.from_zip_for_view(z); - let statics = Interface.Statics.mk_map(settings, term); - let target = - switch ( - Indicated.index(z) - |> OptUtil.and_then(idx => Id.Map.find_opt(idx, statics)) - ) { - | Some(ci) => - switch (Info.ancestors_of(ci)) { - | [] => None - | [parent, ..._] => Some(parent) - } - | None => None - }; - switch (target) { - | None => Error(Action.Failure.Cant_select) - | Some(id) => - switch (Select.term(id, z)) { - | Some(z) => Ok(z) - | None => Error(Action.Failure.Cant_select) - } - }; - }; + | Select(Term(Current)) => + switch (Select.current_term(z)) { + | None => Error(Cant_select) + | Some(z) => Ok(z) + } + | Select(Smart(n)) => + switch (smart_select(n, z)) { + | None => Error(Cant_select) + | Some(z) => Ok(z) + } | Select(Term(Id(id, d))) => switch (Select.term(id, z)) { | Some(z) => @@ -128,13 +163,9 @@ let go_z = | None => Error(Action.Failure.Cant_select) } | Select(Tile(Current)) => - switch (Indicated.index(z)) { - | None => Error(Action.Failure.Cant_select) - | Some(id) => - switch (Select.tile(id, z)) { - | Some(z) => Ok(z) - | None => Error(Action.Failure.Cant_select) - } + switch (Select.current_tile(z)) { + | None => Error(Cant_select) + | Some(z) => Ok(z) } | Select(Tile(Id(id, d))) => switch (Select.tile(id, z)) { @@ -184,15 +215,45 @@ let go_z = }; }; +let go_history = + (~settings: CoreSettings.t, a: Action.t, ed: Editor.t) + : Action.Result.t(Editor.t) => { + open Result.Syntax; + /* This function records action history */ + let Editor.State.{zipper, meta} = ed.state; + let+ z = go_z(~settings, ~meta, a, zipper); + Editor.new_state(~settings, a, z, ed); +}; + let go = (~settings: CoreSettings.t, a: Action.t, ed: Editor.t) : Action.Result.t(Editor.t) => - if (ed.read_only && is_write_action(a)) { - Result.Ok(ed); - } else { + /* This function wraps assistant completions. If completions are enabled, + * then beginning any action (other than accepting a completion) clears + * the completion buffer before performing the action. Conversely, + * after any edit action, a new completion is set in the buffer */ + if (ed.read_only && Action.prevent_in_read_only_editor(a)) { + Ok(ed); + } else if (settings.assist && settings.statics) { open Result.Syntax; - let Editor.State.{zipper, meta} = ed.state; - Effect.s_clear(); - let+ z = go_z(~settings, ~meta, a, zipper); - Editor.new_state(~effects=Effect.s^, a, z, ed); + let ed = + a == Buffer(Accept) + ? ed + : ( + switch (go_history(~settings, Buffer(Clear), ed)) { + | Ok(ed) => ed + | Error(_) => ed + } + ); + let* ed = go_history(~settings, a, ed); + Action.is_edit(a) + ? { + switch (go_history(~settings, Buffer(Set(TyDi)), ed)) { + | Error(err) => Error(err) + | Ok(ed) => Ok(ed) + }; + } + : Ok(ed); + } else { + go_history(~settings, a, ed); }; diff --git a/src/haz3lcore/zipper/action/ProjectorPerform.re b/src/haz3lcore/zipper/action/ProjectorPerform.re new file mode 100644 index 0000000000..a0996437bd --- /dev/null +++ b/src/haz3lcore/zipper/action/ProjectorPerform.re @@ -0,0 +1,129 @@ +open Projector; +open ProjectorBase; + +/* Updates the underlying piece of syntax for a projector */ +module Update = { + let update_piece = + (f: Base.projector => Base.projector, id: Id.t, syntax: syntax) => + switch (syntax) { + | Projector(pr) when pr.id == id => Base.Projector(f(pr)) + | x => x + }; + + let init = (kind: t, syntax: syntax): syntax => { + /* We set the projector id equal to the Piece id for convienence + * including cursor-info association. We maintain this invariant + * when we update a projector's contained syntax */ + let (module P) = to_module(kind); + switch (P.can_project(syntax) && minimum_projection_condition(syntax)) { + | false => syntax + | true => Projector({id: Piece.id(syntax), kind, model: P.init, syntax}) + }; + }; + + let add_projector = (kind: Base.kind, id: Id.t, syntax: syntax) => + switch (syntax) { + | Projector(pr) when Piece.id(syntax) == id => init(kind, pr.syntax) + | syntax when Piece.id(syntax) == id => init(kind, syntax) + | x => x + }; + + let remove_projector = (id: Id.t, syntax: syntax) => + switch (syntax) { + | Projector(pr) when pr.id == id => pr.syntax + | x => x + }; + + let add_or_remove_projector = (kind: Base.kind, id: Id.t, syntax: syntax) => + switch (syntax) { + | Projector(pr) when Piece.id(syntax) == id => pr.syntax + | syntax when Piece.id(syntax) == id => init(kind, syntax) + | x => x + }; + + let remove_any_projector = (syntax: syntax) => + switch (syntax) { + | Projector(pr) => pr.syntax + | x => x + }; + + let update = + (f: Base.projector => Base.projector, id: Id.t, z: ZipperBase.t) + : ZipperBase.t => + ZipperBase.MapPiece.fast_local(update_piece(f, id), id, z); + + let add = (k: Base.kind, id: Id.t, z: ZipperBase.t): ZipperBase.t => + ZipperBase.MapPiece.fast_local(add_projector(k, id), id, z); + + let add_or_remove = (k: Base.kind, id: Id.t, z: ZipperBase.t): ZipperBase.t => + ZipperBase.MapPiece.fast_local(add_or_remove_projector(k, id), id, z); + + let remove = (id: Id.t, z: ZipperBase.t): ZipperBase.t => + ZipperBase.MapPiece.fast_local(remove_projector(id), id, z); + + let remove_all = (z: ZipperBase.t): ZipperBase.t => + ZipperBase.MapPiece.go(remove_any_projector, z); +}; + +/* If the caret is inside the indicated piece, move it out + * NOTE: Might need to be updated to support pieces with more than 2 delims */ +let move_out_of_piece = + (d: Util.Direction.t, rel: Indicated.relation, z: Zipper.t): Zipper.t => + switch (rel) { + | Sibling => {...z, caret: Outer} + | Parent => + switch (Zipper.move(d, {...z, caret: Outer})) { + | Some(z) => z + | None => z + } + }; + +let go = + (jump_to_id_indicated, jump_to_side_of_id, a: Action.project, z: Zipper.t) + : result(ZipperBase.t, Action.Failure.t) => { + switch (a) { + | SetIndicated(p) => + switch (Indicated.for_index(z)) { + | None => Error(Cant_project) + | Some((piece, d, rel)) => + Ok(move_out_of_piece(d, rel, z) |> Update.add(p, Piece.id(piece))) + } + | ToggleIndicated(p) => + switch (Indicated.for_index(z)) { + | None => Error(Cant_project) + | Some((piece, d, rel)) => + Ok( + move_out_of_piece(d, rel, z) + |> Update.add_or_remove(p, Piece.id(piece)), + ) + } + | Remove(id) => Ok(Update.remove(id, z)) + | SetSyntax(id, syntax) => + /* Note we update piece id to keep in sync with projector id; + * See intial id setting in Update.init */ + Ok( + Update.update( + p => {...p, syntax: Piece.replace_id(id, syntax)}, + id, + z, + ), + ) + | SetModel(id, model) => Ok(Update.update(pr => {...pr, model}, id, z)) + | Focus(id, d) => + let z = + switch (d) { + | None => + /* d == None means focus by mouse click */ + jump_to_id_indicated(z, id) |> Option.value(~default=z) + | Some(_) => z + }; + switch (Projector.indicated(z)) { + | Some((_, p)) => + let (module P) = to_module(p.kind); + P.focus((id, d)); + Ok(z); + | None => Error(Cant_project) + }; + | Escape(id, d) => Ok(jump_to_side_of_id(d, z, id)) + }; +}; diff --git a/src/haz3lcore/zipper/action/Select.re b/src/haz3lcore/zipper/action/Select.re index 143ce6a29b..dca2607863 100644 --- a/src/haz3lcore/zipper/action/Select.re +++ b/src/haz3lcore/zipper/action/Select.re @@ -19,10 +19,27 @@ module Make = (M: Editor.Meta.S) => { let vertical = (d: Direction.t, ed: Zipper.t): option(Zipper.t) => Move.do_vertical(primary, d, ed); + let go = (d: Action.move, z: Zipper.t) => + switch (d) { + | Goal(Piece(_)) => failwith("Select.go not implemented for Piece Goal") + | Goal(Point(goal)) => + let anchor = z |> Zipper.toggle_focus |> Zipper.caret_point(M.measured); + Move.do_towards(~anchor, primary, goal, z); + | Extreme(d) => Move.do_extreme(primary, d, z) + | Local(d) => + /* Note: Don't update target on vertical selection */ + switch (d) { + | Left(_) => primary(Left, z) + | Right(_) => primary(Right, z) + | Up => vertical(Left, z) + | Down => vertical(Right, z) + } + }; + let range = (l: Id.t, r: Id.t, z: Zipper.t): option(Zipper.t) => { let* z = Move.jump_to_id(z, l); let* Measured.{last, _} = Measured.find_by_id(r, M.measured); - Move.do_towards(primary, last, z); + Move.do_towards(Zipper.select, last, z); }; let term = (id: Id.t, z: Zipper.t): option(Zipper.t) => { @@ -37,20 +54,146 @@ module Make = (M: Editor.Meta.S) => { Move.do_towards(primary, last, z); }; - let go = (d: Action.move, z: Zipper.t) => - switch (d) { - | Goal(Piece(_)) => failwith("Select.go not implemented for Piece Goal") - | Goal(Point(goal)) => - let anchor = z |> Zipper.toggle_focus |> Zipper.caret_point(M.measured); - Move.do_towards(~anchor, primary, goal, z); - | Extreme(d) => Move.do_extreme(primary, d, z) - | Local(d) => - /* Note: Don't update target on vertical selection */ - switch (d) { - | Left(_) => primary(Left, z) - | Right(_) => primary(Right, z) - | Up => vertical(Left, z) - | Down => vertical(Right, z) + let current_term = z => { + let* id = Indicated.index(z); + term(id, z); + }; + + let current_tile = z => { + let* id = Indicated.index(z); + tile(id, z); + }; + + let grow_right_until_case_or_rule = + Move.do_until(go(Local(Right(ByToken))), Piece.is_case_or_rule); + + let shrink_left_until_not_case_or_rule_or_space = + Move.do_until( + go(Local(Left(ByToken))), + Piece.is_not_case_or_rule_or_space, + ); + + let containing_rule = z => { + let* z = current_tile(z); + let* z = grow_right_until_case_or_rule(z); + shrink_left_until_not_case_or_rule_or_space(z); + }; + + let nice_term = (z: Zipper.t) => + switch (Indicated.piece''(z)) { + | Some((p, _, _)) => + switch (p) { + | Secondary(_) => failwith("Select.nice_term unimplemented") + | Grout(_) + | Projector(_) + | Tile({ + label: [_], + mold: {nibs: ({shape: Convex, _}, {shape: Convex, _}), _}, + _, + }) => + current_term(z) + | Tile({label: ["let" | "type", ..._], _}) => current_tile(z) + | Tile({label: ["|", "=>"], _}) => containing_rule(z) + | Tile(t) => + switch (t.label, Zipper.parent(z)) { + | ([","], Some(Tile({label: ["[", "]"] | ["(", ")"], id, _}))) => + term(id, z) + | _ => current_term(z) + } + } + | _ => None + }; + + let grow_right_until_not_comment_or_space = + Move.do_until(go(Local(Right(ByToken))), Piece.not_comment_or_space); + + let containing_secondary_run = z => { + let z = + switch (Move.left_until_not_comment_or_space(~move_first=false, z)) { + | None => + /* Due to implementation details of Move.do_until (specifically its + * use of Indicated), this behaves poorly if we're one token away + * from the beginning of the syntax. We handle that case here */ + let z = Zipper.set_caret(Outer, z); + switch (Zipper.move(Left, z)) { + | Some(z) => z + | None => z + }; + | Some(z) => z + }; + let* z = grow_right_until_not_comment_or_space(z); + go(Local(Left(ByToken)), z); /* above overshoots */ + }; + + let indicated_token = (z: Zipper.t) => + switch (Indicated.piece'(~no_ws=false, ~ign=Piece.is_secondary, z)) { + | Some((Secondary(_), _, _)) => + /* If there is secondary on both sides, select the + * largest contiguous run of non-linebreak secondary */ + containing_secondary_run(z) + | Some((_, Left, _)) when z.caret == Outer => + /* If we're on the far right side of a non-secondary piece, we + * still prefer to select it over secondary to the right */ + let* z = Move.go(Local(Left(ByToken)), z); + go(Local(Right(ByToken)), z); + | Some(_) => go(Local(Right(ByToken)), z) + | _ => None + }; + + let parent_of_indicated = (z: Zipper.t, info_map) => { + let statics_of = Id.Map.find_opt(_, info_map); + let* base_id = Indicated.index(z); + let* ci = statics_of(base_id); + let* id = + switch (Info.ancestors_of(ci)) { + | [] => None + | [parent, ..._] => Some(parent) + }; + let* ci_parent = statics_of(id); + switch (Info.cls_of(ci_parent)) { + | Exp(Let | TyAlias) => + /* For definition-type forms, don't select the body, + * unless the body is precisely what we're clicking on */ + switch (ci_parent) { + | InfoExp({term: t, _}) => + switch (IdTagged.term_of(t)) { + | Let(_, _, body) + | TyAlias(_, _, body) => + let body_id = IdTagged.rep_id(body); + base_id == body_id ? term(id, z) : tile(id, z); + | _ => tile(id, z) + } + | _ => tile(id, z) + } + | Exp(Match) => + /* Case rules aren't terms in the syntax model, + * but here we pretend they are */ + let* z = Move.left_until_case_or_rule(z); + switch (Indicated.piece''(z)) { + | Some((p, _, _)) => + switch (p) { + | Tile({label: ["|", "=>"], _}) => containing_rule(z) + | Tile({label: ["case", "end"], _}) => term(id, z) + | _ => None + } + | _ => None + }; + | _ => + switch (Info.ancestors_of(ci_parent)) { + | [] => term(id, z) + | [gp, ..._] => + let* ci_gp = statics_of(gp); + switch (Info.cls_of(ci_parent), Info.cls_of(ci_gp)) { + | ( + Exp(Tuple) | Pat(Tuple) | Typ(Prod), + Exp(Parens) | Pat(Parens) | Typ(Parens), + ) => + /* If parent is tuple, check if it's in parens, + * and if so, select the parens as well */ + term(gp, z) + | _ => term(id, z) + }; } }; + }; }; diff --git a/src/haz3lcore/zipper/projectors/CheckboxProj.re b/src/haz3lcore/zipper/projectors/CheckboxProj.re new file mode 100644 index 0000000000..b1d734a8cf --- /dev/null +++ b/src/haz3lcore/zipper/projectors/CheckboxProj.re @@ -0,0 +1,53 @@ +open Util; +open ProjectorBase; +open Virtual_dom.Vdom; + +let of_mono = (syntax: Piece.t): option(string) => + switch (syntax) { + | Tile({label: [l], _}) => Some(l) + | _ => None + }; + +let mk_mono = (sort: Sort.t, string: string): Piece.t => + string |> Form.mk_atomic(sort) |> Piece.mk_tile(_, []); + +let state_of = (piece: Piece.t): option(bool) => + piece |> of_mono |> Option.map(bool_of_string); + +let get = (piece: Piece.t): bool => + switch (piece |> of_mono |> Util.OptUtil.and_then(bool_of_string_opt)) { + | None => failwith("Checkbox: not boolean literal") + | Some(s) => s + }; + +let put = (bool: bool): Piece.t => bool |> string_of_bool |> mk_mono(Exp); + +let toggle = (piece: Piece.t) => put(!get(piece)); + +let view = + (_, ~info, ~local as _, ~parent: external_action => Ui_effect.t(unit)) => + Node.input( + ~attrs= + [ + Attr.create("type", "checkbox"), + Attr.on_input((_, _) => + parent(SetSyntax(put(!get(info.syntax)))) + ), + ] + @ (get(info.syntax) ? [Attr.checked] : []), + (), + ); + +module M: Projector = { + [@deriving (show({with_path: false}), sexp, yojson)] + type model = unit; + [@deriving (show({with_path: false}), sexp, yojson)] + type action = unit; + let init = (); + let can_project = p => state_of(p) != None; + let can_focus = false; + let placeholder = (_, _) => Inline(2); + let update = (model, _) => model; + let view = view; + let focus = _ => (); +}; diff --git a/src/haz3lcore/zipper/projectors/FoldProj.re b/src/haz3lcore/zipper/projectors/FoldProj.re new file mode 100644 index 0000000000..b21ab12721 --- /dev/null +++ b/src/haz3lcore/zipper/projectors/FoldProj.re @@ -0,0 +1,22 @@ +open Util; +open ProjectorBase; +open Virtual_dom.Vdom; +open Node; + +module M: Projector = { + [@deriving (show({with_path: false}), sexp, yojson)] + type model = unit; + [@deriving (show({with_path: false}), sexp, yojson)] + type action = unit; + let init = (); + let can_project = _ => true; + let can_focus = false; + let placeholder = (_, _) => Inline(2); + let update = (_, _) => (); + let view = (_, ~info as _, ~local as _, ~parent) => + div( + ~attrs=[Attr.on_double_click(_ => parent(Remove))], + [text("⋱")], + ); + let focus = _ => (); +}; diff --git a/src/haz3lcore/zipper/projectors/InfoProj.re b/src/haz3lcore/zipper/projectors/InfoProj.re new file mode 100644 index 0000000000..6b467e76b1 --- /dev/null +++ b/src/haz3lcore/zipper/projectors/InfoProj.re @@ -0,0 +1,94 @@ +open Virtual_dom.Vdom; +open Node; +open ProjectorBase; + +let mode = (info: option(Info.t)): option(Mode.t) => + switch (info) { + | Some(InfoExp({mode, _})) + | Some(InfoPat({mode, _})) => Some(mode) + | _ => None + }; + +let expected_ty = (info: option(Info.t)): option(Typ.t) => + switch (mode(info)) { + | Some(mode) => Some(Mode.ty_of(mode)) + | _ => None + }; + +let self_ty = (info: option(Info.t)): option(Typ.t) => + switch (info) { + | Some(InfoExp({self, ctx, _})) => Self.typ_of_exp(ctx, self) + | Some(InfoPat({self, ctx, _})) => Self.typ_of_pat(ctx, self) + | _ => None + }; + +let totalize_ty = (expected_ty: option(Typ.t)): Typ.t => + switch (expected_ty) { + | Some(expected_ty) => expected_ty + | None => Typ.fresh(Unknown(Internal)) + }; + +module M: Projector = { + [@deriving (show({with_path: false}), sexp, yojson)] + type model = + | Expected + | Self; + + [@deriving (show({with_path: false}), sexp, yojson)] + type action = + | ToggleDisplay; + + let init = Expected; + + let can_project = (p: Piece.t): bool => { + switch (Piece.sort(p)) { + | (Exp | Pat, _) => true + | _ when Piece.is_grout(p) => true /* Grout don't have sorts rn */ + | _ => false + }; + }; + + let can_focus = false; + + let display_ty = (model, info) => + switch (model) { + | _ when mode(info) == Some(Syn) => info |> self_ty + | Self => info |> self_ty + | Expected => info |> expected_ty + }; + + let display_mode = (model, info): string => + switch (model) { + | _ when mode(info) == Some(Syn) => "⇐" + | Self => "⇐" + | Expected => "⇒" + }; + + let display = (model, info) => + display_ty(model, info) |> totalize_ty |> Typ.pretty_print; + + let placeholder = (model, info) => + Inline((display(model, info.ci) |> String.length) + 5); + + let update = (model, a: action) => + switch (a, model) { + | (ToggleDisplay, Expected) => Self + | (ToggleDisplay, Self) => Expected + }; + + let view = (model, ~info, ~local, ~parent as _) => + div( + ~attrs=[ + Attr.classes(["info", "code"]), + Attr.on_mousedown(_ => local(ToggleDisplay)), + ], + [ + text("⋱ " ++ display_mode(model, info.ci) ++ " "), + div( + ~attrs=[Attr.classes(["type"])], + [text(display(model, info.ci))], + ), + ], + ); + let focus = _ => (); +}; diff --git a/src/haz3lcore/zipper/projectors/SliderFProj.re b/src/haz3lcore/zipper/projectors/SliderFProj.re new file mode 100644 index 0000000000..4ad36621ad --- /dev/null +++ b/src/haz3lcore/zipper/projectors/SliderFProj.re @@ -0,0 +1,36 @@ +open Util; +open Virtual_dom.Vdom; +open ProjectorBase; + +/* Some decimal places necessary to avoid becoming an int */ +let float_of_float = s => s |> float_of_string |> Printf.sprintf("%.2f"); + +let put = (s: string): Piece.t => s |> float_of_float |> Piece.mk_mono(Exp); + +let get_opt = (piece: Piece.t): option(float) => + piece |> Piece.of_mono |> Util.OptUtil.and_then(float_of_string_opt); + +let get = (piece: Piece.t): float => + switch (get_opt(piece)) { + | None => failwith("ERROR: Slider: not float literal") + | Some(s) => s + }; + +module M: Projector = { + [@deriving (show({with_path: false}), sexp, yojson)] + type model = unit; + [@deriving (show({with_path: false}), sexp, yojson)] + type action = unit; + let init = (); + let can_project = p => get_opt(p) != None; + let can_focus = false; + let placeholder = (_, _) => Inline(10); + let update = (model, _) => model; + let view = + (_, ~info, ~local as _, ~parent: external_action => Ui_effect.t(unit)) => + Util.Web.range( + ~attrs=[Attr.on_input((_, v) => parent(SetSyntax(put(v))))], + get(info.syntax) |> Printf.sprintf("%.2f"), + ); + let focus = _ => (); +}; diff --git a/src/haz3lcore/zipper/projectors/SliderProj.re b/src/haz3lcore/zipper/projectors/SliderProj.re new file mode 100644 index 0000000000..2a73c6d012 --- /dev/null +++ b/src/haz3lcore/zipper/projectors/SliderProj.re @@ -0,0 +1,33 @@ +open Util; +open Virtual_dom.Vdom; +open ProjectorBase; + +let put: string => Piece.t = Piece.mk_mono(Exp); + +let get_opt = (piece: Piece.t): option(int) => + piece |> Piece.of_mono |> Util.OptUtil.and_then(int_of_string_opt); + +let get = (piece: Piece.t): string => + switch (get_opt(piece)) { + | None => failwith("ERROR: Slider: not integer literal") + | Some(s) => string_of_int(s) + }; + +module M: Projector = { + [@deriving (show({with_path: false}), sexp, yojson)] + type model = unit; + [@deriving (show({with_path: false}), sexp, yojson)] + type action = unit; + let init = (); + let can_project = p => get_opt(p) != None; + let can_focus = false; + let placeholder = (_, _) => Inline(10); + let update = (model, _) => model; + let view = + (_, ~info, ~local as _, ~parent: external_action => Ui_effect.t(unit)) => + Util.Web.range( + ~attrs=[Attr.on_input((_, v) => parent(SetSyntax(put(v))))], + get(info.syntax), + ); + let focus = _ => (); +}; diff --git a/src/haz3lcore/zipper/projectors/TextAreaProj.re b/src/haz3lcore/zipper/projectors/TextAreaProj.re new file mode 100644 index 0000000000..d6488afd86 --- /dev/null +++ b/src/haz3lcore/zipper/projectors/TextAreaProj.re @@ -0,0 +1,121 @@ +open Util; +open Virtual_dom.Vdom; +open ProjectorBase; + +let of_id = (id: Id.t) => + "id" ++ (id |> Id.to_string |> String.sub(_, 0, 8)); + +let of_mono = (syntax: Piece.t): option(string) => + switch (syntax) { + | Tile({label: [l], _}) => Some(StringUtil.unescape_linebreaks(l)) + | _ => None + }; + +let mk_mono = (sort: Sort.t, string: string): Piece.t => + string + |> StringUtil.escape_linebreaks + |> Form.mk_atomic(sort) + |> Piece.mk_tile(_, []); + +let get = (piece: Piece.t): string => + switch (piece |> of_mono) { + | None => failwith("TextArea: not string literal") + | Some(s) => s + }; + +let put = (s: string): Piece.t => s |> mk_mono(Exp); + +let put = (str: string): external_action => + SetSyntax(str |> Form.string_quote |> put); + +let is_last_pos = id => + Web.TextArea.caret_at_end(Web.TextArea.get(of_id(id))); +let is_first_pos = id => + Web.TextArea.caret_at_start(Web.TextArea.get(of_id(id))); + +let key_handler = (id, ~parent, evt) => { + open Effect; + let key = Key.mk(KeyDown, evt); + + switch (key.key) { + | D("ArrowRight" | "ArrowDown") when is_last_pos(id) => + JsUtil.get_elem_by_id(of_id(id))##blur; + Many([parent(Escape(Right)), Stop_propagation]); + | D("ArrowLeft" | "ArrowUp") when is_first_pos(id) => + JsUtil.get_elem_by_id(of_id(id))##blur; + Many([parent(Escape(Left)), Stop_propagation]); + /* Defer to parent editor undo for now */ + | D("z" | "Z" | "y" | "Y") when Key.ctrl_held(evt) || Key.meta_held(evt) => + Many([Prevent_default]) + | D("z" | "Z") + when Key.shift_held(evt) && (Key.ctrl_held(evt) || Key.meta_held(evt)) => + Many([Prevent_default]) + | D("\"") => + /* Hide quotes from both the textarea and parent editor */ + Many([Prevent_default, Stop_propagation]) + | _ => Stop_propagation + }; +}; + +let textarea = + (id, ~parent: external_action => Ui_effect.t(unit), text: string) => + Node.textarea( + ~attrs=[ + Attr.id(of_id(id)), + Attr.on_keydown(key_handler(id, ~parent)), + Attr.on_input((_, new_text) => + Effect.(Many([parent(put(new_text))])) + ), + /* Note: adding these handlers below because + * currently these are handled on page level. + * unnecesary maybe if we move handling down */ + Attr.on_copy(_ => Effect.Stop_propagation), + Attr.on_cut(_ => Effect.Stop_propagation), + Attr.on_paste(_ => Effect.Stop_propagation), + Attr.string_property("value", text), + ], + [], + ); + +let view = (_, ~info, ~local as _, ~parent) => { + let text = info.syntax |> get |> Form.strip_quotes; + Node.div( + ~attrs=[Attr.classes(["wrapper"])], + [ + Node.div( + ~attrs=[Attr.classes(["cols", "code"])], + [Node.text("·")] @ [textarea(info.id, ~parent, text)], + ), + ], + ); +}; + +module M: Projector = { + [@deriving (show({with_path: false}), sexp, yojson)] + type model = unit; + [@deriving (show({with_path: false}), sexp, yojson)] + type action = unit; + let init = (); + let can_project = _ => true; //TODO(andrew): restrict somehow + let can_focus = true; + let placeholder = (_, info) => { + let str = Form.strip_quotes(get(info.syntax)); + Block({ + row: StringUtil.num_lines(str), + /* +2 for left and right padding */ + col: 2 + StringUtil.max_line_width(str), + }); + }; + let update = (model, _) => model; + let view = view; + let focus = ((id: Id.t, d: option(Direction.t))) => { + JsUtil.get_elem_by_id(of_id(id))##focus; + switch (d) { + | None => () + | Some(Left) => + Web.TextArea.set_caret_to_start(Web.TextArea.get(of_id(id))) + | Some(Right) => + Web.TextArea.set_caret_to_end(Web.TextArea.get(of_id(id))) + }; + }; +}; diff --git a/src/haz3lschool/Exercise.re b/src/haz3lschool/Exercise.re index 86fdd4ce99..b5e7dfc76d 100644 --- a/src/haz3lschool/Exercise.re +++ b/src/haz3lschool/Exercise.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; open Haz3lcore; module type ExerciseEnv = { @@ -336,57 +336,59 @@ module F = (ExerciseEnv: ExerciseEnv) => { }; }; - let editor_of_serialization = zipper => Editor.init(zipper); - let eds_of_spec: spec => eds = - ( - { - title, - version, - module_name, - prompt, - point_distribution, - prelude, - correct_impl, - your_tests, - your_impl, - hidden_bugs, - hidden_tests, - syntax_tests, - }, - ) => { - let prelude = editor_of_serialization(prelude); - let correct_impl = editor_of_serialization(correct_impl); - let your_tests = { - let tests = editor_of_serialization(your_tests.tests); - {tests, required: your_tests.required, provided: your_tests.provided}; - }; - let your_impl = editor_of_serialization(your_impl); - let hidden_bugs = - hidden_bugs - |> List.map(({impl, hint}) => { - let impl = editor_of_serialization(impl); - {impl, hint}; - }); - let hidden_tests = { - let {tests, hints} = hidden_tests; - let tests = editor_of_serialization(tests); - {tests, hints}; - }; - { - title, - version, - module_name, - prompt, - point_distribution, - prelude, - correct_impl, - your_tests, - your_impl, - hidden_bugs, - hidden_tests, - syntax_tests, - }; + let eds_of_spec = + ( + { + title, + version, + module_name, + prompt, + point_distribution, + prelude, + correct_impl, + your_tests, + your_impl, + hidden_bugs, + hidden_tests, + syntax_tests, + }, + ~settings: CoreSettings.t, + ) + : eds => { + let editor_of_serialization = Editor.init(~settings); + let prelude = editor_of_serialization(prelude); + let correct_impl = editor_of_serialization(correct_impl); + let your_tests = { + let tests = editor_of_serialization(your_tests.tests); + {tests, required: your_tests.required, provided: your_tests.provided}; + }; + let your_impl = editor_of_serialization(your_impl); + let hidden_bugs = + hidden_bugs + |> List.map(({impl, hint}) => { + let impl = editor_of_serialization(impl); + {impl, hint}; + }); + let hidden_tests = { + let {tests, hints} = hidden_tests; + let tests = editor_of_serialization(tests); + {tests, hints}; + }; + { + title, + version, + module_name, + prompt, + point_distribution, + prelude, + correct_impl, + your_tests, + your_impl, + hidden_bugs, + hidden_tests, + syntax_tests, }; + }; // // Old version of above that did string-based parsing, may be useful @@ -477,8 +479,9 @@ module F = (ExerciseEnv: ExerciseEnv) => { }; }; - let state_of_spec = (spec, ~instructor_mode: bool): state => { - let eds = eds_of_spec(spec); + let state_of_spec = + (spec, ~instructor_mode: bool, ~settings: CoreSettings.t): state => { + let eds = eds_of_spec(~settings, spec); set_instructor_mode({pos: YourImpl, eds}, instructor_mode); }; @@ -498,15 +501,16 @@ module F = (ExerciseEnv: ExerciseEnv) => { (pos, positioned_zippers): persistent_state, ~spec: spec, ~instructor_mode: bool, + ~settings: CoreSettings.t, ) : state => { let lookup = (pos, default) => if (visible_in(pos, ~instructor_mode)) { let persisted_zipper = List.assoc(pos, positioned_zippers); let zipper = PersistentZipper.unpersist(persisted_zipper); - Editor.init(zipper); + Editor.init(zipper, ~settings); } else { - editor_of_serialization(default); + Editor.init(default, ~settings); }; let prelude = lookup(Prelude, spec.prelude); let correct_impl = lookup(CorrectImpl, spec.correct_impl); @@ -554,17 +558,6 @@ module F = (ExerciseEnv: ExerciseEnv) => { // # Stitching - module TermItem = { - type t = { - term: TermBase.UExp.t, - term_ranges: TermRanges.t, - }; - }; - - module StaticsItem = { - type t = CachedStatics.statics; - }; - type stitched('a) = { test_validation: 'a, // prelude + correct_impl + your_tests user_impl: 'a, // prelude + your_impl @@ -575,24 +568,26 @@ module F = (ExerciseEnv: ExerciseEnv) => { hidden_tests: 'a, }; - let wrap_filter = (act: FilterAction.action, term: Term.UExp.t): Term.UExp.t => - TermBase.UExp.{ + let wrap_filter = (act: FilterAction.action, term: UExp.t): UExp.t => + Exp.{ term: - TermBase.UExp.Filter( - FilterAction.(act, One), - {term: Constructor("$e"), ids: [Id.mk()]}, + Exp.Filter( + Filter({ + act: FilterAction.(act, One), + pat: { + term: Constructor("$e", Unknown(Internal) |> Typ.temp), + copied: false, + ids: [Id.mk()], + }, + }), term, ), + copied: false, ids: [Id.mk()], }; - let wrap = (term, editor: Editor.t): TermItem.t => { - term, - term_ranges: editor.state.meta.term_ranges, - }; - - let term_of = (editor: Editor.t): Term.UExp.t => - editor.state.meta.view_term; + let term_of = (editor: Editor.t): UExp.t => + MakeTerm.from_zip_for_sem(editor.state.zipper).term; let stitch3 = (ed1: Editor.t, ed2: Editor.t, ed3: Editor.t) => EditorUtil.append_exp( @@ -600,7 +595,7 @@ module F = (ExerciseEnv: ExerciseEnv) => { term_of(ed3), ); - let stitch_term = ({eds, _}: state): stitched(TermItem.t) => { + let stitch_term = ({eds, _}: state): stitched(UExp.t) => { let instructor = stitch3(eds.prelude, eds.correct_impl, eds.hidden_tests.tests); let user_impl_term = { @@ -617,24 +612,23 @@ module F = (ExerciseEnv: ExerciseEnv) => { let hidden_tests_term = EditorUtil.append_exp(user_impl_term, term_of(eds.hidden_tests.tests)); { - test_validation: wrap(test_validation_term, eds.your_tests.tests), - user_impl: wrap(user_impl_term, eds.your_impl), - user_tests: wrap(user_tests_term, eds.your_tests.tests), + test_validation: test_validation_term, + user_impl: user_impl_term, + user_tests: user_tests_term, // instructor works here as long as you don't shadow anything in the prelude - prelude: wrap(instructor, eds.prelude), - instructor: wrap(instructor, eds.correct_impl), + prelude: instructor, + instructor, hidden_bugs: List.map( - (t): TermItem.t => - wrap(stitch3(eds.prelude, t.impl, eds.your_tests.tests), t.impl), + (t): UExp.t => stitch3(eds.prelude, t.impl, eds.your_tests.tests), eds.hidden_bugs, ), - hidden_tests: wrap(hidden_tests_term, eds.hidden_tests.tests), + hidden_tests: hidden_tests_term, }; }; let stitch_term = Core.Memo.general(stitch_term); - type stitched_statics = stitched(StaticsItem.t); + type stitched_statics = stitched(Editor.CachedStatics.t); /* Multiple stitchings are needed for each exercise (see comments in the stitched type above) @@ -642,14 +636,10 @@ module F = (ExerciseEnv: ExerciseEnv) => { Stitching is necessary to concatenate terms from different editors, which are then typechecked. */ let stitch_static = - (settings: CoreSettings.t, t: stitched(TermItem.t)): stitched_statics => { - let mk = ({term, term_ranges, _}: TermItem.t): StaticsItem.t => { - let info_map = Interface.Statics.mk_map(settings, term); - { - term, - error_ids: Statics.Map.error_ids(term_ranges, info_map), - info_map, - }; + (settings: CoreSettings.t, t: stitched(UExp.t)): stitched_statics => { + let mk = (term: UExp.t): Editor.CachedStatics.t => { + let info_map = Statics.mk(settings, Builtins.ctx_init, term); + {term, error_ids: Statics.Map.error_ids(info_map), info_map}; }; let instructor = mk(t.instructor); { @@ -665,24 +655,6 @@ module F = (ExerciseEnv: ExerciseEnv) => { let stitch_static = Core.Memo.general(stitch_static); - let statics_of_stiched = - (state: state, s: stitched(StaticsItem.t)): StaticsItem.t => - switch (state.pos) { - | Prelude => s.prelude - | CorrectImpl => s.instructor - | YourTestsValidation => s.test_validation - | YourTestsTesting => s.user_tests - | YourImpl => s.user_impl - | HiddenBugs(idx) => List.nth(s.hidden_bugs, idx) - | HiddenTests => s.hidden_tests - }; - - let statics_of = (~settings, exercise: state): StaticsItem.t => - exercise - |> stitch_term - |> stitch_static(settings) - |> statics_of_stiched(exercise); - let prelude_key = "prelude"; let test_validation_key = "test_validation"; let user_impl_key = "user_impl"; @@ -704,7 +676,7 @@ module F = (ExerciseEnv: ExerciseEnv) => { let spliced_elabs = (settings: CoreSettings.t, state: state) - : list((ModelResults.key, DHExp.t)) => { + : list((ModelResults.key, Elaborator.Elaboration.t)) => { let { test_validation, user_impl, @@ -715,8 +687,9 @@ module F = (ExerciseEnv: ExerciseEnv) => { hidden_tests, } = stitch_static(settings, stitch_term(state)); - let elab = (s: CachedStatics.statics) => - Interface.elaborate(~settings, s.info_map, s.term); + let elab = (s: Editor.CachedStatics.t): Elaborator.Elaboration.t => { + d: Interface.elaborate(~settings, s.info_map, s.term), + }; [ (test_validation_key, elab(test_validation)), (user_impl_key, elab(user_impl)), @@ -726,49 +699,36 @@ module F = (ExerciseEnv: ExerciseEnv) => { ] @ ( hidden_bugs - |> List.mapi((n, hidden_bug: StaticsItem.t) => + |> List.mapi((n, hidden_bug: Editor.CachedStatics.t) => (hidden_bugs_key(n), elab(hidden_bug)) ) ); }; - let mk_statics = - (settings: CoreSettings.t, state: state) - : list((ModelResults.key, StaticsItem.t)) => { - let stitched = stitch_static(settings, stitch_term(state)); - [ - (prelude_key, stitched.prelude), - (test_validation_key, stitched.test_validation), - (user_impl_key, stitched.user_impl), - (user_tests_key, stitched.user_tests), - (instructor_key, stitched.instructor), - (hidden_tests_key, stitched.hidden_tests), - ] - @ List.mapi( - (n, hidden_bug: StaticsItem.t) => (hidden_bugs_key(n), hidden_bug), - stitched.hidden_bugs, - ); - }; - module DynamicsItem = { type t = { - term: TermBase.UExp.t, - info_map: Statics.Map.t, + statics: Editor.CachedStatics.t, result: ModelResult.t, }; - let empty: t = { - term: { - term: Tuple([]), - ids: [Id.mk()], - }, - info_map: Id.Map.empty, + let empty: t = {statics: Editor.CachedStatics.empty, result: NoElab}; + let statics_only = (statics: Editor.CachedStatics.t): t => { + statics, result: NoElab, }; - let statics_only = ({term, info_map, _}: StaticsItem.t): t => { - {term, info_map, result: NoElab}; - }; }; + let statics_of_stiched_dynamics = + (state: state, s: stitched(DynamicsItem.t)): Editor.CachedStatics.t => + switch (state.pos) { + | Prelude => s.prelude.statics + | CorrectImpl => s.instructor.statics + | YourTestsValidation => s.test_validation.statics + | YourTestsTesting => s.user_tests.statics + | YourImpl => s.user_impl.statics + | HiddenBugs(idx) => List.nth(s.hidden_bugs, idx).statics + | HiddenTests => s.hidden_tests.statics + }; + /* Given the evaluation results, collects the relevant information for producing dynamic feedback*/ @@ -799,50 +759,27 @@ module F = (ExerciseEnv: ExerciseEnv) => { let test_validation = DynamicsItem.{ - term: test_validation.term, - info_map: test_validation.info_map, + statics: test_validation, result: result_of(test_validation_key), }; let user_impl = - DynamicsItem.{ - term: user_impl.term, - info_map: user_impl.info_map, - result: result_of(user_impl_key), - }; + DynamicsItem.{statics: user_impl, result: result_of(user_impl_key)}; let user_tests = - DynamicsItem.{ - term: user_tests.term, - info_map: user_tests.info_map, - result: result_of(user_tests_key), - }; - let prelude = - DynamicsItem.{ - term: prelude.term, - info_map: prelude.info_map, - result: NoElab, - }; + DynamicsItem.{statics: user_tests, result: result_of(user_tests_key)}; + let prelude = DynamicsItem.{statics: prelude, result: NoElab}; let instructor = - DynamicsItem.{ - term: instructor.term, - info_map: instructor.info_map, - result: result_of(instructor_key), - }; + DynamicsItem.{statics: instructor, result: result_of(instructor_key)}; let hidden_bugs = List.mapi( - (n, statics_item: StaticsItem.t) => - DynamicsItem.{ - term: statics_item.term, - info_map: statics_item.info_map, - result: result_of(hidden_bugs_key(n)), - }, + (n, statics: Editor.CachedStatics.t) => + DynamicsItem.{statics, result: result_of(hidden_bugs_key(n))}, hidden_bugs, ); let hidden_tests = DynamicsItem.{ - term: hidden_tests.term, - info_map: hidden_tests.info_map, + statics: hidden_tests, result: result_of(hidden_tests_key), }; { diff --git a/src/haz3lschool/Gradescope.re b/src/haz3lschool/Gradescope.re index c3bb2a0001..7277fcf85b 100644 --- a/src/haz3lschool/Gradescope.re +++ b/src/haz3lschool/Gradescope.re @@ -1,5 +1,6 @@ open Haz3lcore; -// open Sexplib.Std; +open Util; + open Haz3lschool; open Core; @@ -44,6 +45,7 @@ type section = { type chapter = list(section); module Main = { + let settings = CoreSettings.on; /* Statics and Dynamics on */ let name_to_exercise_export = path => { let yj = Yojson.Safe.from_file(path); switch (yj) { @@ -60,16 +62,11 @@ module Main = { }; let gen_grading_report = exercise => { let zipper_pp = zipper => { - Printer.pretty_print( - ~measured=Measured.of_segment(Zipper.seg_without_buffer(zipper)), - zipper, - ); + Printer.pretty_print(zipper); }; - let settings = CoreSettings.on; let model_results = spliced_elabs(settings, exercise) |> ModelResults.init_eval - //TODO[Matt]: Make sure this times out correctly |> ModelResults.run_pending(~settings); let stitched_dynamics = stitch_dynamic(settings, exercise, Some(model_results)); @@ -117,6 +114,7 @@ module Main = { let exercise = unpersist_state( persistent_state, + ~settings, ~spec, ~instructor_mode=true, ); diff --git a/src/haz3lschool/Grading.re b/src/haz3lschool/Grading.re index eb94be8aa1..9e0f577772 100644 --- a/src/haz3lschool/Grading.re +++ b/src/haz3lschool/Grading.re @@ -1,5 +1,5 @@ open Haz3lcore; -open Sexplib.Std; +open Util; module F = (ExerciseEnv: Exercise.ExerciseEnv) => { open Exercise.F(ExerciseEnv); @@ -171,7 +171,8 @@ module F = (ExerciseEnv: Exercise.ExerciseEnv) => { }; let mk = (~your_impl: Editor.t, ~tests: syntax_tests): t => { - let user_impl_term = your_impl.state.meta.view_term; + let user_impl_term = + MakeTerm.from_zip_for_sem(your_impl.state.zipper).term; let predicates = List.map(((_, p)) => SyntaxTest.predicate_fn(p), tests); diff --git a/src/haz3lschool/SyntaxTest.re b/src/haz3lschool/SyntaxTest.re index ac5f69c50c..385f98021a 100644 --- a/src/haz3lschool/SyntaxTest.re +++ b/src/haz3lschool/SyntaxTest.re @@ -1,5 +1,5 @@ open Haz3lcore; -open Sexplib.Std; +open Util; /* These are the syntax test functions used for the syntax validation @@ -14,12 +14,11 @@ type syntax_result = { percentage: float, }; -let rec find_var_upat = (name: string, upat: Term.UPat.t): bool => { +let rec find_var_upat = (name: string, upat: Pat.t): bool => { switch (upat.term) { | Var(x) => x == name | EmptyHole | Wild - | Triv | Invalid(_) | MultiHole(_) | Int(_) @@ -34,7 +33,7 @@ let rec find_var_upat = (name: string, upat: Term.UPat.t): bool => { List.fold_left((acc, up) => {acc || find_var_upat(name, up)}, false, l) | Parens(up) => find_var_upat(name, up) | Ap(up1, up2) => find_var_upat(name, up1) || find_var_upat(name, up2) - | TypeAnn(up, _) => find_var_upat(name, up) + | Cast(up, _, _) => find_var_upat(name, up) }; }; @@ -46,18 +45,13 @@ let rec find_var_upat = (name: string, upat: Term.UPat.t): bool => { if name="a", then l=[fun x -> x+1] */ let rec find_in_let = - ( - name: string, - upat: Term.UPat.t, - def: Term.UExp.t, - l: list(Term.UExp.t), - ) - : list(Term.UExp.t) => { + (name: string, upat: UPat.t, def: UExp.t, l: list(UExp.t)) + : list(UExp.t) => { switch (upat.term, def.term) { | (Parens(up), Parens(ue)) => find_in_let(name, up, ue, l) | (Parens(up), _) => find_in_let(name, up, def, l) | (_, Parens(ue)) => find_in_let(name, upat, ue, l) - | (TypeAnn(up, _), _) => find_in_let(name, up, def, l) + | (Cast(up, _, _), _) => find_in_let(name, up, def, l) | (Var(x), Fun(_)) => x == name ? [def, ...l] : l | (Tuple(pl), Tuple(ul)) => if (List.length(pl) != List.length(ul)) { @@ -73,8 +67,7 @@ let rec find_in_let = | (Var(_), _) | (Tuple(_), _) | ( - EmptyHole | Wild | Triv | Invalid(_) | MultiHole(_) | Int(_) | Float(_) | - Bool(_) | + EmptyHole | Wild | Invalid(_) | MultiHole(_) | Int(_) | Float(_) | Bool(_) | String(_) | ListLit(_) | Constructor(_) | @@ -90,8 +83,7 @@ let rec find_in_let = Find any function expressions in uexp that are bound to variable name */ let rec find_fn = - (name: string, uexp: Term.UExp.t, l: list(Term.UExp.t)) - : list(Term.UExp.t) => { + (name: string, uexp: UExp.t, l: list(UExp.t)): list(UExp.t) => { switch (uexp.term) { | Let(up, def, body) | Module(up, def, body) => @@ -99,17 +91,19 @@ let rec find_fn = | ListLit(ul) | Tuple(ul) => List.fold_left((acc, u1) => {find_fn(name, u1, acc)}, l, ul) - | TypFun(_, body) - | Fun(_, body) => l |> find_fn(name, body) + | TypFun(_, body, _) + | FixF(_, body, _) + | Fun(_, body, _, _) => l |> find_fn(name, body) | TypAp(u1, _) | Parens(u1) + | Cast(u1, _, _) | UnOp(_, u1) | TyAlias(_, _, u1) | Test(u1) - | Filter(_, _, u1) => l |> find_fn(name, u1) - | Ap(u1, u2) | Dot(u1, u2) - | Pipeline(u1, u2) + | Closure(_, u1) + | Filter(_, u1) => l |> find_fn(name, u1) + | Ap(_, u1, u2) | Seq(u1, u2) | Cons(u1, u2) | ListConcat(u1, u2) @@ -127,15 +121,18 @@ let rec find_fn = ul, ) | EmptyHole - | Triv | Deferral(_) | Invalid(_) | MultiHole(_) + | DynamicErrorHole(_) + | FailedCast(_) | Bool(_) | Int(_) | Float(_) | String(_) | Constructor(_) + | Undefined + | BuiltinFun(_) | Var(_) => l }; }; @@ -143,12 +140,11 @@ let rec find_fn = /* Finds whether variable name is ever mentioned in upat. */ -let rec var_mention_upat = (name: string, upat: Term.UPat.t): bool => { +let rec var_mention_upat = (name: string, upat: Pat.t): bool => { switch (upat.term) { | Var(x) => x == name | EmptyHole | Wild - | Triv | Invalid(_) | MultiHole(_) | Int(_) @@ -169,18 +165,17 @@ let rec var_mention_upat = (name: string, upat: Term.UPat.t): bool => { | Parens(up) => var_mention_upat(name, up) | Ap(up1, up2) => var_mention_upat(name, up1) || var_mention_upat(name, up2) - | TypeAnn(up, _) => var_mention_upat(name, up) + | Cast(up, _, _) => var_mention_upat(name, up) }; }; /* Finds whether variable name is ever mentioned in uexp. */ -let rec var_mention = (name: string, uexp: Term.UExp.t): bool => { +let rec var_mention = (name: string, uexp: Exp.t): bool => { switch (uexp.term) { | Var(x) => x == name | EmptyHole - | Triv | Invalid(_) | MultiHole(_) | Bool(_) @@ -188,8 +183,9 @@ let rec var_mention = (name: string, uexp: Term.UExp.t): bool => { | Float(_) | String(_) | Constructor(_) + | Undefined | Deferral(_) => false - | Fun(args, body) => + | Fun(args, body, _, _) => var_mention_upat(name, args) ? false : var_mention(name, body) | ListLit(l) | Tuple(l) => @@ -198,15 +194,21 @@ let rec var_mention = (name: string, uexp: Term.UExp.t): bool => { | Module(p, def, body) => var_mention_upat(name, p) ? false : var_mention(name, def) || var_mention(name, body) - | TypFun(_, u) + | TypFun(_, u, _) | TypAp(u, _) | Test(u) | Parens(u) | UnOp(_, u) | TyAlias(_, _, u) - | Filter(_, _, u) => var_mention(name, u) - | Ap(u1, u2) - | Pipeline(u1, u2) + | Filter(_, u) => var_mention(name, u) + | DynamicErrorHole(u, _) => var_mention(name, u) + | FailedCast(u, _, _) => var_mention(name, u) + | FixF(args, body, _) => + var_mention_upat(name, args) ? false : var_mention(name, body) + | Closure(_, u) => var_mention(name, u) + | BuiltinFun(_) => false + | Cast(d, _, _) => var_mention(name, d) + | Ap(_, u1, u2) | Seq(u1, u2) | Cons(u1, u2) | ListConcat(u1, u2) @@ -233,11 +235,10 @@ let rec var_mention = (name: string, uexp: Term.UExp.t): bool => { Finds whether variable name is applied on another expresssion. i.e. Ap(Var(name), u) occurs anywhere in the uexp. */ -let rec var_applied = (name: string, uexp: Term.UExp.t): bool => { +let rec var_applied = (name: string, uexp: Exp.t): bool => { switch (uexp.term) { | Var(_) | EmptyHole - | Triv | Invalid(_) | MultiHole(_) | Bool(_) @@ -245,8 +246,10 @@ let rec var_applied = (name: string, uexp: Term.UExp.t): bool => { | Float(_) | String(_) | Constructor(_) + | Undefined | Deferral(_) => false - | Fun(args, body) => + | Fun(args, body, _, _) + | FixF(args, body, _) => var_mention_upat(name, args) ? false : var_applied(name, body) | ListLit(l) | Tuple(l) => @@ -255,18 +258,24 @@ let rec var_applied = (name: string, uexp: Term.UExp.t): bool => { | Module(p, def, body) => var_mention_upat(name, p) ? false : var_applied(name, def) || var_applied(name, body) - | TypFun(_, u) + | TypFun(_, u, _) | Test(u) | Parens(u) | UnOp(_, u) | TyAlias(_, _, u) - | Filter(_, _, u) => var_applied(name, u) + | Filter(_, u) => var_applied(name, u) | TypAp(u, _) => switch (u.term) { | Var(x) => x == name ? true : false | _ => var_applied(name, u) } - | Ap(u1, u2) => + | DynamicErrorHole(_) => false + | FailedCast(_) => false + // This case shouldn't come up! + | Closure(_) => false + | BuiltinFun(_) => false + | Cast(d, _, _) => var_applied(name, d) + | Ap(_, u1, u2) => switch (u1.term) { | Var(x) => x == name ? true : var_applied(name, u2) | _ => var_applied(name, u1) || var_applied(name, u2) @@ -276,11 +285,6 @@ let rec var_applied = (name: string, uexp: Term.UExp.t): bool => { | Var(x) => x == name ? true : List.exists(var_applied(name), us) | _ => List.exists(var_applied(name), us) } - | Pipeline(u1, u2) => - switch (u2.term) { - | Var(x) => x == name ? true : var_applied(name, u1) - | _ => var_applied(name, u1) || var_applied(name, u2) - } | Cons(u1, u2) | Seq(u1, u2) | ListConcat(u1, u2) @@ -304,7 +308,7 @@ let rec var_applied = (name: string, uexp: Term.UExp.t): bool => { /* Check whether all functions bound to variable name are recursive. */ -let is_recursive = (name: string, uexp: Term.UExp.t): bool => { +let is_recursive = (name: string, uexp: Exp.t): bool => { let fn_bodies = [] |> find_fn(name, uexp); if (List.length(fn_bodies) == 0) { false; @@ -322,20 +326,24 @@ let is_recursive = (name: string, uexp: Term.UExp.t): bool => { a tail position in uexp. Note that if the variable is not mentioned anywhere in the expression, the function returns true. */ -let rec tail_check = (name: string, uexp: Term.UExp.t): bool => { +let rec tail_check = (name: string, uexp: Exp.t): bool => { switch (uexp.term) { | EmptyHole - | Triv | Deferral(_) | Invalid(_) | MultiHole(_) + | DynamicErrorHole(_) + | FailedCast(_) | Bool(_) | Int(_) | Float(_) | String(_) | Constructor(_) - | Var(_) => true - | Fun(args, body) => + | Undefined + | Var(_) + | BuiltinFun(_) => true + | FixF(args, body, _) + | Fun(args, body, _, _) => var_mention_upat(name, args) ? false : tail_check(name, body) | Let(p, def, body) | Module(p, def, body) => @@ -347,18 +355,16 @@ let rec tail_check = (name: string, uexp: Term.UExp.t): bool => { !List.fold_left((acc, ue) => {acc || var_mention(name, ue)}, false, l) | Test(_) => false | TyAlias(_, _, u) - | Filter(_, _, u) - | TypFun(_, u) + | Cast(u, _, _) + | Filter(_, u) + | Closure(_, u) + | TypFun(_, u, _) | TypAp(u, _) | Parens(u) => tail_check(name, u) | UnOp(_, u) => !var_mention(name, u) - | Ap(u1, u2) => var_mention(name, u2) ? false : tail_check(name, u1) + | Ap(_, u1, u2) => var_mention(name, u2) ? false : tail_check(name, u1) | DeferredAp(fn, args) => - tail_check( - name, - {ids: [], term: Ap(fn, {ids: [], term: Tuple(args)})}, - ) - | Pipeline(u1, u2) => var_mention(name, u1) ? false : tail_check(name, u2) + tail_check(name, Ap(Forward, fn, Tuple(args) |> Exp.fresh) |> Exp.fresh) | Seq(u1, u2) => var_mention(name, u1) ? false : tail_check(name, u2) | Cons(u1, u2) | ListConcat(u1, u2) @@ -383,7 +389,7 @@ let rec tail_check = (name: string, uexp: Term.UExp.t): bool => { /* Check whether all functions bound to variable name are tail recursive. */ -let is_tail_recursive = (name: string, uexp: Term.UExp.t): bool => { +let is_tail_recursive = (name: string, uexp: UExp.t): bool => { let fn_bodies = [] |> find_fn(name, uexp); if (List.length(fn_bodies) == 0) { false; @@ -396,8 +402,7 @@ let is_tail_recursive = (name: string, uexp: Term.UExp.t): bool => { }; }; -let check = - (uexp: Term.UExp.t, predicates: list(Term.UExp.t => bool)): syntax_result => { +let check = (uexp: UExp.t, predicates: list(UExp.t => bool)): syntax_result => { let results = List.map(pred => {uexp |> pred}, predicates); let length = List.length(predicates); let passing = Util.ListUtil.count_pred(res => res, results); diff --git a/src/haz3lschool/dune b/src/haz3lschool/dune index d9c50213a5..a9f7575c78 100644 --- a/src/haz3lschool/dune +++ b/src/haz3lschool/dune @@ -13,3 +13,11 @@ (libraries ppx_yojson_conv.expander haz3lcore haz3lschool) (preprocess (pps ppx_yojson_conv ppx_let ppx_sexp_conv ppx_deriving.show))) + +(env + (dev + (js_of_ocaml + (flags :standard --debuginfo --noinline --dynlink --linkall --sourcemap))) + (release + (js_of_ocaml + (flags :standard)))) diff --git a/src/haz3lweb/Benchmark.re b/src/haz3lweb/Benchmark.re index 5d0b4390f1..6361b8143e 100644 --- a/src/haz3lweb/Benchmark.re +++ b/src/haz3lweb/Benchmark.re @@ -1,3 +1,5 @@ +open Util; + let sample_1 = {|# Hazel Language Quick Reference # # Recursive Functions (arrow type annotation required) # @@ -43,7 +45,6 @@ let str_to_inserts = (str: string): list(UpdateAction.t) => String.length(str), i => { let c = String.sub(str, i, 1); - let c = c == "\n" ? Haz3lcore.Form.linebreak : c; UpdateAction.PerformAction(Insert(c)); }, ); diff --git a/src/haz3lweb/ColorSteps.re b/src/haz3lweb/ColorSteps.re index fe242aeffc..fe82ab8d02 100644 --- a/src/haz3lweb/ColorSteps.re +++ b/src/haz3lweb/ColorSteps.re @@ -6,7 +6,7 @@ type t = (colorMap, int); /* TODO: Hannah - Pick 7 or so distinct colors from the different color generator thing (HSLuv) Make sure distinguishable for color blind or greyscale - think about related colors for related concepts*/ -let child_colors = ["blue", "pink", "teal", "orange", "purple", "yellow"]; +let child_colors = ["a", "b", "c"]; let empty = (Haz3lcore.Id.Map.empty, 0); let get_color = (id: Haz3lcore.Id.t, (mapping, index): t): (string, t) => diff --git a/src/haz3lweb/DebugConsole.re b/src/haz3lweb/DebugConsole.re index 4e825a27a6..a7f6d8ee33 100644 --- a/src/haz3lweb/DebugConsole.re +++ b/src/haz3lweb/DebugConsole.re @@ -5,39 +5,32 @@ open Haz3lcore; dependency on the model, which is technically against architecture */ let print = ({settings, editors, _}: Model.t, key: string): unit => { - let z = Editors.get_zipper(editors); - let print = str => str |> print_endline; - let settings = settings; - let term = z => z |> MakeTerm.from_zip_for_view |> fst; - let ctx_init = Editors.get_ctx_init(~settings, editors); + let {state: {zipper, meta, _}, _}: Editor.t = Editors.get_editor(editors); + let term = meta.statics.term; + let map = meta.statics.info_map; + let print = print_endline; switch (key) { - | "F1" => z |> Zipper.show |> print - | "F2" => z |> Zipper.unselect_and_zip |> Segment.show |> print - | "F3" => z |> term |> TermBase.UExp.show |> print - | "F4" => - z - |> term - |> Interface.Statics.mk_map_ctx(settings.core, ctx_init) - |> Statics.Map.show - |> print + | "F1" => zipper |> Zipper.show |> print + | "F2" => zipper |> Zipper.unselect_and_zip |> Segment.show |> print + | "F3" => term |> UExp.show |> print + | "F4" => map |> Statics.Map.show |> print | "F5" => - let env_init = Editors.get_env_init(~settings, editors); - Interface.eval_z(~settings=settings.core, ~env_init, ~ctx_init, z) + let env = Editors.get_env_init(~settings, editors); + Interface.elaborate(~settings=settings.core, map, term) + |> Interface.evaluate(~settings=settings.core, ~env) |> ProgramResult.show |> print; | "F6" => - let index = Indicated.index(z); - let map = - z |> term |> Interface.Statics.mk_map_ctx(settings.core, ctx_init); + let index = Indicated.index(zipper); switch (index) { | Some(index) => - switch (Haz3lcore.Id.Map.find_opt(index, map)) { + print("id:" ++ Id.to_string(index)); + switch (Id.Map.find_opt(index, map)) { | Some(ci) => print(Info.show(ci)) | None => print("DEBUG: No CI found for index") - } + }; | None => print("DEBUG: No indicated index") }; - | _ => print("DEBUG: No action for key: " ++ key) }; }; diff --git a/src/haz3lweb/Editors.re b/src/haz3lweb/Editors.re index 95a1d81dbe..f8fa4e0b06 100644 --- a/src/haz3lweb/Editors.re +++ b/src/haz3lweb/Editors.re @@ -1,6 +1,5 @@ -open Sexplib.Std; -open Haz3lcore; open Util; +open Haz3lcore; [@deriving (show({with_path: false}), sexp, yojson)] type scratch = (int, list(ScratchSlide.state)); @@ -40,7 +39,31 @@ let put_editor = (ed: Editor.t, eds: t): t => Exercises(n, specs, Exercise.put_editor(exercise, ed)) }; -let get_zipper = (editors: t): Zipper.t => get_editor(editors).state.zipper; +let update = (f: Editor.t => Editor.t, editors: t): t => + editors |> get_editor |> f |> put_editor(_, editors); + +let update_opt = (editors: t, f: Editor.t => option(Editor.t)): option(t) => + editors |> get_editor |> f |> Option.map(put_editor(_, editors)); + +let perform_action = + (~settings: CoreSettings.t, editors: t, a: Action.t) + : UpdateAction.Result.t(t) => { + let settings = + switch (editors) { + | Exercises(_) => + /* If we're in exercises mode, statics is calculated externally, + * so we set it to off here to disable internal calculation*/ + CoreSettings.on + | _ => settings + }; + switch (Perform.go(~settings, a, get_editor(editors))) { + | Error(err) => Error(FailedToPerform(err)) + | Ok(ed) => Ok(put_editor(ed, editors)) + }; +}; + +let update_current_editor_statics = settings => + update(Editor.update_statics(~settings)); let get_ctx_init = (~settings as _: Settings.t, editors: t): Ctx.t => switch (editors) { @@ -56,39 +79,6 @@ let get_env_init = (~settings as _: Settings.t, editors: t): Environment.t => | Documentation(_) => Builtins.env_init }; -let mk_statics = (~settings: Settings.t, editors: t): CachedStatics.t => { - let editor = get_editor(editors); - let ctx_init = get_ctx_init(~settings, editors); - switch (editors) { - | _ when !settings.core.statics => CachedStatics.mk([]) - | Scratch(idx, _) => - let key = ScratchSlide.scratch_key(string_of_int(idx)); - [(key, ScratchSlide.mk_statics(~settings, editor, ctx_init))] - |> CachedStatics.mk; - | Documentation(name, _) => - let key = ScratchSlide.scratch_key(name); - [(key, ScratchSlide.mk_statics(~settings, editor, ctx_init))] - |> CachedStatics.mk; - | Exercises(_, _, exercise) => - Exercise.mk_statics(settings.core, exercise) |> CachedStatics.mk - }; -}; - -let lookup_statics = - (~settings: Settings.t, ~statics, editors: t): CachedStatics.statics => - switch (editors) { - | _ when !settings.core.statics => CachedStatics.empty_statics - | Scratch(idx, _) => - let key = ScratchSlide.scratch_key(string_of_int(idx)); - CachedStatics.lookup(statics, key); - | Documentation(name, _) => - let key = ScratchSlide.scratch_key(name); - CachedStatics.lookup(statics, key); - | Exercises(_, _, exercise) => - let key = Exercise.key_for_statics(exercise); - CachedStatics.lookup(statics, key); - }; - /* Each mode (e.g. Scratch, School) requires elaborating on some number of expressions that are spliced together from the editors @@ -97,23 +87,20 @@ let lookup_statics = Used in the Update module */ let get_spliced_elabs = - (~settings: Settings.t, statics, editors: t) - : list((ModelResults.key, DHExp.t)) => + (~settings: CoreSettings.t, editors: t) + : list((ModelResults.key, Elaborator.Elaboration.t)) => switch (editors) { | Scratch(idx, _) => let key = ScratchSlide.scratch_key(idx |> string_of_int); - let CachedStatics.{term, info_map, _} = - lookup_statics(~settings, ~statics, editors); - let d = Interface.elaborate(~settings=settings.core, info_map, term); - [(key, d)]; + let statics = get_editor(editors).state.meta.statics; + let d = Interface.elaborate(~settings, statics.info_map, statics.term); + [(key, {d: d})]; | Documentation(name, _) => let key = ScratchSlide.scratch_key(name); - let CachedStatics.{term, info_map, _} = - lookup_statics(~settings, ~statics, editors); - let d = Interface.elaborate(~settings=settings.core, info_map, term); - [(key, d)]; - | Exercises(_, _, exercise) => - Exercise.spliced_elabs(settings.core, exercise) + let statics = get_editor(editors).state.meta.statics; + let d = Interface.elaborate(~settings, statics.info_map, statics.term); + [(key, {d: d})]; + | Exercises(_, _, exercise) => Exercise.spliced_elabs(settings, exercise) }; let set_instructor_mode = (editors: t, instructor_mode: bool): t => @@ -128,34 +115,37 @@ let set_instructor_mode = (editors: t, instructor_mode: bool): t => ) }; -let reset_nth_slide = (n, slides) => { +let reset_nth_slide = (~settings: CoreSettings.t, n, slides): list(Editor.t) => { let (_, init_editors, _) = Init.startup.scratch; let data = List.nth(init_editors, n); - let init_nth = ScratchSlide.unpersist(data); + let init_nth = ScratchSlide.unpersist(~settings, data); Util.ListUtil.put_nth(n, init_nth, slides); }; -let reset_named_slide = (name, slides) => { +let reset_named_slide = + (~settings: CoreSettings.t, name, slides): list((string, Editor.t)) => { let (_, init_editors, _) = Init.startup.documentation; let data = List.assoc(name, init_editors); - let init_name = ScratchSlide.unpersist(data); + let init_name = ScratchSlide.unpersist(~settings, data); slides |> List.remove_assoc(name) |> List.cons((name, init_name)); }; -let reset_current = (editors: t, ~instructor_mode: bool): t => +let reset_current = + (editors: t, ~settings: CoreSettings.t, ~instructor_mode: bool): t => switch (editors) { - | Scratch(n, slides) => Scratch(n, reset_nth_slide(n, slides)) + | Scratch(n, slides) => Scratch(n, reset_nth_slide(~settings, n, slides)) | Documentation(name, slides) => - Documentation(name, reset_named_slide(name, slides)) + Documentation(name, reset_named_slide(~settings, name, slides)) | Exercises(n, specs, _) => Exercises( n, specs, - List.nth(specs, n) |> Exercise.state_of_spec(~instructor_mode), + List.nth(specs, n) + |> Exercise.state_of_spec(~settings, ~instructor_mode), ) }; -let import_current = (editors: t, data: option(string)): t => +let import_current = (~settings, editors: t, data: option(string)): t => switch (editors) { | Documentation(_) | Exercises(_) => failwith("impossible") @@ -163,7 +153,7 @@ let import_current = (editors: t, data: option(string)): t => switch (data) { | None => editors | Some(data) => - let state = ScratchSlide.import(data); + let state = ScratchSlide.import(~settings, data); let slides = Util.ListUtil.put_nth(idx, state, slides); Scratch(idx, slides); } diff --git a/src/haz3lweb/ExerciseUtil.re b/src/haz3lweb/ExerciseUtil.re index 345d79c331..6885b8ae88 100644 --- a/src/haz3lweb/ExerciseUtil.re +++ b/src/haz3lweb/ExerciseUtil.re @@ -1,7 +1,8 @@ open Virtual_dom.Vdom; let code = (code: string) => { - Node.span(~attr=Attr.class_("exercise-code"), [Node.text(code)]); + Node.span(~attrs=[Attr.class_("code")], [Node.text(code)]); }; -let equiv = Node.span(~attr=Attr.class_("equiv"), [Node.text(" ≡ ")]); +let equiv = + Node.span(~attrs=[Attr.class_("equiv")], [Node.text(" ≡ ")]); diff --git a/src/haz3lweb/Export.re b/src/haz3lweb/Export.re index 0aa22384e2..9c9f709fa9 100644 --- a/src/haz3lweb/Export.re +++ b/src/haz3lweb/Export.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type all = { @@ -23,11 +23,11 @@ let mk_all = (~instructor_mode, ~log) => { let settings = Store.Settings.export(); let explainThisModel = Store.ExplainThisModel.export(); let settings_obj = Store.Settings.load(); - let scratch = Store.Scratch.export(~settings=settings_obj.core.evaluation); - let documentation = - Store.Documentation.export(~settings=settings_obj.core.evaluation); + let scratch = Store.Scratch.export(~settings=settings_obj.core); + let documentation = Store.Documentation.export(~settings=settings_obj.core); let exercise = Store.Exercise.export( + ~settings=settings_obj.core, ~specs=ExerciseSettings.exercises, ~instructor_mode, ); @@ -55,7 +55,12 @@ let import_all = (data, ~specs) => { let settings = Store.Settings.import(all.settings); Store.ExplainThisModel.import(all.explainThisModel); let instructor_mode = settings.instructor_mode; - Store.Scratch.import(~settings=settings.core.evaluation, all.scratch); - Store.Exercise.import(all.exercise, ~specs, ~instructor_mode); + Store.Scratch.import(~settings=settings.core, all.scratch); + Store.Exercise.import( + ~settings=settings.core, + all.exercise, + ~specs, + ~instructor_mode, + ); Log.import(all.log); }; diff --git a/src/haz3lweb/FailedInput.re b/src/haz3lweb/FailedInput.re index 199d0b8e50..7e40d69427 100644 --- a/src/haz3lweb/FailedInput.re +++ b/src/haz3lweb/FailedInput.re @@ -1,5 +1,5 @@ open Haz3lcore; -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type reason = diff --git a/src/haz3lweb/FontMetrics.re b/src/haz3lweb/FontMetrics.re index 262ac9ebf2..4ed525c176 100644 --- a/src/haz3lweb/FontMetrics.re +++ b/src/haz3lweb/FontMetrics.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@warning "-33"] [@deriving (show({with_path: false}), sexp, yojson)] diff --git a/src/haz3lweb/Grading.re b/src/haz3lweb/Grading.re index ac7414a5a1..e16827b918 100644 --- a/src/haz3lweb/Grading.re +++ b/src/haz3lweb/Grading.re @@ -5,22 +5,24 @@ include Haz3lschool.Grading.F(Exercise.ExerciseEnv); let score_view = ((earned: points, max: points)) => { div( - ~attr= + ~attrs=[ Attr.classes([ "test-percent", Float.equal(earned, max) ? "all-pass" : "some-fail", ]), + ], [text(Printf.sprintf("%.1f / %.1f pts", earned, max))], ); }; let percentage_view = (p: percentage) => { div( - ~attr= + ~attrs=[ Attr.classes([ "test-percent", Float.equal(p, 1.) ? "all-pass" : "some-fail", ]), + ], [text(Printf.sprintf("%.0f%%", 100. *. p))], ); }; @@ -54,10 +56,10 @@ module TestValidationReport = { let view = (~inject, report: t, max_points: int) => { Cell.report_footer_view([ div( - ~attr=Attr.classes(["test-summary"]), + ~attrs=[Attr.classes(["test-summary"])], [ div( - ~attr=Attr.class_("test-text"), + ~attrs=[Attr.class_("test-text")], [score_view(score_of_percent(percentage(report), max_points))] @ textual_summary(report), ), @@ -83,24 +85,23 @@ module MutationTestingReport = { let summary_message = (~score, ~total, ~found): Node.t => div( - ~attr=Attr.classes(["test-text"]), + ~attrs=[Attr.classes(["test-text"])], [score_view(score), text(summary_str(~total, ~found))], ); let bar = (~inject, instances) => div( - ~attr=Attr.classes(["test-bar"]), + ~attrs=[Attr.classes(["test-bar"])], List.mapi( (id, (status, _)) => div( - ~attr= - Attr.many([ - Attr.classes(["segment", TestStatus.to_string(status)]), - Attr.on_click( - //TODO: wire up test ids - TestView.jump_to_test(~inject, HiddenBugs(id), Id.invalid), - ), - ]), + ~attrs=[ + Attr.classes(["segment", TestStatus.to_string(status)]), + Attr.on_click( + //TODO: wire up test ids + TestView.jump_to_test(~inject, HiddenBugs(id), Id.invalid), + ), + ], [], ), instances, @@ -115,13 +116,14 @@ module MutationTestingReport = { ); let status_class = total == found ? "Pass" : "Fail"; div( - ~attr= + ~attrs=[ Attr.classes([ "cell-item", "test-summary", "cell-report", status_class, ]), + ], [ summary_message( ~score=score_of_percent(percentage(report), max_points), @@ -135,21 +137,21 @@ module MutationTestingReport = { let individual_report = (id, ~inject, ~hint: string, ~status: TestStatus.t) => div( - ~attr= - Attr.many([ - Attr.classes(["test-report"]), - //TODO: wire up test ids - Attr.on_click( - TestView.jump_to_test(~inject, HiddenBugs(id), Id.invalid), - ), - ]), + ~attrs=[ + Attr.classes(["test-report"]), + //TODO: wire up test ids + Attr.on_click( + TestView.jump_to_test(~inject, HiddenBugs(id), Id.invalid), + ), + ], [ div( - ~attr= + ~attrs=[ Attr.classes([ "test-id", "Test" ++ TestStatus.to_string(status), ]), + ], /* NOTE: prints lexical index, not unique id */ [text(string_of_int(id + 1))], ), @@ -157,12 +159,13 @@ module MutationTestingReport = { ] @ [ div( - ~attr= + ~attrs=[ Attr.classes([ "test-hint", "test-instance", TestStatus.to_string(status), ]), + ], [text(hint)], ), ], @@ -212,7 +215,7 @@ module MutationTestingReport = { // |> Zipper.zip // |> MakeTerm.go // |> fst - // |> Term.UExp.show + // |> UExp.show // |> print_endline // |> (_ => Virtual_dom.Vdom.Effect.Ignore); @@ -257,16 +260,18 @@ module SyntaxReport = { let result_string = status ? "Pass" : "Indet"; div( - ~attr=Attr.classes(["test-report"]), + ~attrs=[Attr.classes(["test-report"])], [ div( - ~attr=Attr.classes(["test-id", "Test" ++ result_string]), + ~attrs=[Attr.classes(["test-id", "Test" ++ result_string])], [text(string_of_int(i + 1))], ), ] @ [ div( - ~attr=Attr.classes(["test-hint", "test-instance", result_string]), + ~attrs=[ + Attr.classes(["test-hint", "test-instance", result_string]), + ], [text(hint)], ), ], @@ -297,10 +302,10 @@ module SyntaxReport = { Some( Cell.report_footer_view([ div( - ~attr=Attr.classes(["test-summary"]), + ~attrs=[Attr.classes(["test-summary"])], [ div( - ~attr=Attr.class_("test-text"), + ~attrs=[Attr.class_("test-text")], [ percentage_view(syntax_report.percentage), text( @@ -337,7 +342,7 @@ module ImplGradingReport = { // let num_passed = num_passed(report); // let status_class = total == num_passed ? "Pass" : "Fail"; // div( - // ~attr= + // ~attrs= // Attr.classes([ // "cell-item", // "test-summary", @@ -357,18 +362,18 @@ module ImplGradingReport = { let individual_report = (i, ~inject, ~hint: string, ~status, (id, _)) => div( - ~attr= - Attr.many([ - Attr.classes(["test-report"]), - Attr.on_click(TestView.jump_to_test(~inject, HiddenTests, id)), - ]), + ~attrs=[ + Attr.classes(["test-report"]), + Attr.on_click(TestView.jump_to_test(~inject, HiddenTests, id)), + ], [ div( - ~attr= + ~attrs=[ Attr.classes([ "test-id", "Test" ++ TestStatus.to_string(status), ]), + ], /* NOTE: prints lexical index, not unique id */ [text(string_of_int(i + 1))], ), @@ -376,12 +381,13 @@ module ImplGradingReport = { ] @ [ div( - ~attr= + ~attrs=[ Attr.classes([ "test-hint", "test-instance", TestStatus.to_string(status), ]), + ], [text(hint)], ), ], @@ -426,10 +432,10 @@ module ImplGradingReport = { Some( Cell.report_footer_view([ div( - ~attr=Attr.classes(["test-summary"]), + ~attrs=[Attr.classes(["test-summary"])], [ div( - ~attr=Attr.class_("test-text"), + ~attrs=[Attr.class_("test-text")], [ score_view( score_of_percent( diff --git a/src/haz3lweb/Init.ml b/src/haz3lweb/Init.ml index da597e8f67..4bdbbec0db 100644 --- a/src/haz3lweb/Init.ml +++ b/src/haz3lweb/Init.ml @@ -27,9 +27,9 @@ let startup : PersistentData.t = context_inspector = false; instructor_mode = true; benchmark = false; - mode = Documentation; explainThis = { show = true; show_feedback = false; highlight = NoHighlight }; + mode = Documentation; }; scratch = ( 0, @@ -37,99 +37,71 @@ let startup : PersistentData.t = { zipper = "((selection((focus Left)(content())(mode \ - Normal)))(backpack())(relatives((siblings(((Secondary((id \ - 81269f55-a66c-48d1-9fbe-83187a492f55)(content(Whitespace\" \ - \"))))(Secondary((id \ - a4e41744-51dc-43bb-b359-47cb9649dcd4)(content(Whitespace\" \ - \")))))((Grout((id ef3fb913-bd26-4ef8-af2f-424a73c5c753)(shape \ + Normal)))(backpack())(relatives((siblings((((Grout((id \ + e87c8d67-9374-4a6f-ba01-5ec8f300b924)(shape \ Convex))))))(ancestors())))(caret Outer))"; - backup_text = " "; + backup_text = ""; }; { zipper = "((selection((focus Left)(content())(mode \ - Normal)))(backpack())(relatives((siblings(((Secondary((id \ - 3fd71a3d-9baa-4362-9887-450674850113)(content(Whitespace\" \ - \"))))(Secondary((id \ - 140c0376-4f67-40b6-8056-8cac787af42d)(content(Whitespace\" \ - \")))))((Grout((id 35a88970-2d50-43a7-a476-f81f5b36728d)(shape \ + Normal)))(backpack())(relatives((siblings((((Grout((id \ + e87c8d67-9374-4a6f-ba01-5ec8f300b924)(shape \ Convex))))))(ancestors())))(caret Outer))"; - backup_text = " "; + backup_text = ""; }; { zipper = "((selection((focus Left)(content())(mode \ - Normal)))(backpack())(relatives((siblings(((Secondary((id \ - 36ace27f-cd35-4880-b50c-7629d3a8476a)(content(Whitespace\" \ - \"))))(Secondary((id \ - 39a56f0c-5214-443b-8bd9-931ac9a7720a)(content(Whitespace\" \ - \")))))((Grout((id cbfc7b9d-7a60-4d4d-9a04-5239fe7008a3)(shape \ + Normal)))(backpack())(relatives((siblings((((Grout((id \ + e87c8d67-9374-4a6f-ba01-5ec8f300b924)(shape \ Convex))))))(ancestors())))(caret Outer))"; - backup_text = " "; + backup_text = ""; }; { zipper = "((selection((focus Left)(content())(mode \ - Normal)))(backpack())(relatives((siblings(((Secondary((id \ - 83b9a843-4947-43b0-8232-fb9ce31f8628)(content(Whitespace\" \ - \"))))(Secondary((id \ - abca2150-7d0a-4c6c-8502-bdef953a11be)(content(Whitespace\" \ - \")))))((Grout((id f292f825-054d-4023-80f7-5e436bbc25ff)(shape \ + Normal)))(backpack())(relatives((siblings((((Grout((id \ + e87c8d67-9374-4a6f-ba01-5ec8f300b924)(shape \ Convex))))))(ancestors())))(caret Outer))"; - backup_text = " "; + backup_text = ""; }; { zipper = "((selection((focus Left)(content())(mode \ - Normal)))(backpack())(relatives((siblings(((Secondary((id \ - 520a7c0c-6bb8-4bdc-a548-5431ef003028)(content(Whitespace\" \ - \"))))(Secondary((id \ - dd7c1758-0001-46c0-8ab3-e43a23285e0e)(content(Whitespace\" \ - \")))))((Grout((id 06807411-26c5-493c-8835-258878cb073e)(shape \ + Normal)))(backpack())(relatives((siblings((((Grout((id \ + e87c8d67-9374-4a6f-ba01-5ec8f300b924)(shape \ Convex))))))(ancestors())))(caret Outer))"; - backup_text = " "; + backup_text = ""; }; { zipper = "((selection((focus Left)(content())(mode \ - Normal)))(backpack())(relatives((siblings(((Secondary((id \ - c0748728-2618-4872-881c-ccb38dbd0c58)(content(Whitespace\" \ - \"))))(Secondary((id \ - ab68e973-bf30-463d-989b-c7e37921aca2)(content(Whitespace\" \ - \")))))((Grout((id a9b8ab49-ba54-46b5-b504-c85c3f615c64)(shape \ + Normal)))(backpack())(relatives((siblings((((Grout((id \ + e87c8d67-9374-4a6f-ba01-5ec8f300b924)(shape \ Convex))))))(ancestors())))(caret Outer))"; - backup_text = " "; + backup_text = ""; }; { zipper = "((selection((focus Left)(content())(mode \ - Normal)))(backpack())(relatives((siblings(((Secondary((id \ - 53f99ea5-f1e2-4c4b-bb11-8bb270cc563d)(content(Whitespace\" \ - \"))))(Secondary((id \ - 0595315c-7bd1-43dc-8cd5-ef755f9d7538)(content(Whitespace\" \ - \")))))((Grout((id 6ee496e0-c06a-4c46-bfdd-c844017a8bd2)(shape \ + Normal)))(backpack())(relatives((siblings((((Grout((id \ + e87c8d67-9374-4a6f-ba01-5ec8f300b924)(shape \ Convex))))))(ancestors())))(caret Outer))"; - backup_text = " "; + backup_text = ""; }; { zipper = "((selection((focus Left)(content())(mode \ - Normal)))(backpack())(relatives((siblings(((Secondary((id \ - cdc8e64d-6836-4d9f-9353-969397bfe2ab)(content(Whitespace\" \ - \"))))(Secondary((id \ - 82f3fe37-c665-4aeb-af3d-01ad0de37d40)(content(Whitespace\" \ - \"))))(Secondary((id \ - 749ce88d-f0e0-4694-b13a-0831f733b0ed)(content(Whitespace\" \ - \"))))(Secondary((id \ - 4a7e3e85-8563-4160-a121-bc3c0911118b)(content(Whitespace\" \ - \")))))((Grout((id 75ba0150-8d58-4efe-9253-cc2d7f4df1c4)(shape \ + Normal)))(backpack())(relatives((siblings((((Grout((id \ + e87c8d67-9374-4a6f-ba01-5ec8f300b924)(shape \ Convex))))))(ancestors())))(caret Outer))"; - backup_text = " "; + backup_text = ""; }; ], - [ ("scratch_0", Evaluation) ] ); + [ ("scratch_0", Evaluation); ("scratch_1", Evaluation) ] ); documentation = - ( "Programming Expressively", + ( "Basic Reference", [ ( "Modules", { @@ -1236,8394 +1208,8419 @@ let startup : PersistentData.t = zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Secondary((id \ - 8068a0c4-8131-4ce5-a850-c17e7e7e38a7)(content(Comment\"# \ + 81369b05-3100-46fa-8519-383f032773b7)(content(Comment\"# \ Internal Regression Tests: Function literal casting \ #\"))))(Secondary((id \ - 3be72b01-de96-4cd5-910f-b6f3ab6a172e)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 4d828014-6d8f-434b-abf2-6a662fe33c69)(content(Comment\"# None \ + 661ca937-ef26-4d0f-8e56-34169b5314b4)(content(Whitespace\"\\n\"))))(Secondary((id \ + cec34ac6-7912-499a-9c79-3044a2463686)(content(Comment\"# None \ of the below should trigger runtime exceptions \ #\"))))(Secondary((id \ - c3af568c-60e3-49fb-b4b6-aceb07a91e97)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - e57439be-1c01-459a-bcf9-cd5f3aa8c65d)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - ce9fa5fe-b457-40f2-b69a-1dd30d72b19a)(label(let = \ + 7226679b-c010-43b2-9dc4-17a1c5810b79)(content(Whitespace\"\\n\"))))(Secondary((id \ + 3286f00c-648a-45c0-b4ba-facb03d5f5eb)(content(Whitespace\"\\n\"))))(Tile((id \ + 9eaeefd6-f39a-4e11-9bbd-7670fa49ae2d)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 16))(sort Exp))))))(shards(0 1 \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - cbeba9b0-28a2-4e5f-84d3-1ac692fdadac)(content(Whitespace\" \ + 2b64b7f2-0ed1-4c42-a823-872b8a547369)(content(Whitespace\" \ \"))))(Tile((id \ - 5c050101-1fa6-4df8-b20b-b19c253a622d)(label(g))(mold((out \ + e27950cc-13f0-4e63-b33d-bb38bcf4a33d)(label(g))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Tile((id \ - f9aa410a-67dd-402d-bb0f-4a7681401d98)(label(:))(mold((out \ - Pat)(in_())(nibs(((shape(Concave 11))(sort \ - Pat))((shape(Concave 11))(sort \ + ebd66162-10cb-405d-a69c-87c51113f790)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ Typ))))))(shards(0))(children())))(Secondary((id \ - 364edc1f-bb6f-4b64-b3c8-88889944ab35)(content(Whitespace\" \ - \"))))(Secondary((id \ - 8bd22357-2c15-4dcc-92b8-5aa2f6e4762a)(content(Whitespace\" \ - \"))))(Grout((id f20dff97-39f2-4f4d-8f31-684088be69f0)(shape \ - Convex)))(Tile((id \ - ca20cc5f-f628-4149-9310-d59868ecc7a9)(label(->))(mold((out \ - Typ)(in_())(nibs(((shape(Concave 6))(sort \ - Typ))((shape(Concave 6))(sort \ - 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Exp))((shape(Concave 14))(sort Exp))))))(shards(0 \ 1))(children(((Secondary((id \ - 0e052a09-7aba-466c-bfb4-81468b12f9fc)(content(Whitespace\" \ + 89915481-daa5-42f3-954f-948c1aff1549)(content(Whitespace\" \ \"))))(Tile((id \ - 2daa0ef8-d29d-48ae-a138-61fc401ad950)(label(\"(\"\")\"))(mold((out \ + a53dceac-6fe5-405e-a1d7-97343fbc9030)(label(\"(\"\")\"))(mold((out \ Pat)(in_(Pat))(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0 1))(children(((Tile((id \ - be490e19-a602-45dc-b654-6715e590f251)(label(a))(mold((out \ + 0b692918-371b-49dd-9f3d-6c93800c3f31)(label(a))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Tile((id \ - 22e34140-165f-4fac-9ec4-d8e7ab2a3c6f)(label(,))(mold((out \ - Pat)(in_())(nibs(((shape(Concave 14))(sort \ - Pat))((shape(Concave 14))(sort \ + a1517b07-805c-43bf-88df-39d427604f7d)(label(,))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 15))(sort \ + Pat))((shape(Concave 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7860cae2-6f31-4aa9-b131-39cec4057ea0)(content(Whitespace\" \ + 2836f94f-1d02-470e-85ad-b0fee4aa4c22)(content(Whitespace\" \ \"))))(Tile((id \ - 0ca76690-1cf4-41c4-8da5-d4360b4f861f)(label(f))(mold((out \ + f07dcef0-5700-4c69-afad-63e79497701e)(label(f))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 1fe1d913-15ab-4a15-a3f3-81ea684b4397)(label(\"(\"\")\"))(mold((out \ - Exp)(in_(Exp))(nibs(((shape(Concave 1))(sort Exp))((shape \ + 452a38b7-3724-47ae-91d2-b397871e54c8)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape(Concave 2))(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - ff2435e9-c2e0-4316-ac4c-5fe3d2fb687e)(label(1))(mold((out \ + 8a70ca24-26f2-4608-a159-1f11ed4901c0)(label(1))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 6d0b606c-d057-42b3-9d3d-33679988a5a0)(label(,))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 14))(sort \ - Exp))((shape(Concave 14))(sort \ + f340d87c-adff-463e-9045-fcac56ce16fc)(label(,))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 15))(sort \ + Exp))((shape(Concave 15))(sort \ Exp))))))(shards(0))(children())))(Secondary((id \ - 617a93e3-6dd3-46e4-9def-86803cd285d2)(content(Whitespace\" \ + d439aade-1f27-494b-9e00-1930511c5192)(content(Whitespace\" \ \"))))(Tile((id \ - b7f7bb7b-95dd-4cb0-9f3d-b119c4e00b2f)(label(2))(mold((out \ + 59050d8e-66da-4abd-8ed4-5e6febdb06a8)(label(2))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children()))))))))(Tile((id \ - c9999f9e-81e5-457f-bcf4-6fe7400c3e28)(label(\";\"))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 10))(sort \ - Exp))((shape(Concave 10))(sort \ + f485a019-0a07-40d3-899a-9512d4def50c)(label(\";\"))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 16))(sort \ + Exp))((shape(Concave 16))(sort \ Exp))))))(shards(0))(children())))(Secondary((id \ - 726577bf-09ce-4f2e-beae-8218ea89f6ef)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 52fbcb6c-95d9-4124-85d3-f3ce3a042329)(content(Whitespace\" \ - \"))))(Secondary((id \ - 177b5c85-7c56-4a83-a5f7-51cdd52cbba7)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 12f1f2ad-fae3-4ca3-a8fe-fa6fe4b1b167)(content(Whitespace\" \ - \"))))(Grout((id 2b4b41a7-f15e-4558-a584-c0cdce779d18)(shape \ + 5633975f-c769-481e-9b92-68cb2685176c)(content(Whitespace\"\\n\"))))(Grout((id \ + ec5fef77-52f4-4093-a5fa-7e07d30a822b)(shape \ Convex))))))(ancestors())))(caret Outer))"; backup_text = "# Internal Regression Tests: Function literal casting #\n\ # None of the below should trigger runtime exceptions #\n\n\ - let g: -> = fun _ -> 9 in -g(1);\n\n\ + let g: ? -> ? = fun _ -> 9 in -g(1);\n\n\ let f = fun b -> b && true in f(true);\n\ - let f = fun b: -> b && true in f(true);\n\ + let f = fun b: ? -> b && true in f(true);\n\ let f = fun b: Bool -> b && true in f(true);\n\ - let f: = fun b -> b && true in f(true);\n\ - let f: = fun b: -> b && true in f(true);\n\ - let f: = fun b: Bool -> b && true in f(true);\n\ - let f: -> = fun b -> b && true in f(true);\n\ - let f: -> = fun b: -> b && true in f(true);\n\ - let f: -> = fun b: Bool -> b && true in f(true); #ERR#\n\ - let f: Bool -> = fun b -> b && true in f(true);\n\ - let f: Bool -> = fun b: -> b && true in f(true);\n\ - let f: Bool -> = fun b: Bool -> b && true in f(true);\n\ + let f: ? = fun b -> b && true in f(true);\n\ + let f: ? = fun b: ? -> b && true in f(true);\n\ + let f: ? = fun b: Bool -> b && true in f(true);\n\ + let f: ? -> ? = fun b -> b && true in f(true);\n\ + let f: ? -> ? = fun b: ? -> b && true in f(true);\n\ + let f: ? -> ? = fun b: Bool -> b && true in f(true);\n\ + let f: Bool -> ? = fun b -> b && true in f(true);\n\ + let f: Bool -> ? = fun b: ? -> b && true in f(true);\n\ + let f: Bool -> ? = fun b: Bool -> b && true in f(true);\n\ let f: Bool -> Bool = fun b -> b && true in f(true);\n\ - let f: Bool -> Bool = fun b: -> b && true in f(true);\n\ + let f: Bool -> Bool = fun b: ? -> b && true in f(true);\n\ let f: Bool -> Bool = fun b: Bool -> b && true in f(true);\n\ - let f: -> Bool = fun b -> b && true in f(true);\n\ - let f: -> Bool = fun b: -> b && true in f(true);\n\ - let f: -> Bool = fun b: Bool -> b && true in f(true); #ERR#\n\n\ + let f: ? -> Bool = fun b -> b && true in f(true);\n\ + let f: ? -> Bool = fun b: ? -> b && true in f(true);\n\ + let f: ? -> Bool = fun b: Bool -> b && true in f(true); #ERR#\n\n\ let f = fun b -> b && true in f(true) && true;\n\ - let f = fun b: -> b && true in f(true) && true;\n\ + let f = fun b: ? -> b && true in f(true) && true;\n\ let f = fun b: Bool -> b && true in f(true) && true;\n\ - let f: = fun b -> b && true in f(true) && true;\n\ - let f: = fun b: -> b && true in f(true) && true;\n\ - let f: = fun b: Bool -> b && true in f(true) && true;\n\ - let f: -> = fun b -> b && true in f(true) && true;\n\ - let f: -> = fun b: -> b && true in f(true) && true;\n\ - let f: -> = fun b: Bool -> b && true in f(true) && true;\n\ - let f: Bool -> = fun b -> b && true in f(true) && true;\n\ - let f: Bool -> = fun b: -> b && true in f(true) && true;\n\ - let f: Bool -> = fun b: Bool -> b && true in f(true) && \ - true;\n\ + let f: ? = fun b -> b && true in f(true) && true;\n\ + let f: ? = fun b: ? -> b && true in f(true) && true;\n\ + let f: ? = fun b: Bool -> b && true in f(true) && true;\n\ + let f: ? -> ? = fun b -> b && true in f(true) && true;\n\ + let f: ? -> ? = fun b: ? -> b && true in f(true) && true;\n\ + let f: ? -> ? = fun b: Bool -> b && true in f(true) && true;\n\ + let f: Bool -> ? = fun b -> b && true in f(true) && true;\n\ + let f: Bool -> ? = fun b: ? -> b && true in f(true) && true;\n\ + let f: Bool -> ? = fun b: Bool -> b && true in f(true) && true;\n\ let f: Bool -> Bool = fun b -> b && true in f(true) && true;\n\ - let f: Bool -> Bool = fun b: -> b && true in f(true) && \ - true;\n\ + let f: Bool -> Bool = fun b: ? -> b && true in f(true) && true;\n\ let f: Bool -> Bool = fun b: Bool -> b && true in f(true) && \ true;\n\ - let f: -> Bool = fun b -> b && true in f(true) && true;\n\ - let f: -> Bool = fun b: -> b && true in f(true) && true;\n\ - let f: -> Bool = fun b: Bool -> b && true in f(true) && \ + let f: ? -> Bool = fun b -> b && true in f(true) && true;\n\ + let f: ? -> Bool = fun b: ? -> b && true in f(true) && true;\n\ + let f: ? -> Bool = fun b: Bool -> b && true in f(true) && \ true;\n\n\ let f = fun a, b -> a + 1 in f(1, 2);\n\ - let f = fun a: , b -> a + 1 in f(1, 2);\n\ + let f = fun a: ?, b -> a + 1 in f(1, 2);\n\ let f = fun a: Int, b -> a + 1 in f(1, 2);\n\ - let f = fun (a, b): (Int, ) -> a + 1 in f(1, 2);\n\ - let f: = fun a, b -> a + 1 in f(1, 2);\n\ - let f: = fun a: , b -> a + 1 in f(1, 2);\n\ - let f: = fun a: Int, b -> a + 1 in f(1, 2);\n\ - let f: = fun (a, b): (Int, ) -> a + 1 in f(1, 2);\n\ - let f: -> = fun a, b -> a + 1 in f(1, 2);\n\ - let f: -> = fun a: , b -> a + 1 in f(1, 2);\n\ - let f: -> = fun a: Int, b -> a + 1 in f(1, 2);\n\ - let f: -> = fun (a, b): (Int, ) -> a + 1 in f(1, 2);\n\ - let f: ( , ) -> = fun a, b -> a + 1 in f(1, 2);\n\ - let f: ( , ) -> = fun a: , b -> a + 1 in f(1, 2);\n\ - let f: ( , ) -> = fun a: Int, b -> a + 1 in f(1, 2);\n\ - let f: ( , ) -> = fun (a, b): (Int, ) -> a + 1 in f(1, \ + let f = fun (a, b): (Int, ?) -> a + 1 in f(1, 2);\n\ + let f: ? = fun a, b -> a + 1 in f(1, 2);\n\ + let f: ? = fun a: ?, b -> a + 1 in f(1, 2);\n\ + let f: ? = fun a: Int, b -> a + 1 in f(1, 2);\n\ + let f: ? = fun (a, b): (Int, ?) -> a + 1 in f(1, 2);\n\ + let f: ? -> ? = fun a, b -> a + 1 in f(1, 2);\n\ + let f: ? -> ? = fun a: ?, b -> a + 1 in f(1, 2);\n\ + let f: ? -> ? = fun a: Int, b -> a + 1 in f(1, 2);\n\ + let f: ? -> ? = fun (a, b): (Int, ?) -> a + 1 in f(1, 2);\n\ + let f: (?, ?) -> ? = fun a, b -> a + 1 in f(1, 2);\n\ + let f: (?, ?) -> ? = fun a: ?, b -> a + 1 in f(1, 2);\n\ + let f: (?, ?) -> ? = fun a: Int, b -> a + 1 in f(1, 2);\n\ + let f: (?, ?) -> ? = fun (a, b): (Int, ?) -> a + 1 in f(1, 2);\n\ + let f: (Int, ?) -> ? = fun a, b -> a + 1 in f(1, 2);\n\ + let f: (Int, ?) -> ? = fun a: ?, b -> a + 1 in f(1, 2);\n\ + let f: (Int, ?) -> ? = fun a: Int, b -> a + 1 in f(1, 2);\n\ + let f: (Int, ?) -> ? = fun (a, b): (Int, ?) -> a + 1 in f(1, \ 2);\n\ - let f: (Int, ) -> = fun a, b -> a + 1 in f(1, 2);\n\ - let f: (Int, ) -> = fun a: , b -> a + 1 in f(1, 2);\n\ - let f: (Int, ) -> = fun a: Int, b -> a + 1 in f(1, 2);\n\ - let f: (Int, ) -> = fun (a, b): (Int, ) -> a + 1 in \ + let f: (Int, ?) -> Int = fun a, b -> a + 1 in f(1, 2);\n\ + let f: (Int, ?) -> Int = fun a: ?, b -> a + 1 in f(1, 2);\n\ + let f: (Int, ?) -> Int = fun a: Int, b -> a + 1 in f(1, 2);\n\ + let f: (Int, ?) -> Int = fun (a, b): (Int, ?) -> a + 1 in \ f(1, 2);\n\ - let f: (Int, ) -> Int = fun a, b -> a + 1 in f(1, 2);\n\ - let f: (Int, ) -> Int = fun a: , b -> a + 1 in f(1, 2);\n\ - let f: (Int, ) -> Int = fun a: Int, b -> a + 1 in f(1, 2);\n\ - let f: (Int, ) -> Int = fun (a, b): (Int, ) -> a + 1 in \ - f(1, 2);\n\ - let f: -> Int = fun a, b -> a + 1 in f(1, 2);\n\ - let f: -> Int = fun a: , b -> a + 1 in f(1, 2);\n\ - let f: -> Int = fun a: Int, b -> a + 1 in f(1, 2);\n\ - let f: -> Int = fun (a, b): (Int, ) -> a + 1 in f(1, 2);\n\ - \ \n\ - \ "; + let f: ? -> Int = fun a, b -> a + 1 in f(1, 2);\n\ + let f: ? -> Int = fun a: ?, b -> a + 1 in f(1, 2);\n\ + let f: ? -> Int = fun a: Int, b -> a + 1 in f(1, 2);\n\ + let f: ? -> Int = fun (a, b): (Int, ?) -> a + 1 in f(1, 2);\n\ + \ "; } ); ( "ADT Statics", { zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Secondary((id \ - 28357f24-0bee-423a-8233-69bbb2cfd787)(content(Comment\"# \ + 8f545503-9ccc-4a1f-9570-51cc80ed498b)(content(Comment\"# \ Internal Regression Tests: ADT Statics #\"))))(Secondary((id \ - da7d803e-5f91-4afc-b529-fbd0ec0eaafd)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 505df48d-38fb-4b63-8962-c4aa88f70e50)(content(Comment\"# All \ + 7df37433-694f-49e1-bd34-5e440ddce095)(content(Whitespace\"\\n\"))))(Secondary((id \ + f1af6a08-8b94-424e-bf1e-94bb5efddca9)(content(Comment\"# All \ commented lines should show errors as described \ #\"))))(Secondary((id \ - 70e54a1b-8e3f-4e8a-a0f2-f132102dcca2)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 0c97d2fe-e4fa-4699-889c-26f406fc97b7)(content(Comment\"# No \ + 19de118a-4634-458e-ab3d-fa2ddd45182a)(content(Whitespace\"\\n\"))))(Secondary((id \ + 94a20bbb-796f-4b4b-b587-ad228fc451ed)(content(Comment\"# No \ other lines should show errors #\"))))(Secondary((id \ - d99dce2d-ee04-4e13-bcef-375f0608d8c9)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - e13aaf5d-7c93-429f-93ff-47ddd45609b7)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 545d83f6-f159-4fe2-9fb6-f9514dd064b8)(content(Comment\"#type \ + e3134ee0-6c81-431e-a0e9-019b4a005233)(content(Whitespace\"\\n\"))))(Secondary((id \ + ced5b603-67a5-4d6b-8c60-e20d3dc77d8e)(content(Whitespace\"\\n\"))))(Secondary((id \ + bfd76574-e632-450b-8129-cd813c164e53)(content(Comment\"#type \ definitions: no errors#\"))))(Secondary((id \ - b8fe9b8a-9e2e-4774-8e8d-c5202e4d567c)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 54e23d33-2b44-4416-baa9-b82dd9d49fcb)(label(type = \ + 5bbfdda1-e2fe-4fe2-97b5-8e83fe230690)(content(Whitespace\"\\n\"))))(Tile((id \ + e9e303cd-7ef7-4fb5-8cde-6a1951181563)(label(type = \ in))(mold((out Exp)(in_(TPat Typ))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 16))(sort Exp))))))(shards(0 1 \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - db084c97-20fe-487e-8d52-80bc76bd2ede)(content(Whitespace\" \ - \"))))(Grout((id 7273a907-7f31-458a-b84a-ea0a5f3bcab0)(shape \ - Convex)))(Secondary((id \ - 1b874263-3f04-4e50-8ea6-a6a6631c789d)(content(Whitespace\" \ + a72a561d-27a9-41f2-8ef3-8065d19a5fde)(content(Whitespace\" \ + \"))))(Tile((id \ + 850533e9-4d0b-46dd-ba43-5be3eef2406a)(label(?))(mold((out \ + TPat)(in_())(nibs(((shape Convex)(sort TPat))((shape \ + Convex)(sort \ + TPat))))))(shards(0))(children())))(Secondary((id \ + fadcfc44-7cdf-4c69-9f56-1a64ce2ae893)(content(Whitespace\" \ \")))))((Secondary((id \ - 540a9dc5-a060-46f2-987e-8c45d8a3d040)(content(Whitespace\" \ - \"))))(Grout((id 99c6cef7-771c-4b30-afc6-648a2a9b52eb)(shape \ - Convex)))(Secondary((id \ - 67a07a9c-618f-4947-87a0-229733d058e4)(content(Whitespace\" \ + fb0ed68b-3058-49d0-a2d0-658170c04016)(content(Whitespace\" \ + \"))))(Tile((id \ + 1e0c1cb1-d251-4e7b-86c2-e7b1cc089924)(label(?))(mold((out \ + Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ + Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ + 606fc561-7a9f-4c4c-81ab-f4b09c51a78a)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 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1))(children(((Tile((id \ - 930f5a73-f1c0-476a-ba8c-8a113bc9669a)(label(Bool))(mold((out \ + 999c4101-8ebd-4d93-9906-b556bb305e2a)(label(Bool))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort \ Typ))))))(shards(0))(children()))))))))(Secondary((id \ - a5b78531-9d59-4865-a4f0-23232aaad93d)(content(Whitespace\" \ + f0238c1a-3945-4c7f-9966-2545926eb26a)(content(Whitespace\" \ \")))))((Secondary((id \ - ec7248c7-90ca-447f-8192-89917f308bfd)(content(Whitespace\" \ + 800201b5-5580-49dd-ad62-99ce0b47c89d)(content(Whitespace\" \ \"))))(Tile((id \ - 6ea16184-54d7-4ec4-b8c1-0a7146937b23)(label(Yo))(mold((out \ + 5f57a0cd-5a53-4ada-9763-8140b101bb3a)(label(Yo))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 161d2a9b-370b-426a-a206-fbbaf8959b85)(label(\"(\"\")\"))(mold((out \ - Exp)(in_(Exp))(nibs(((shape(Concave 1))(sort Exp))((shape \ + fb796612-8216-4817-94fb-3f09f8795f2f)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape(Concave 2))(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - cc4bb669-3a95-4bd9-bf9f-8290ae158a85)(label(true))(mold((out \ + b76aa6bc-00a8-4153-89bf-3a9e8789aaf8)(label(true))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort \ Exp))))))(shards(0))(children()))))))))(Secondary((id \ - 1a9b1b31-8fc5-4c30-b7a8-f4842dd8e199)(content(Whitespace\" \ + e8e11231-b230-4b90-b83d-cfdb94b2d52b)(content(Whitespace\" \ \")))))))))(Secondary((id \ - eb20e134-9a53-4f56-ae7d-269ee258279c)(content(Whitespace\" \ + 5f4d8d62-4c94-45cf-8386-31cfcfb681ce)(content(Whitespace\" \ \"))))(Secondary((id \ - c248cce3-ba8f-435d-8a74-cf066d9e31be)(content(Comment\"#err: \ + 60550c2e-99ea-4d67-a46e-7bfd21e3c12f)(content(Comment\"#err: \ type incons#\"))))(Secondary((id \ - 13e9a30a-2b86-4f35-8b75-a70f09c615d8)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 5a2fdd2d-99ff-4488-9a13-d03a37eb4f65)(label(\"\\\"Thats all, \ + a324778b-19b4-4577-b891-afd8d0a8ed6c)(content(Whitespace\"\\n\"))))(Tile((id \ + c2c4604a-ea41-48ed-954c-d825082fac69)(label(\"\\\"Thats all, \ folks\\\"\"))(mold((out Exp)(in_())(nibs(((shape Convex)(sort \ Exp))((shape Convex)(sort \ Exp))))))(shards(0))(children())))(Secondary((id \ - 54a6e50e-2bf0-4f4d-a156-5746fe45d59e)(content(Whitespace\"\\226\\143\\142\")))))))(ancestors())))(caret \ + f321b9fc-2601-4ac4-a8e8-49860032d8b9)(content(Whitespace\"\\n\")))))))(ancestors())))(caret \ Outer))"; backup_text = "# Internal Regression Tests: ADT Statics #\n\ # All commented lines should show errors as described #\n\ # No other lines should show errors #\n\n\ #type definitions: no errors#\n\ - type = in\n\ + type ? = ? in\n\ type SingleNull = +One in\n\ type Single = +F(Int) in\n\ type GoodSum = A + B + C(Int) in\n\ - type Partial = Ok( ) + in\n\ + type Partial = Ok(?) + ? in\n\ type DoubleAlias = GoodSum in\n\ type VerticalLeading =\n\ + A\n\ + B(GoodSum)\n\ - + C(Bool->Bool) \n\ + + C(Bool->Bool) \n\ in\n\n\ #incorrect or incomplete type definitions#\n\ - type badTypeName = in #err: invalid type name#\n\ - type ( , ) = in #err: invalid type name#\n\ - type = badTypeToken in #err: invalid type token#\n\ + type badTypeName = ? in #err: invalid type name#\n\ + type (?, ?) = ? in #err: invalid type name#\n\ + type ? = badTypeToken in #err: invalid type token#\n\ type NotASum = NotInSum(Bool) in #err: cons not in sum#\n\ - type Bool = in #err: shadows base type#\n\ + type Bool = ? in #err: shadows base type#\n\ type Dupes =\n\ + Guy(Bool) #no err#\n\ + Guy(Int) #err: already used#\n\ @@ -9633,7 +9630,7 @@ let startup : PersistentData.t = + notvalid #err: invalid#\n\ + Bool #err: expected cons found type#\n\ + Int(Int) #err: expected cons found type#\n\ - + ( )(Int) #err: expected cons found type#\n\ + + (?)(Int) #err: expected cons found type#\n\ + A(Bool)(Int) in #err: expected cons found app#\n\n\ #sums in compound aliases dont add ctrs to scope#\n\ #but compound alias types should propagate analytically#\n\ @@ -9690,4356 +9687,5493 @@ let startup : PersistentData.t = zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Secondary((id \ - c02465e1-d580-455a-aa60-b6aeb9216493)(content(Comment\"# \ + 4b993118-7181-44f4-9ebc-5135577cb42e)(content(Comment\"# \ Hazel Language Quick Reference #\"))))(Secondary((id \ - eac6ad58-e3bb-434f-9db0-2e8fd6072393)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 8a5b7f9a-b19d-4d34-9d0c-c880eebb5d39)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 33151d9c-2446-45f8-a398-c06e4328a468)(content(Comment\"# \ + 3d39cc52-4179-4dbd-8d7f-8444c8c48de9)(content(Whitespace\"\\n\"))))(Secondary((id \ + 3ab06844-7eec-4f8f-a87d-0e3001a93b11)(content(Whitespace\"\\n\"))))(Secondary((id \ + 660bfaf3-fa8e-4961-84e1-b1ab5e2ee342)(content(Comment\"# \ Empty holes stand for missing expressions, patterns, or types \ #\"))))(Secondary((id \ - c8cc13c9-440e-4c52-a8ef-429a39de48d6)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 2fffac84-5d83-47ae-b058-6d237944ec5f)(label(let = \ + b4bd89a7-3836-47a7-ae3f-ddc44c38f63f)(content(Whitespace\"\\n\"))))(Tile((id \ + bf501ab4-ecae-40cb-92a0-9d647a99869c)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - ca102bc0-c98e-4779-a3d0-29482db11528)(content(Whitespace\" \ + 3d0bf2f9-4dae-493f-a12a-c91a69304b52)(content(Whitespace\" \ \"))))(Tile((id \ - 23d28c28-f709-48fd-80a2-91a1261c65a9)(label(empty_hole))(mold((out \ + 9cbd9e9b-4487-4788-90e9-c28bb96ad6b8)(label(empty_hole))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ - a19670da-602a-43b1-98dc-be30daf8027d)(content(Whitespace\" \ + a3705e23-36e4-49d6-bc51-c89215d22537)(content(Whitespace\" \ \")))))((Secondary((id \ - 9be33140-aae6-45d2-b3af-d7236ae2fa80)(content(Whitespace\" \ - \"))))(Grout((id 10150851-d9f1-4c1b-88c1-6eb9cc5ef8b3)(shape \ + fa5cdc0b-fca9-4405-924f-26e7854788c0)(content(Whitespace\" \ + \"))))(Grout((id 736aa798-6b99-4d74-90b5-86362fac847f)(shape \ Convex)))(Secondary((id \ - 2826cf66-55bb-4b97-8e94-d11a05b82536)(content(Whitespace\" \ + 9b90b22f-953c-4c44-b66d-f9775ffbf704)(content(Whitespace\" \ \")))))))))(Secondary((id \ - f1ca0924-2102-4d29-a917-84ed940bed3a)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - f8475082-76c2-4eb8-a3fb-647d9045149b)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 23d2e2a0-ff71-4ff1-b0a7-97f7ca53bfde)(content(Comment\"# \ - Integers #\"))))(Secondary((id \ - c0b7cecc-18fa-4e0b-a69f-1f1fd0f4bc77)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 1a5bb703-4fc2-4a12-956f-28017ffd7729)(label(let = \ + d6de8893-5e8f-499e-a60b-4bb98d8287ac)(content(Whitespace\"\\n\"))))(Secondary((id \ + 7c56a6a5-2b97-43a2-bcb7-8427d98d4b25)(content(Whitespace\"\\n\"))))(Secondary((id \ + 7a57d160-9fec-41b1-a798-9698db0d9922)(content(Comment\"# \ + Non-empty holes are the red boxes around type errors \ + #\"))))(Secondary((id \ + 0bbd0db5-d159-448b-9309-d6d1a62f9acf)(content(Whitespace\"\\n\"))))(Secondary((id \ + eb0e72d7-aca5-4fbf-9f96-4014d26702cd)(content(Comment\"# (you \ + can still run programs with non-empty holes) \ + #\"))))(Secondary((id \ + bb719100-e8dd-4526-8f87-fd6a7820a55f)(content(Whitespace\"\\n\"))))(Tile((id \ + ed7ac66c-6dde-4648-89b4-580a79ed2d8e)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - 6fb983fb-2e59-46ca-968c-ca1e8977e0eb)(content(Whitespace\" \ + 0b5e8152-d002-426f-933d-2979e0d17dd7)(content(Whitespace\" \ \"))))(Tile((id \ - acbb1a16-353e-40fc-b2cd-1e1e5fbf323d)(label(int_lits))(mold((out \ + 5c5191a3-bd21-4580-9e1e-fc55767f0b14)(label(non_empty_hole))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ - cd520e4a-49ec-4ba0-aefa-29ea494ce3f1)(content(Whitespace\" \ + c3e57b97-f59f-473b-b722-63e553f38ba1)(content(Whitespace\" \ \"))))(Tile((id \ - aad44b6d-55b1-4e71-9a3b-0dd9a5398b50)(label(:))(mold((out \ - Pat)(in_())(nibs(((shape(Concave 11))(sort \ - Pat))((shape(Concave 11))(sort \ + ef7ca920-f58d-427f-9aae-9a1a89783317)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ Typ))))))(shards(0))(children())))(Secondary((id \ - 58477ce1-301d-412b-b1f7-1ac9f7aba4bb)(content(Whitespace\" \ + 525770e4-1524-4e6d-85ce-12d93cc21ce9)(content(Whitespace\" \ \"))))(Tile((id \ - ee9010f8-c67e-43e5-965b-e4532e62cbdc)(label(Int))(mold((out \ + c2664c78-f796-4942-ae39-b1ac905775f7)(label(Int))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ - 0a73b46a-1d11-402c-b8d0-f9fec6af22ea)(content(Whitespace\" \ + 155ca8c1-fd5d-4fc0-9c70-40a0393ba9cc)(content(Whitespace\" \ \")))))((Secondary((id \ - 586e8fad-120e-4a52-929e-85b9d8f28b1e)(content(Whitespace\" \ + 8096339d-a032-4643-9b56-8949687b308f)(content(Whitespace\" \ \"))))(Tile((id \ - 062a379e-884f-422c-aa61-721b97b3e20a)(label(1))(mold((out \ + 9b3bab41-f41f-4ac5-a520-84ee8f4042cc)(label(true))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Secondary((id \ - 425a6af2-5fc0-47ea-96f9-b5f92c2c0957)(content(Whitespace\" \ + 791ed55a-ce5f-4398-8772-54209ad86244)(content(Whitespace\" \ \")))))))))(Secondary((id \ - d1e0b19c-3d09-4eee-970c-3b50fea7d15f)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - aba91b6f-c7b4-4dd4-a962-0954aeb11b3a)(label(let = \ + 100e3ae8-5942-4b9d-aecf-3be6f603808b)(content(Whitespace\" \ + \"))))(Secondary((id \ + fdee7287-47a8-48ce-b823-9f59fc313629)(content(Whitespace\"\\n\"))))(Secondary((id \ + 0141e36d-2974-43ec-994d-30cb244fa5c6)(content(Whitespace\"\\n\"))))(Secondary((id \ + a0f55543-a78d-4fa0-b763-8ba69aba702a)(content(Comment\"# \ + Booleans #\"))))(Secondary((id \ + a08d87a6-c940-43e0-8c7b-9ac699933c1f)(content(Whitespace\"\\n\"))))(Tile((id \ + ee0ebe75-b5cd-4519-8d2d-7c1831a633cd)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - 5942a084-27cb-41c8-8048-c0c4c6fd2532)(content(Whitespace\" \ + f364b57e-2fbd-4364-9ae2-e1814619a202)(content(Whitespace\" \ \"))))(Tile((id \ - 753c2bc1-4dd7-413d-b35d-754a16eb667e)(label(negation))(mold((out \ + 989cd45e-2ed1-48e3-9546-1c82558ee3ce)(label(bool))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ - Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ - 1d10b712-3445-44e6-ab94-6502ef325682)(content(Whitespace\" \ + Convex)(sort Pat))))))(shards(0))(children())))(Tile((id \ + 05926ea4-9b3d-4371-90a3-fe8c2b4cd893)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ + Typ))))))(shards(0))(children())))(Secondary((id \ + 3c81c789-e5cf-4b7c-8157-1ff9121b1205)(content(Whitespace\" \ + \"))))(Tile((id \ + 37bd5a94-8a24-48f2-90fa-dc9c26dbefdc)(label(Bool))(mold((out \ + Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ + Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ + c87c752d-9251-450b-a00c-ad2ad02f68e4)(content(Whitespace\" \ \")))))((Secondary((id \ - 7ae5f68d-af34-4e15-8764-257a5a4d685f)(content(Whitespace\" \ + bbdde6f7-5dcf-4604-99e2-8290687f2a67)(content(Whitespace\" \ \"))))(Tile((id \ - 91a73ee8-d7c2-4390-af1f-5e8b8f74c4ab)(label(-))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 2))(sort Exp))))))(shards(0))(children())))(Tile((id \ - 52032473-7237-4de7-aaef-1572d21778d4)(label(1))(mold((out \ + e0f43d1e-ca1e-47bc-a005-9208e06f576d)(label(true))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Secondary((id \ - 9fd2d207-8aef-4b51-985e-6b4b0f85cd50)(content(Whitespace\" \ + cafe7e8c-16f0-44f1-bc68-55a9cbc819cf)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 35e9fd97-0dfa-4760-94f4-54a56efc7bc6)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 994e8699-eae6-4f4a-89e4-e8ad228936d2)(label(let = \ + a939976f-0365-45b4-afef-bf55ae0ca282)(content(Whitespace\"\\n\"))))(Tile((id \ + e197b30f-cbac-4be4-85eb-cbc8bd93515a)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - a90dbe49-f009-4b7b-9c2a-1c67ebfa886f)(content(Whitespace\" \ + c36a29b2-d4ed-4834-965a-42392b214224)(content(Whitespace\" \ \"))))(Tile((id \ - fe5e28ce-5530-4c62-a241-5d8069f21e4e)(label(arithmetic))(mold((out \ + bec60015-6e5d-40df-a85e-d3a130e743e9)(label(operators))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ - d5090a02-9928-482a-948f-1b616daa5209)(content(Whitespace\" \ + 02fea887-d7d8-4ffe-b7e3-937a3cdf6dce)(content(Whitespace\" \ \")))))((Secondary((id \ - ef75cb3f-3312-4415-92ff-8a8b8cbb4912)(content(Whitespace\" \ + 8e07feea-4dd1-4745-ae81-f2178975d9b5)(content(Whitespace\" \ \"))))(Tile((id \ - 688e886f-8b0d-4a1d-b344-f53a8d213f33)(label(1))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ - Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 696aa524-06f5-4717-b164-62e42ae4b9bf)(label(*))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 4))(sort \ - 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3f1d1253-4e0e-4331-bf9c-180e141079b2)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 29d208e1-0c45-44d2-9d94-99224e7b7bae)(content(Comment\"# \ - Non-empty holes are the red dotted boxes around errors \ - #\"))))(Secondary((id \ - 394efbca-78fe-4391-aed8-7cf3e9954cff)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 5501da01-0362-43bd-90d2-2f73051ebd5d)(content(Comment\"# (you \ - can still run programs with non-empty holes) \ - #\"))))(Secondary((id \ - 83366e95-3f7a-43c0-b6dd-b8b856c15bff)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 8ff64362-463c-4a28-b9fb-c5874d923bb7)(label(let = \ + 25c0cf10-0f56-4ba1-82e9-decf3713982b)(content(Whitespace\"\\n\")))))))))(Secondary((id \ + aeb31005-a681-42ec-9fbb-80f743adabbc)(content(Whitespace\"\\n\"))))(Tile((id \ + 94cc5701-6289-4ea8-848c-2d600b5122c3)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ 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0b139f15-6838-49ef-82e4-cbc793728a74)(content(Whitespace\" \ + \"))))(Tile((id \ + 6fb1e073-7438-4730-baca-fcceff91fdd3)(label(==))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 9))(sort \ + Exp))((shape(Concave 9))(sort \ + Exp))))))(shards(0))(children())))(Secondary((id \ + a54cdde1-509e-425a-9324-c9c193506f2f)(content(Whitespace\" \ \"))))(Tile((id \ - ea9e7253-a352-4836-881f-0127b1c871b8)(label(2))(mold((out \ + dacd2803-8d82-473c-bcb7-67361214f2d2)(label(5))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0))(children())))(Secondary((id \ + fa4b0d41-fe34-4970-a3f1-2b64178fd114)(content(Whitespace\" \ + \")))))))))(Tile((id \ + c4ef4f30-4ea8-48a7-a48b-9379b68a1933)(label(\";\"))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 16))(sort \ + Exp))((shape(Concave 16))(sort \ + Exp))))))(shards(0))(children())))(Secondary((id \ + fa633e11-2211-44dd-ae73-69f3aa368032)(content(Whitespace\"\\n\"))))(Secondary((id \ + 2dddcb80-8751-4337-a04f-a5b915d7264c)(content(Whitespace\"\\n\"))))(Secondary((id \ + 52ba9392-cb17-4a17-9424-1ec23bf8c424)(content(Comment\"# The \ + value of the program is shown at the bottom \ + #\"))))(Secondary((id \ + 1025583f-c9fd-4bdf-ae33-39d591894f63)(content(Whitespace\" \ + \"))))(Secondary((id \ + ed6fa8ec-6f73-40d4-974b-fb5a6e500413)(content(Whitespace\" \ + \"))))(Secondary((id \ + 82208130-4678-4f0d-aa70-71bab80882fc)(content(Whitespace\"\\n\"))))(Tile((id \ + edd07cfe-f3d0-46b8-bae7-8c8c7e98a471)(label(2))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0))(children())))(Secondary((id \ + c18ac8c5-f3b1-4264-bb1b-edda6e53fcfc)(content(Whitespace\" \ + \"))))(Tile((id \ + 7dead34d-45fb-4be7-8cc3-3036b7d1bcc2)(label(+))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 6))(sort \ + Exp))((shape(Concave 6))(sort \ + Exp))))))(shards(0))(children())))(Secondary((id \ + ffaeee98-c1de-4d9c-b8d1-ec6f1c2e2f80)(content(Whitespace\" \ + \"))))(Tile((id \ + f31878be-5cd4-4e79-827d-a1d16c837a27)(label(2))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))))(ancestors())))(caret \ + Outer))"; + backup_text = + "# Hazel Language Quick Reference #\n\n\ + # Empty holes stand for missing expressions, patterns, or \ + types #\n\ + let empty_hole = in\n\n\ + # Non-empty holes are the red boxes around type errors #\n\ + # (you can still run programs with non-empty holes) #\n\ + let non_empty_hole : Int = true in \n\n\ + # Booleans #\n\ + let bool: Bool = true in\n\ + let operators = !true && false || true in\n\ + let conditional = if !true then 1 else 2 in\n\n\ + # Integers #\n\ + let num: Int = 1 in\n\ + let arithmetic = -num*1 + 2/3 - 4**5 in\n\ + let comparison =\n\ + (0 == 0, 0 < 1, 1 <= 1, 2 > 1, 1 >= 1) \n\ + in\n\n\ + # Floating Point Numbers #\n\ + let float: Float = 0.1 in\n\ + let artihmetic = 0. *. 1. +. 2. /. 3. -. 4. **. 5. in\n\ + let comparison =\n\ + (0. ==. 0., 0. <. 1., 1. <=. 1., 2. >. 1., 1. >=. 1.) \n\ + in\n\n\ + # Strings #\n\ + let string = \"Hello, world!\" in \n\ + let concatenation = string ++ \" Goodbye.\" in\n\ + let comparison = string$== \"Hello, world!\" in\n\n\ + # Tuples (Destructured with let expressions) #\n\ + let tuple : (Int, Bool, (Bool, Int)) =\n\ + (1, true, (false, 3)) in\n\ + let (a, b, (c, d)) = tuple in\n\n\ + # Functions (Take a single argument which can be a tuple) #\n\ + let y : (Int, Int, Int) -> Int =\n\ + fun (m, x, b) -> m * x + b in\n\n\ + # Recursive Functions (Arrow type annotation required) #\n\ + let double_recursively : Int -> Int =\n\ + fun n ->\n\ + if n == 0 \n\ + then 0 \n\ + else double_recursively(n - 1) + 2 \n\ + in\n\n\ + # Mutual Recursion (bind tuples of functions) #\n\ + let (even : Int -> Bool, odd : Int -> Bool) = \n\ + (fun n -> if n == 0 then true else odd(n - 1),\n\ + fun n -> if n == 0 then false else even(n - 1)) \n\ + in\n\n\ + # Lists #\n\ + let empty_list : [Int] = [] in\n\ + let non_empty_list : [Int] = 1::2::3::[] in\n\ + let list_literals : [Int] = [1, 2, 3] in\n\ + let length : [Int] -> Int =\n\ + fun xs ->\n\ + case xs\n\ + | [] => 0\n\ + | hd::tl => 1 + length(tl) \n\ + end \n\ + in\n\ + let has_at_least_two_elements : [Int] -> Bool =\n\ + fun xs ->\n\ + case xs\n\ + | [] => false\n\ + | hd::[] => false\n\ + | a::b::[] => true \n\ + end \n\ + in\n\n\ + # Algebraic Data Types #\n\ + type Exp =\n\ + + Var(String)\n\ + + Lam(String, Exp)\n\ + + Ap(Exp, Exp) in\n\ + let exp_equal: (Exp, Exp) -> Bool =\n\ + fun es ->\n\ + case es\n\ + | Var(x), Var(y) => x$== y\n\ + | Lam(x1, e1), Lam(x2, e2) =>\n\ + x1$== x2 && exp_equal(e1, e2)\n\ + | Ap(e1, e2), Ap(e3, e4) =>\n\ + exp_equal(e1, e3) && exp_equal(e2, e4)\n\ + | _ => false \n\ + end \n\ + in\n\n\ + # Polymorphic Functions #\n\ + let poly_id: forall a -> a -> a =\n\ + typfun a -> fun x : a -> x \n\ + in\n\ + let apply_both:\n\ + forall a -> forall b -> (forall c -> c -> c) -> ((a, b) -> \ + (a, b)) =\n\ + typfun a -> typfun b ->\n\ + fun f : forall c -> (c -> c) ->\n\ + fun (x, y) : (a, b) -> (f@(x), f@(y)) \n\ + in\n\ + let list_length: forall a -> [a] -> Int =\n\ + typfun a -> fun l : [a] ->\n\ + case l\n\ + | [] => 0\n\ + | hd::tl => 1 + list_length@(tl) \n\ + end \n\ + in\n\n\ + # Tests, separated by semicolons #\n\ + test 2 + 2 == 4 end;\n\ + test 3 + 3 == 6 end;\n\ + test 2 + 2 == 5 end;\n\n\ + # The value of the program is shown at the bottom # \n\ + 2 + 2"; + } ); + ( "Projectors", + { + zipper = + "((selection((focus Left)(content())(mode \ + Normal)))(backpack())(relatives((siblings(()((Secondary((id \ + c3fe923c-f1b5-4fe4-91f3-1920083a48fd)(content(Comment\"# \ + PROJECTORS #\"))))(Secondary((id \ + 82e9ab71-8f1a-473b-8719-bca4ac1abb73)(content(Whitespace\"\\n\"))))(Secondary((id \ + c2aeea8b-6a4b-41c8-ae37-6957844cc632)(content(Whitespace\"\\n\"))))(Secondary((id \ + 5083b6d7-9860-44f2-a372-a7982bac5411)(content(Comment\"# Some \ + kinds of syntax have dedicated GUIs. \ + #\"))))(Secondary((id \ + 685340fd-64fc-47d0-9478-1146c2a75fd0)(content(Whitespace\"\\n\"))))(Secondary((id \ + 95a769cb-ccc7-4050-be14-6c316a60273f)(content(Comment\"# The \ + menu at the bottom left shows which GUIs \ + #\"))))(Secondary((id \ + 1912ca64-3e07-4dcb-9ca7-7d2134c7cf8a)(content(Whitespace\"\\n\"))))(Secondary((id \ + fcbdfc8d-3d9d-4a71-a6ea-7651147d365f)(content(Comment\"# (if \ + any) are applicable to the current term \ + #\"))))(Secondary((id \ + d7774693-9d72-4d87-8f4e-b43c785f4251)(content(Whitespace\"\\n\"))))(Secondary((id \ + 7a231164-a872-4d26-8184-823adee3e3d7)(content(Comment\"# \ + indicated by the caret. \ + #\"))))(Secondary((id \ + 013fc5f7-e8d4-48f7-bcbe-9429f55e4fb2)(content(Whitespace\"\\n\"))))(Secondary((id \ + e72ec872-a3c5-4cd3-ad82-c792dcb3c8b8)(content(Whitespace\"\\n\"))))(Secondary((id \ + 13ee2a51-1c77-428b-a88a-86c662cf961c)(content(Comment\"# Fold \ + projectors cover terms with abstractions. \ + #\"))))(Secondary((id \ + c3f89d08-bdef-4590-be4f-3072c9bd534a)(content(Whitespace\"\\n\"))))(Secondary((id \ + 77d14b50-f736-4c3f-af1c-e0ada25aaadf)(content(Comment\"# 1. A \ + simple fold roles up any term, replacing \ + #\"))))(Secondary((id \ + de94238a-f9da-4725-a7cd-8c262def9569)(content(Whitespace\"\\n\"))))(Secondary((id \ + 1f4aecb5-7b1d-4516-9689-86d55a50eca8)(content(Comment\"# \ + it with ... until it is expanded again. \ + #\"))))(Secondary((id \ + 943b3a44-589d-4acb-9ec9-a4335a102c65)(content(Whitespace\"\\n\"))))(Secondary((id \ + 0064f32d-87a1-4d3c-8ca7-2d986a42811c)(content(Whitespace\"\\n\"))))(Tile((id \ + b3a3bfee-bcdb-438f-ad33-e3f7e336b3ea)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + e992a23f-ce0a-4e05-a49a-09e84388f1d2)(content(Whitespace\" \ + \"))))(Tile((id \ + d776d3ac-ddeb-4cdc-9bb8-3c3b487840be)(label(fold))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ + 8e21014a-816f-4572-b065-34a5a04dc6f9)(content(Whitespace\" \ + \")))))((Secondary((id \ + d983dc5b-b4b8-46e8-ab8a-a6c5297ce98b)(content(Whitespace\" \ + \"))))(Projector((id \ + 3d5d8571-e287-4660-889d-019fd826d793)(kind \ + Fold)(syntax(Tile((id \ + 3d5d8571-e287-4660-889d-019fd826d793)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ + 9403eac8-9e96-4c73-84ab-ff94fbcb1864)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ + 81926204-d883-4cc9-ae43-6ccc4ab42857)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ + 2cfeb841-d069-4aa6-9ad8-931ef62214bc)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ + 0b6d67f7-b22c-402e-9fe8-9fa10c54adf2)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ + 25ec067f-2025-45f2-bc61-5e1839184086)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ + e0716c75-b708-491e-9844-48d0424e6545)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ + 6057d41b-727d-4f1d-91b4-4f78e45607a2)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ + 33e14eaf-32e1-490d-b554-574e60d7a8ea)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ + 9ff9a3be-2da6-427c-a42d-0b8f699e4de0)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ + a6bb2777-ba78-455a-a252-dcc8f6ac664c)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ + 7269fe06-4f65-439c-a289-dfcdcc6d230a)(label(\"()\"))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children())))))))))))))))))))))))))))))))))))))))))))))))))))))))))))(model\"()\")))(Secondary((id \ + 695e3712-f2c0-4fb1-98c8-5c4dae7bef90)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + 0746c10c-3faa-4fca-875f-34dacf07e128)(content(Whitespace\"\\n\"))))(Secondary((id \ + 0116db5a-a7b9-4a59-8f20-bde869ae5cbf)(content(Whitespace\"\\n\"))))(Secondary((id \ + 22e07ba4-9f84-47c8-ac0e-3cbf64f8a41a)(content(Comment\"# 2. A \ + semantic fold covers a term with a property: \ + #\"))))(Secondary((id \ + 2324126a-fd02-4d46-8dca-f54ecc1f3c53)(content(Whitespace\"\\n\"))))(Secondary((id \ + 3246672d-f43f-48d7-aff8-14b4179ace2a)(content(Comment\"# \ + Click to toggle inferred & synthesized types \ + #\"))))(Secondary((id \ + 83092344-09b3-4027-b669-02cd44e7e379)(content(Whitespace\"\\n\"))))(Secondary((id \ + c2c02009-b47d-4948-8679-da0ed059a6d2)(content(Whitespace\"\\n\"))))(Tile((id \ + 844dec42-9f30-4750-ac38-a51b56142ee3)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + 7bb8fe9e-04a0-4ee7-9d36-4a31dfd14c05)(content(Whitespace\" \ + \"))))(Tile((id \ + 1865a79f-c653-44f5-8081-ce2c140f2d80)(label(folds))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Tile((id \ + e819a137-478c-4ba7-9085-f4cbc8335c7d)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ + Typ))))))(shards(0))(children())))(Secondary((id \ + d67fb96f-9d3f-4488-b4d9-2a59566cc091)(content(Whitespace\" \ + \"))))(Projector((id \ + 68602b6d-43bb-402b-9a24-bf990bf1c22c)(kind \ + Fold)(syntax(Tile((id \ + 68602b6d-43bb-402b-9a24-bf990bf1c22c)(label(\"(\"\")\"))(mold((out \ + Typ)(in_(Typ))(nibs(((shape Convex)(sort Typ))((shape \ + Convex)(sort Typ))))))(shards(0 1))(children(((Tile((id \ + d4f45557-5d33-4376-aacb-21c1e9a1f0b4)(label(Int))(mold((out \ + Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ + Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ + ec4942d0-661e-4086-8ca7-8b076abb5813)(content(Whitespace\" \ + \"))))(Tile((id \ + 1ec7773a-82e6-4fae-aa59-4762e198c98a)(label(->))(mold((out \ + Typ)(in_())(nibs(((shape(Concave 6))(sort \ + Typ))((shape(Concave 6))(sort \ + Typ))))))(shards(0))(children())))(Secondary((id \ + a89b1307-c340-4055-9a7a-17d319ac6fcd)(content(Whitespace\" \ + \"))))(Tile((id \ + 54bf5314-84f6-4701-bc2a-008fc9485ee2)(label(Bool))(mold((out \ + Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ + Convex)(sort \ + Typ))))))(shards(0))(children())))))))))(model\"()\")))(Secondary((id \ + c3061b0b-9b43-4426-b14f-2f08c245f300)(content(Whitespace\" \ + \")))))((Secondary((id \ + e614e364-e221-402f-8556-50e8caf3b940)(content(Whitespace\" \ + \"))))(Projector((id \ + 2b8a4030-bf70-47b6-8546-4cbe256e5cae)(kind \ + Info)(syntax(Grout((id \ + 2b8a4030-bf70-47b6-8546-4cbe256e5cae)(shape Convex))))(model \ + Expected)))(Secondary((id \ + b6c9f4cd-120e-471a-8874-24b43aab5df9)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + df00c631-b6c1-42ba-b179-22bfbe078fcd)(content(Whitespace\"\\n\"))))(Secondary((id \ + eb6977fb-0298-4bd6-8106-515bf6274105)(content(Whitespace\"\\n\"))))(Secondary((id \ + a46616c8-f52b-4755-9bf1-e1a324298a9a)(content(Comment\"# \ + Projectors on literal data are called livelits. \ + #\"))))(Secondary((id \ + c507ba49-0c28-49ba-ab08-be00b86f7cfe)(content(Whitespace\"\\n\"))))(Secondary((id \ + 7c56f9a4-5c09-4a53-952d-9261a9f17ec8)(content(Comment\"# \ + Three base types literals use inline views: \ + #\"))))(Secondary((id \ + 5bd865da-3375-478d-9b93-1d4861cb6a22)(content(Whitespace\"\\n\"))))(Secondary((id \ + a58a0cc6-4614-440c-8093-c54b3d3b19c2)(content(Whitespace\"\\n\"))))(Tile((id \ + c2ab8eb6-631f-4976-a9bb-cc92eca07f78)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + 6d0b5f74-5e96-4be7-847d-05afbe3955ab)(content(Whitespace\" \ + \"))))(Tile((id \ + 7fd412a0-6516-4d01-bb44-c735d79b4a4b)(label(guard))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Tile((id \ + 5c956f02-69a9-4dd7-882a-48e8e73f874e)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ + Typ))))))(shards(0))(children())))(Secondary((id \ + 9e02c123-880b-4f88-9675-501fcc7f2ed2)(content(Whitespace\" \ + \"))))(Tile((id \ + 0d782687-5bf4-4317-8e23-22bf7f91758e)(label(Bool))(mold((out \ + Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ + Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ + ef93835e-4a99-4b7c-824d-b51cf70ddd60)(content(Whitespace\" \ + \")))))((Secondary((id \ + 13722973-e012-4c13-b9bb-aa8d9a1de6b8)(content(Whitespace\" \ + \"))))(Projector((id \ + efd30209-5976-4ccc-835c-3ea6ae1ab13b)(kind \ + Checkbox)(syntax(Tile((id \ + efd30209-5976-4ccc-835c-3ea6ae1ab13b)(label(true))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))(model\"()\")))(Secondary((id \ + e5b36263-d7e9-4927-be88-7d4d9c2924b6)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + d24bac73-2ba2-4b2f-853e-50c123946a33)(content(Whitespace\"\\n\"))))(Tile((id \ + 4892097f-1fd3-4a33-abcf-ac4c55757fa6)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + 034b65f9-e9a1-4aa0-9626-b600062d3c11)(content(Whitespace\" \ + \"))))(Tile((id \ + 112fc7f9-ce6e-41d2-9774-4722ef92bd06)(label(phase))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Tile((id \ + 3ec69819-dc39-4266-ba08-a08fb08718e7)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ + Typ))))))(shards(0))(children())))(Secondary((id \ + 6842035c-1e3f-48a6-b922-78b770510221)(content(Whitespace\" \ + \"))))(Tile((id \ + 2234dc42-947d-48bd-bae1-b8ce61de2020)(label(Int))(mold((out \ + Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ + Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ + 8e8e1227-03c6-466d-ae1c-1784bbe5ba33)(content(Whitespace\" \ + \")))))((Secondary((id \ + ffc5eb91-0f98-4587-a956-f55e0115fcfa)(content(Whitespace\" \ + \"))))(Projector((id \ + 2b03a748-4f50-474d-adae-814785dc3692)(kind \ + Slider)(syntax(Tile((id \ + 2b03a748-4f50-474d-adae-814785dc3692)(label(44))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))(model\"()\")))(Secondary((id \ + e14500bd-7737-41f9-af43-3e06b6d9d3fd)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + 0d9164c7-2310-4ce0-8e74-d22008f2984d)(content(Whitespace\"\\n\"))))(Tile((id \ + cbcc44ec-1ab4-43a8-bd41-1e76afcaa012)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + 7d7b5b27-6af3-4ca1-96f2-c1073ead531d)(content(Whitespace\" \ + \"))))(Tile((id \ + a42f4aad-ae62-4024-b157-f44502f3f96c)(label(float))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Tile((id \ + 9d656f04-dd32-4594-8b63-a579f2774e9c)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ + Typ))))))(shards(0))(children())))(Secondary((id \ + 81a8b0cc-0433-4234-938f-f6d16e0cf314)(content(Whitespace\" \ + \"))))(Tile((id \ + b9066610-92a5-42df-97be-b261927b7e0e)(label(Float))(mold((out \ + Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ + Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ + eff1cce3-2d0f-4d2c-9d12-a4a4763c6c7f)(content(Whitespace\" \ + \")))))((Secondary((id \ + f1df0e58-a7f3-4494-812d-a558c96c0c63)(content(Whitespace\" \ + \"))))(Projector((id \ + 043196ac-dc43-489c-85e8-4bf31d6853c7)(kind \ + SliderF)(syntax(Tile((id \ + 043196ac-dc43-489c-85e8-4bf31d6853c7)(label(79.00))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))(model\"()\")))(Secondary((id \ + d2618e65-e9a8-46c1-b5c4-4d6ee1b25a77)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + 47e6a486-67d1-4b89-b005-1aad616e4012)(content(Whitespace\"\\n\"))))(Secondary((id \ + 0ea2f253-0d49-49f7-88fd-e2775aedbab4)(content(Whitespace\"\\n\"))))(Secondary((id \ + d2a60e8e-a397-4fde-9b3d-8de7d44c435b)(content(Comment\"# \ + Inline error decorations (same as for tokens) \ + #\"))))(Secondary((id \ + 89c3bf87-33f1-4bd8-84ac-794962a1b06f)(content(Whitespace\"\\n\"))))(Secondary((id \ + a2b7b074-9f8b-401d-8277-433283b3dd3d)(content(Whitespace\"\\n\"))))(Tile((id \ + 5c88bf9f-3a1c-494b-b9b6-ab25e9f8c748)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + ba3c4c94-a6d3-4e67-8f8c-fe1ef283e42a)(content(Whitespace\" \ + \"))))(Tile((id \ + be3365c0-8223-46e9-bf78-1355cb4b9963)(label(\"(\"\")\"))(mold((out \ + Pat)(in_(Pat))(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0 1))(children(((Tile((id \ + 2528ecd7-2bca-4088-8642-07347f97dfe6)(label(a))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Tile((id \ + 0d999b5a-f816-4d8d-93ac-31800d93edac)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ + Typ))))))(shards(0))(children())))(Tile((id \ + 3f3703f7-333f-4e29-b21c-377af36cca38)(label(Int))(mold((out \ + Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ + Convex)(sort Typ))))))(shards(0))(children())))(Tile((id \ + d99b5782-c227-4008-9446-c36b0c1b98c9)(label(,))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 15))(sort \ + Pat))((shape(Concave 15))(sort \ + Pat))))))(shards(0))(children())))(Secondary((id \ + 046a4766-e8ec-41f2-b458-01129c599528)(content(Whitespace\" \ + \"))))(Tile((id \ + 58292f14-1e4c-4936-93fe-6780f53b9b48)(label(f))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Tile((id \ + b2844336-ccf3-4198-856e-10181c19b357)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ + Typ))))))(shards(0))(children())))(Secondary((id \ + 6ed09a11-ecba-4d05-9ee6-3aa7ddbe7195)(content(Whitespace\" \ + \"))))(Tile((id \ + 8342017f-290a-410a-abeb-99cb7f7c2e12)(label(Float))(mold((out \ + Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ + Convex)(sort \ + Typ))))))(shards(0))(children()))))))))(Secondary((id \ + a0c9eae6-7599-4723-9a73-8739578452dd)(content(Whitespace\" \ + \")))))((Secondary((id \ + 520a0dab-48a7-4998-af8a-42121ea7c03b)(content(Whitespace\" \ + \"))))(Projector((id \ + 73403eff-1a14-4a95-aa97-08847365f7f7)(kind \ + Checkbox)(syntax(Tile((id \ + 73403eff-1a14-4a95-aa97-08847365f7f7)(label(true))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))(model\"()\")))(Tile((id \ + f2ebe0f4-7569-4327-a816-302a359154dd)(label(,))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 15))(sort \ + Exp))((shape(Concave 15))(sort \ + Exp))))))(shards(0))(children())))(Secondary((id \ + e22631a3-3621-4bc7-8df0-034c3dd83ef0)(content(Whitespace\" \ + \"))))(Projector((id \ + 1b9c2559-9fa5-45e0-8136-45cf1ba5a153)(kind \ + Slider)(syntax(Tile((id \ + 1b9c2559-9fa5-45e0-8136-45cf1ba5a153)(label(28))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))(model\"()\")))(Secondary((id \ + d9c1a18b-7ece-4b06-923d-5f41364ee432)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + 5a1ba563-db2a-4084-947e-9086b6e75501)(content(Whitespace\"\\n\"))))(Secondary((id \ + d1e25e85-434f-40d9-b8c8-41ed2e3b5928)(content(Whitespace\"\\n\"))))(Secondary((id \ + 32f12f1f-4721-4be5-9864-b8a852649666)(content(Comment\"# The \ + String base type get a multiline view: #\"))))(Secondary((id \ + b4568a57-45a5-4058-b04c-17693cad93bc)(content(Whitespace\"\\n\"))))(Secondary((id \ + 34e3a828-278f-4b76-9794-a02b9f40ed6e)(content(Whitespace\"\\n\"))))(Tile((id \ + 4757c00d-9783-4b47-806b-872b9728e17c)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + 25de0cd1-e0cd-40e2-b298-bba63463e402)(content(Whitespace\" \ + \"))))(Tile((id \ + 007595ce-99f5-4d6b-bc0d-157c343ee846)(label(_))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ + 15c0db9c-4ffc-4a65-85bf-1f7663ffb7a6)(content(Whitespace\" \ + \")))))((Secondary((id \ + 7b655a09-dea7-489f-8c63-4bae6cf1ddb5)(content(Whitespace\" \ + \"))))(Projector((id \ + 56d4b3d2-48ae-485f-ac8f-4465bb35110f)(kind \ + TextArea)(syntax(Tile((id \ + 56d4b3d2-48ae-485f-ac8f-4465bb35110f)(label(\"\\\"\\\"\"))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))(model\"()\")))(Secondary((id \ + 39c7d0a1-2b1c-434e-969e-f3a8d480b98c)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + 5c35b6c4-e575-4907-975b-94ca40431ea4)(content(Whitespace\"\\n\"))))(Tile((id \ + cce56473-5258-4c91-8036-41fdfa6ba6b1)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + 85a1dc46-86fb-4585-aac0-3281491cd83d)(content(Whitespace\" \ + \"))))(Tile((id \ + 5b032c7b-bcb3-4af2-951e-40f7691af336)(label(__))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ + 86e081ce-920e-4f89-8ef3-0c54d43d6693)(content(Whitespace\" \ + \")))))((Secondary((id \ + 2d5a8239-42f4-4bc0-ae3c-ee19a920124f)(content(Whitespace\" \ + \"))))(Projector((id \ + f0c0f5d9-251b-4e16-a0b9-0ea8cd416b67)(kind \ + TextArea)(syntax(Tile((id \ + f0c0f5d9-251b-4e16-a0b9-0ea8cd416b67)(label(\"\\\"\\\\n\\\"\"))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))(model\"()\")))(Secondary((id \ + 66e6258f-a354-4df0-950a-5416915fbb9c)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + 2fe9926a-316d-44ce-b729-6cb5031c1e95)(content(Whitespace\"\\n\"))))(Tile((id \ + 95aeb505-339e-4761-bce3-1f39778bb748)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + ada7f019-d3d4-4b7b-8755-e26aa8256731)(content(Whitespace\" \ + \"))))(Tile((id \ + 4c1360b2-dafe-422e-b3b6-b96ec36e7ac8)(label(___))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ + 0d894ba4-cf26-403f-9a23-267609fe46f4)(content(Whitespace\" \ + \")))))((Secondary((id \ + 9d4ceb1c-6b22-4a06-a218-633b4a5890dc)(content(Whitespace\" \ + \"))))(Projector((id \ + e7f57a83-ecba-45f4-b7c3-e576c0452edf)(kind \ + TextArea)(syntax(Tile((id \ + e7f57a83-ecba-45f4-b7c3-e576c0452edf)(label(\"\\\"a\\\"\"))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))(model\"()\")))(Secondary((id \ + ed6e4e97-cda5-4f4a-b917-01a2e251030f)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + c0e84d18-89a3-456e-ae6f-853eac5c6e24)(content(Whitespace\"\\n\"))))(Tile((id \ + 0e2a557d-8235-4160-ba5a-137b96581ee7)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + d174d025-b139-4cec-94b8-bf1739822683)(content(Whitespace\" \ + \"))))(Tile((id \ + 51b2e64d-97dd-4136-a322-9567742961c7)(label(____))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ + 5975f35a-5be5-487c-9c60-684e8196ee5e)(content(Whitespace\" \ + \")))))((Secondary((id \ + 655b0f6d-81ea-4402-b279-6b1ae84beba4)(content(Whitespace\" \ + \"))))(Projector((id \ + aed58904-b2f8-4101-8472-45e7f1f12683)(kind \ + TextArea)(syntax(Tile((id \ + aed58904-b2f8-4101-8472-45e7f1f12683)(label(\"\\\"shift\\\\n\\\"\"))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))(model\"()\")))(Secondary((id \ + 437dcb66-6719-46ca-9822-d869d8e8360c)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + 4579fb70-9d19-4a24-abd3-5683a11e35c2)(content(Whitespace\"\\n\"))))(Tile((id \ + c182f185-1c46-4fbf-8554-8a31b842934b)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + a256562d-4dd1-4c1f-8b3a-61488ef8203e)(content(Whitespace\" \ + \"))))(Tile((id \ + 73420d3d-60aa-48f3-af7f-9e0271b218f9)(label(_____))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ + 09b22cf6-e566-43df-a6ef-9a2b8cc5b124)(content(Whitespace\" \ + \")))))((Secondary((id \ + fc90fed4-a5d3-4d27-9f7a-cd75421abaee)(content(Whitespace\" \ + \"))))(Projector((id \ + 41dbf9b6-0f60-4ab3-bb0e-a5fdc9512d82)(kind \ + TextArea)(syntax(Tile((id \ + 41dbf9b6-0f60-4ab3-bb0e-a5fdc9512d82)(label(\"\\\"\\\\nmalicious\\\"\"))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))(model\"()\")))(Secondary((id \ + e2d4adfe-b2e5-4e21-a5f0-8f8a1384582c)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + 941557a3-c4d6-4c32-91c9-8e3ea317335e)(content(Whitespace\"\\n\"))))(Tile((id \ + 1eb285f2-a7d4-4cff-a8a9-79fc4bdc3047)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + 92fa5f2d-59f7-4fe5-91d6-a327ba868447)(content(Whitespace\" \ + \"))))(Tile((id \ + e7dd8df0-14df-41f3-8ebb-747d42daf6ce)(label(______))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ + 50a8159f-2f81-4ac8-bb46-c93c6d1c3a36)(content(Whitespace\" \ + \")))))((Secondary((id \ + c8ba0030-44ed-43ff-915f-1fd4afc25529)(content(Whitespace\" \ + \"))))(Projector((id \ + 7d31fa70-e091-4443-89af-6d6380fe31f0)(kind \ + TextArea)(syntax(Tile((id \ + 7d31fa70-e091-4443-89af-6d6380fe31f0)(label(\"\\\"a\\\\n \ + shift\\\\n malicious\\\"\"))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))(model\"()\")))(Secondary((id \ + b30e104e-26d2-48e5-acb1-8b1857c4f7ec)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + 6d752567-c069-4bc2-aa74-ab77e213936e)(content(Whitespace\"\\n\"))))(Secondary((id \ + 71cd9b4c-db26-4ddf-888d-affbc48abbe9)(content(Whitespace\"\\n\"))))(Secondary((id \ + 934e0d04-e4c9-4442-99c1-3ce6a26cc38f)(content(Comment\"# \ + Multiline error decorations #\"))))(Secondary((id \ + 1a2d4d43-52ba-4bc2-a92d-72000df5929c)(content(Whitespace\"\\n\"))))(Secondary((id \ + 62f74d6d-efb5-47a4-9512-79ed238f03ae)(content(Whitespace\"\\n\"))))(Tile((id \ + 28fef6b0-7141-4ca5-a327-811d58ee2058)(label(let = \ + in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + 8edbca7a-12c5-4751-a236-c6c59f036b4c)(content(Whitespace\" \ + \"))))(Tile((id \ + 96dabc0d-1364-4af0-b557-a01c20442170)(label(box))(mold((out \ + Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ + Convex)(sort Pat))))))(shards(0))(children())))(Tile((id \ + 952e73a0-52ca-4a10-8d5f-11fc0f6e25db)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ + Typ))))))(shards(0))(children())))(Secondary((id \ + fcd699c8-85dd-4eaf-98b8-cf8d1749218a)(content(Whitespace\" \ + \"))))(Tile((id \ + 9153ca41-34c1-4033-8ea0-07d786aac3b7)(label(Int))(mold((out \ + Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ + Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ + 663d4b08-149b-4a22-a648-28ee7fbaf563)(content(Whitespace\" \ + \")))))((Secondary((id \ + 98446bd1-f187-49a0-88b6-675489b23464)(content(Whitespace\" \ + \"))))(Projector((id \ + c5d4d591-d15a-4c66-88f0-7a88f3a6ce78)(kind \ + TextArea)(syntax(Tile((id \ + c5d4d591-d15a-4c66-88f0-7a88f3a6ce78)(label(\"\\\"\\\\nmalicious\\\"\"))(mold((out \ + Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ + Convex)(sort \ + Exp))))))(shards(0))(children()))))(model\"()\")))(Secondary((id \ + 70a41503-246e-4418-b534-83cdbb15b99f)(content(Whitespace\" \ + \")))))))))(Secondary((id \ + 3696b18f-b1e7-4e15-9dbd-f56d1aa7b8d9)(content(Whitespace\"\\n\"))))(Secondary((id \ + 590c1453-d66d-4f00-a5de-8b3f5260eac6)(content(Whitespace\"\\n\"))))(Secondary((id \ + ef7baae7-4b97-4e0a-a47e-46016f4081e5)(content(Comment\"# \ + ERRATA: \ + #\"))))(Secondary((id \ + 21fb30f2-004b-4a3a-a1dd-3b91cc0b4e8f)(content(Whitespace\"\\n\"))))(Secondary((id \ + ff763ee5-f5a4-4e0f-a850-7b9a91a5d58b)(content(Comment\"# The \ + bottom toggle can also be used to remove \ + #\"))))(Secondary((id \ + 19b420fc-4ede-4dcd-80d5-b81c38f14ad6)(content(Whitespace\"\\n\"))))(Secondary((id \ + b6babb47-898f-4849-9c28-5b743c812dd0)(content(Comment\"# \ + projectors. Currently only bidelmited terms can \ + #\"))))(Secondary((id \ + cefebeb8-fb83-4c6e-a7fa-84a49405466c)(content(Whitespace\"\\n\"))))(Secondary((id \ + bf02836d-ff10-4a96-942a-453c62a31581)(content(Comment\"# \ + projected, so some may have to be parenthesized. \ + #\"))))(Secondary((id \ + bd3e1e37-6d64-4f8b-9ca8-ffbdc7764025)(content(Whitespace\"\\n\"))))(Secondary((id \ + c2918a56-dd9e-4f8a-a4cd-b2b23942beb2)(content(Comment\"# \ + Projectors are persistent across sessions, but \ + #\"))))(Secondary((id \ + 080de242-c6d2-40ca-8fa9-f468ba2a1d38)(content(Whitespace\"\\n\"))))(Secondary((id \ + 774c7448-85eb-4a6a-a386-85d9b22afaf3)(content(Comment\"# \ + currently are lost on cut/copy. Both these \ + #\"))))(Secondary((id \ + 76a6c462-75ad-4993-b3df-7edb908e4ce7)(content(Whitespace\"\\n\"))))(Secondary((id \ + 1fd463eb-40fa-45a3-a0ef-2914f7eef9dc)(content(Comment\"# \ + restrictions will be removed in a future update. \ + #\"))))(Secondary((id \ + 0f713bb7-d313-4787-984a-a2eaa053543e)(content(Whitespace\"\\n\"))))(Secondary((id \ + e97ef593-1455-45de-836a-da7c5d454188)(content(Whitespace\"\\n\"))))(Secondary((id \ + 756174a2-3850-4d3c-8446-6c258a43a511)(content(Comment\"# \ + Projectors playground #\"))))(Secondary((id \ + b7272053-6d1b-4720-90bd-8d6ec1cebe37)(content(Whitespace\"\\n\"))))(Secondary((id \ + f30d8335-627f-4c75-80ee-5e4cd5fd8f03)(content(Whitespace\"\\n\"))))(Tile((id \ + 03bbbeb6-15ad-4496-8d90-07207ebe0b32)(label(if then \ + else))(mold((out Exp)(in_(Exp Exp))(nibs(((shape Convex)(sort \ + Exp))((shape(Concave 13))(sort Exp))))))(shards(0 1 \ + 2))(children(((Secondary((id \ + ffc0838c-d5c7-41c9-b38a-0a7a7b9e9d22)(content(Whitespace\" \ + \"))))(Projector((id \ + ab0e5a46-5dc9-41fc-a3eb-fa7092c96743)(kind \ + Checkbox)(syntax(Tile((id \ + ab0e5a46-5dc9-41fc-a3eb-fa7092c96743)(label(true))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ - 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"# Hazel Language Quick Reference #\n\n\ - # Empty holes stand for missing expressions, patterns, or \ - types #\n\ - let empty_hole = in\n\n\ - # Integers #\n\ - let int_lits : Int = 1 in\n\ - let negation = -1 in\n\ - let arithmetic = 1*2 + 8/4 in\n\ - let int_comparison = (10 == 10, 1 < 2, 2 <= 3, 3 > 2, 2 >= 1) \ - in\n\n\ - # Floating Point Numbers #\n\ - let float_lits : Float = 1.5 in\n\ - let float_artih = 1. *. 2. +. 8. /. 4. in\n\ - let float_comparison = (10. ==.10., 1. <.2., 2. <=.3., 3. \ - >.2., 2. >=.1.) in\n\n\ - # Booleans #\n\ - let booleans : (Bool, Bool) = (true, false) in\n\ - let conditionals =\n\ - let (x, y) = (2 + 2, 3 + 3) in\n\ - if y > x then 1\n\ - else 2\n\ - in\n\n\ - # Tuples #\n\ - let tuples : (Int, Bool, (Bool, Int)) = (1, true, (false, 3)) \ - in\n\ - let (a, b, (c, d)) = tuples in\n\n\ - # Functions #\n\ - let y : (Int, Int, Int) -> Int =\n\ - fun (m, x, b) -> m * x + b\n\ - in\n\n\ - # Recursive Functions (arrow type annotation required) #\n\ - let double_recursively : Int -> Int =\n\ - fun n ->\n\ - if n == 0 then 0\n\ - else double_recursively(n - 1) + 2\n\ - in\n\n\ - # Mutual Recursion (bind tuples of functions) #\n\ - let (even : Int -> Bool, odd : Int -> Bool) = \n\ - (fun n -> if n == 0 then true else odd(n - 1), \n\ - fun n -> if n == 0 then false else even(n - 1)) in \n\n\ - # Lists #\n\ - let empty_list : [Int] = [] in\n\ - let non_empty_list : [Int] = 1::2::3::[] in\n\ - let list_literals : [Int] = [1, 2, 3] in\n\ - let length : [Int] -> Int =\n\ - fun xs ->\n\ - case xs\n\ - | [] => 0\n\ - | hd::tl => 1 + length(tl) \n\ - end\n\ - in\n\ - let has_at_least_two_elements : [Int] -> Bool =\n\ - fun xs ->\n\ - case xs\n\ - | [] => false\n\ - | hd::[] => false\n\ - | a::b::[] => true \n\ - end\n\ - in\n\n\ - # Polymorphic Functions #\n\ - let poly_id : forall a -> a -> a =\n\ - typfun a -> fun x : a -> x\n\ - in\n\ - let apply_both : forall a -> forall b ->\n\ - (forall c -> c -> c) -> ((a, b) -> (a, b)) =\n\ - typfun a -> typfun b -> fun f : forall c -> (c -> c) ->\n\ - fun (x, y) : (a, b) -> (f@(x), f@(y))\n\ - in\n\ - let list_length : forall a -> [a] -> Int =\n\ - typfun a -> fun l : [a] ->\n\ - case l\n\ - | [] => 0\n\ - | hd::tl => 1 + list_length@(tl)\n\ - end\n\ - in\n\n\ - # Strings #\n\ - let string_lits = \"Hello, world!\" in \n\ - let string_equality = string_lits $== \"Hello, world!\" in \n\n\ - # Non-empty holes are the red dotted boxes around errors #\n\ - # (you can still run programs with non-empty holes) #\n\ - let non_empty_hole : Int = true in \n\n\ - # Tests, separated by semicolons #\n\ - test 2 + 2 == 4 end;\n\ - test 3 + 3 == 6 end;\n\ - test 2 + 2 == 5 end;\n\n\ - 2 + 2"; + "# PROJECTORS #\n\n\ + # Some kinds of syntax have dedicated GUIs. #\n\ + # The menu at the bottom left shows which GUIs #\n\ + # (if any) are applicable to the current term #\n\ + # indicated by the caret. #\n\n\ + # Fold projectors cover terms with abstractions. #\n\ + # 1. A simple fold roles up any term, replacing #\n\ + # it with ... until it is expanded again. #\n\n\ + let fold = in\n\n\ + # 2. A semantic fold covers a term with a property: #\n\ + # Click to toggle inferred & synthesized types #\n\n\ + let folds: = in\n\n\ + # Projectors on literal data are called livelits. #\n\ + # Three base types literals use inline views: #\n\n\ + let guard: Bool = in\n\ + let phase: Int = in\n\ + let float: Float = in\n\n\ + # Inline error decorations (same as for tokens) #\n\n\ + let (a:Int, f: Float) = , in\n\n\ + # The String base type get a multiline view: #\n\n\ + let _ = in\n\ + let __ = in\n\ + let ___ = in\n\ + let ____ = in\n\ + let _____ = in\n\ + let ______ = in\n\n\ + # Multiline error decorations #\n\n\ + let box: Int = in\n\n\ + # ERRATA: #\n\ + # The bottom toggle can also be used to remove #\n\ + # projectors. Currently only bidelmited terms can #\n\ + # projected, so some may have to be parenthesized. #\n\ + # Projectors are persistent across sessions, but #\n\ + # currently are lost on cut/copy. Both these #\n\ + # restrictions will be removed in a future update. #\n\n\ + # Projectors playground #\n\n\ + if && < () \n\ + then ______ else \"its: \" ++ box"; } ); ( "Types & static errors", { zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Secondary((id \ - c2890a35-b3f1-4653-9767-8d5f9752ead5)(content(Comment\"# \ + 5da92fc0-10cd-4354-bf0b-1a22accca803)(content(Comment\"# \ Internal Regression Tests: Type errors #\"))))(Secondary((id \ - 090c5ddf-5c26-4a14-a1b9-eab92cb073c4)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 5a4d6644-ce5b-4818-a4c6-2905ca7b9d43)(content(Comment\"# Each \ + 42a2f89c-4a95-4199-8800-f53809f593ba)(content(Whitespace\"\\n\"))))(Secondary((id \ + e86dd07c-7157-40bc-bdaf-59d06e0034c9)(content(Comment\"# Each \ line should show errors or not as indicated \ #\"))))(Secondary((id \ - 49670809-d955-4be4-8de7-a13e0c26ec98)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 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6))(sort \ - Exp))((shape(Concave 6))(sort \ + 1fe29849-3433-4740-997d-668eef8d71bc)(label(::))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 7))(sort \ + Exp))((shape(Concave 7))(sort \ Exp))))))(shards(0))(children())))(Tile((id \ - 6aa18463-de32-445c-8338-c11780d4d4d0)(label([ ]))(mold((out \ + fddd3561-51a2-491a-97e0-6893154e3b03)(label([ ]))(mold((out \ Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - 4a870256-b389-4bbb-95bd-47834fae994b)(label(2))(mold((out \ + 7a30df1d-81b1-46fd-8c4a-bfdfaf7539fc)(label(2))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort \ Exp))))))(shards(0))(children()))))))))(Secondary((id \ - 369ea7b7-0d09-42c6-8b54-6cb084d8270f)(content(Whitespace\" \ + d9a4e603-08c1-48ed-b113-0009ac910bfd)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 5c3c92c6-a066-49fb-ba63-589c5b309625)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 6dbcf6a1-4176-46e9-802a-b16c71d040ab)(label(let = \ + a4f64779-84df-4eff-ad25-7229fc9add4e)(content(Whitespace\"\\n\"))))(Tile((id \ + 2eaa6225-8b50-4fac-af7c-cdf6ac0f02a6)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 16))(sort Exp))))))(shards(0 1 \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - 9ef098ad-fe36-44f2-9487-6d9ff6656d48)(content(Whitespace\" \ + 5f0766be-60e9-482f-8a6e-6a64ce842de5)(content(Whitespace\" \ \"))))(Tile((id \ - 1d8fcf7b-fa79-4de7-a9f4-55fff3ada3bc)(label(_))(mold((out \ + 6c0df814-7020-470c-97cc-0f341aca78f3)(label(_))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Tile((id \ - cca7629b-c4d5-4045-a00e-197b16dffc60)(label(:))(mold((out \ - Pat)(in_())(nibs(((shape(Concave 11))(sort \ - Pat))((shape(Concave 11))(sort \ + fad6a5cb-f485-4b9f-82a3-b8320e4fa334)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ Typ))))))(shards(0))(children())))(Secondary((id \ - 7eaffe3b-5b20-4937-a693-400f5a3d7987)(content(Whitespace\" \ - \"))))(Tile((id d1ce8a09-d6e6-443e-8fb6-77904043ba41)(label([ \ + 492524db-e03a-4c8d-9a86-b26f60766009)(content(Whitespace\" \ + \"))))(Tile((id 115fad2d-7365-4eb3-a443-de1405399eb7)(label([ \ ]))(mold((out Typ)(in_(Typ))(nibs(((shape Convex)(sort \ Typ))((shape Convex)(sort Typ))))))(shards(0 \ 1))(children(((Tile((id \ - f2827f6e-aef6-40eb-9e99-959cbeb8f626)(label(Int))(mold((out \ + 6f8c6706-b54f-4238-a10a-ff9cf1665bef)(label(Int))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort \ Typ))))))(shards(0))(children()))))))))(Secondary((id \ - a5a96d03-071f-4595-bb82-1f287d604bb3)(content(Whitespace\" \ + a3a40f71-1c95-4f85-96a2-fe2a8f17114f)(content(Whitespace\" \ \")))))((Secondary((id \ - aa9f6dd4-afc8-432f-9060-c140c31c2b5b)(content(Whitespace\" \ + b3ee84c6-5986-4301-8114-32bf685a1d09)(content(Whitespace\" \ \"))))(Tile((id \ - 9c1620d9-ae11-41e1-ad5e-663b10aa1c56)(label(1.0))(mold((out \ + 474aa01d-ec29-4809-9449-d6bdcf751a01)(label(1.0))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 4c545fe6-4860-489f-aaed-de76ee3722c2)(label(::))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 6))(sort \ - Exp))((shape(Concave 6))(sort \ + bf89fc82-3456-464c-8b15-538542e3e74d)(label(::))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 7))(sort \ + Exp))((shape(Concave 7))(sort \ Exp))))))(shards(0))(children())))(Tile((id \ - 90f05b86-6ed6-4da8-a1da-5bc842610088)(label([ ]))(mold((out \ + 9af9f47e-fb39-487c-b81b-d7595b7ed4ec)(label([ ]))(mold((out \ Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - 357ac56b-6008-46c3-823c-f71e965f9072)(label(2))(mold((out \ + d174f6ac-82a8-4e02-a620-0c5f4d69469f)(label(2))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort \ Exp))))))(shards(0))(children()))))))))(Secondary((id \ - ef444fb8-d541-400d-9576-a500ff7bea51)(content(Whitespace\" \ + d077972b-d5d8-4f44-9782-2eadffb6362f)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 125ff66a-6b89-4566-98fd-2a802fd970b5)(content(Whitespace\" \ + 8b3b7181-bdce-48f7-a421-444869d6724f)(content(Whitespace\" \ \"))))(Secondary((id \ - 5939a641-eb88-4f4f-a322-69b1571271b5)(content(Comment \ + 7fe3f81a-c96a-4136-930e-308dbe1b388a)(content(Comment \ #err#))))(Secondary((id \ - 7baecabf-72e3-4455-9cfb-16777b0057ac)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - bd06e95c-6b0f-4708-b642-e09aec6b32ef)(label(let = \ + 843fd20e-f889-44d5-9b72-a22c3ff45ac3)(content(Whitespace\"\\n\"))))(Tile((id \ + c332994a-4006-41ad-9b56-aa50ab90e60d)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 16))(sort Exp))))))(shards(0 1 \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - bff70791-8893-4e8b-9f92-e0ac69a6e939)(content(Whitespace\" \ + be403d06-669b-481c-9837-90f26e2f9277)(content(Whitespace\" \ \"))))(Tile((id \ - 34216c66-e05e-4f03-91a9-61f892a850f8)(label(_))(mold((out \ + 58666b1c-385c-4fcf-bace-08d280664e93)(label(_))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Tile((id \ - f7733b0c-dd77-44b7-b56e-d0c1a6636b6c)(label(:))(mold((out \ - Pat)(in_())(nibs(((shape(Concave 11))(sort \ - Pat))((shape(Concave 11))(sort \ + 0b67de8b-c914-41d4-aded-0de955e9e96f)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ Typ))))))(shards(0))(children())))(Secondary((id \ - 8f04892c-18d2-404b-9894-3e9aecc981e2)(content(Whitespace\" \ - \"))))(Tile((id b48afdf7-f131-4d9f-b829-0bb01434f348)(label([ \ + 383def64-d2d5-49e7-b908-233f1356abd0)(content(Whitespace\" \ + \"))))(Tile((id 959d1342-a60f-467c-9e6b-736a06e3b167)(label([ \ ]))(mold((out Typ)(in_(Typ))(nibs(((shape Convex)(sort \ Typ))((shape Convex)(sort Typ))))))(shards(0 \ 1))(children(((Tile((id \ - 2546b193-bb89-4e2c-a1e1-c0c3aa775d8a)(label(Int))(mold((out \ + ed75b169-9e3e-4614-b0ab-bd533e3cb14e)(label(Int))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort \ Typ))))))(shards(0))(children()))))))))(Secondary((id \ - 925587ff-8973-457c-853a-0f6c71cd9c4a)(content(Whitespace\" \ + c081f642-8c3e-44c5-ac73-7096709f2140)(content(Whitespace\" \ \")))))((Secondary((id \ - 5ca988e2-330d-4e80-91b9-e9031eba4cef)(content(Whitespace\" \ + 7a586f57-38eb-45d4-b816-acb66c51c1b4)(content(Whitespace\" \ \"))))(Tile((id \ - ed424387-c3f5-4d4e-a276-ae526e114f39)(label(1))(mold((out \ + 9763aeaf-c06f-4b68-a254-a74077d5e931)(label(1))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 41bdc089-5d46-461e-91f0-3c4d5c8c975c)(label(::))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 6))(sort \ - Exp))((shape(Concave 6))(sort \ + c6fb1be3-3c11-4f07-9fde-7dee7f515a86)(label(::))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 7))(sort \ + Exp))((shape(Concave 7))(sort \ Exp))))))(shards(0))(children())))(Tile((id \ - 75eaeaea-6d82-4f4f-8ff2-c3d0163c6017)(label([ ]))(mold((out \ + 4560f41b-0387-4d28-925d-c84471ac0707)(label([ ]))(mold((out \ Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - 4516c234-075e-4464-965c-666a0de1e8cd)(label(2.0))(mold((out \ + 686f2d71-762a-4ab2-aa74-49b68f2c06bf)(label(2.0))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort \ Exp))))))(shards(0))(children()))))))))(Secondary((id \ - cb0e4361-9db0-45cf-9b66-9f1812a87332)(content(Whitespace\" \ + 0be59aeb-1745-4b49-bbb6-8fde7dc8189e)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 1be9f5d9-ceb5-4b89-811d-6975be2757f4)(content(Whitespace\" \ + 863e7f16-0102-446b-b2bf-8b0a77ba6cde)(content(Whitespace\" \ \"))))(Secondary((id \ - 8cd1685f-b46f-4d3e-81e3-632df69a6af7)(content(Comment \ + ae46b032-fb59-479e-84bb-18846b40ac4a)(content(Comment \ #err#))))(Secondary((id \ - 0193a545-1ce2-4a17-94b8-be94999b8a06)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - b5361ea7-4e12-48c1-8444-5e38cbb19a59)(label(\"\\\"BYE\\\"\"))(mold((out \ + a8f1d162-0617-4555-b6cb-a3921504c7fc)(content(Whitespace\"\\n\"))))(Tile((id \ + c50d9505-c1c8-4d29-84d6-fa5b82723196)(label(\"\\\"BYE\\\"\"))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort \ Exp))))))(shards(0))(children()))))))(ancestors())))(caret \ @@ -14049,36 +15183,36 @@ let startup : PersistentData.t = # Each line should show errors or not as indicated #\n\n\ let _ = unbound in #err#\n\ let Undefined = Undefined in # 2x err# \n\ - let true = 2 in #err# \n\n\ - let = if true then 1 else 1. in #err# \n\ + let true = 2 in #2x err# \n\n\ + let ? = if true then 1 else 1. in #err# \n\ let _ = if true then 1 else 1. in #err#\n\ - let _: = if true then 1 else 1. in\n\ + let _: ? = if true then 1 else 1. in\n\ let _: Int = if true then 1 else 1. in #err#\n\ let _: Fake = if true then 1 else true in #err#\n\ let _, _ = if true then 1 else 1. in #2x err#\n\ let _, _ = (if true then 1 else 1.), in #err#\n\ - let _: , _ = (if true then 1 else 1.), in \n\ - let [_] = [(if true then 1 else 1.)] in \n\ - let [_] = (if true then 1 else 1.) in #2x err# \n\n\ - ( )(if true then 1 else 1.);\n\ + let _: ?, _ = (if true then 1 else 1.), in \n\ + let [_] = [(if true then 1 else 1.)] in #2x err#\n\ + let [_] = (if true then 1 else 1.) in #3x err# \n\n\ + (?)(if true then 1 else 1.);\n\ 1(if true then 1 else 1.); #err#\n\ (1)(if true then 1 else 1.); #err#\n\ - (fun -> )(if true then 1 else 1.);\n\ - (fun _ -> )(if true then 1 else 1.);\n\ - (fun _: -> )(if true then 1 else 1.);\n\ - (fun _: Int -> )(if true then 1 else 1.); #err#\n\n\ + (fun ? -> ?)(if true then 1 else 1.);\n\ + (fun _ -> ?)(if true then 1 else 1.);\n\ + (fun _: ? -> ?)(if true then 1 else 1.);\n\ + (fun _: Int -> ?)(if true then 1 else 1.); #err#\n\n\ let _ = fun x -> if true then 1 else 1. in #err#\n\ - let _: = fun x -> if true then 1 else 1. in\n\ - let _: -> = fun x -> if true then 1 else 1. in\n\ - let _: -> Int = fun x -> if true then 1 else 1. in #err#\n\ - let _: -> [ ] = fun x -> if true then 1 else 1. in #2x err#\n\n\ - ( )::[(if true then 1 else 1.)];\n\ + let _: ? = fun x -> if true then 1 else 1. in\n\ + let _: ? -> ? = fun x -> if true then 1 else 1. in\n\ + let _: ? -> Int = fun x -> if true then 1 else 1. in #err#\n\ + let _: ? -> [?] = fun x -> if true then 1 else 1. in #2x err#\n\n\ + (?)::[(if true then 1 else 1.)];\n\ 1::[(if true then 1 else 1.)]; #err#\n\ (1, 1)::[(if true then 1 else 1.)]; #2x err#\n\n\ - let = [1, 1., true] in #err: inconsistent#\n\ + let ? = [1, 1., true] in #err: inconsistent#\n\ let _ = [1, 1., true] in #err: inconsistent#\n\ - let _: = [1, 1., true] in \n\ - let _: [ ] = [1, 1., true] in\n\ + let _: ? = [1, 1., true] in \n\ + let _: [?] = [1, 1., true] in\n\ let _: [Int] = [1, 1., true] in #2x err#\n\n\ let _: [Int] = 1::[2] in\n\ let _: [Int] = 1.0::[2] in #err#\n\ @@ -14090,1728 +15224,1727 @@ let startup : PersistentData.t = zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Secondary((id \ - 1f7bcab0-da00-4299-b43a-3ca1ef8ca2f5)(content(Comment\"# \ + 579a2658-f19d-496b-83bb-3840422b8218)(content(Comment\"# \ Lambda Calculus via evaluation by substitution \ #\"))))(Secondary((id \ - a927feba-9938-45cc-88da-4ca88fbace46)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 59554d6d-5be9-43cb-a4d6-1edf55e3c098)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 41573bf5-78b0-4f95-b6e2-3c4ce9dbd6d5)(content(Comment\"# An \ + 58d3c269-21cb-4b04-839c-d1e745cd6c9a)(content(Whitespace\"\\n\"))))(Secondary((id \ + b3539b17-f970-4b91-a865-6f442db15e21)(content(Whitespace\"\\n\"))))(Secondary((id \ + 53f9307e-6888-4508-86de-8c15c2a0b734)(content(Comment\"# An \ Expression is a variable, function, or application \ #\"))))(Secondary((id \ - 5e7af976-9c1e-4841-847a-70c966af0583)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - a76c3b61-221f-4e94-b8fd-5b45183df229)(label(type = \ + c9014d63-730a-4661-b521-6b44ae002db9)(content(Whitespace\"\\n\"))))(Tile((id \ + 3b6f8f45-d98f-453f-815a-57eaf3789cbd)(label(type = \ in))(mold((out Exp)(in_(TPat Typ))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 16))(sort Exp))))))(shards(0 1 \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - 40bbb356-6987-428c-a8ed-2a6b99066f39)(content(Whitespace\" \ + 904b8eb7-4c19-4abf-8637-740ad6c6186a)(content(Whitespace\" \ \"))))(Tile((id \ - 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76aa3723-c0f2-41a8-a8aa-ec010969619b)(label(,))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 15))(sort \ + Exp))((shape(Concave 15))(sort \ Exp))))))(shards(0))(children())))(Secondary((id \ - 62eb476d-c91c-4c67-bd46-be123833cbdf)(content(Whitespace\" \ + 478ac908-46d2-4e78-8cae-1a803f6de024)(content(Whitespace\" \ \"))))(Tile((id \ - 1ff88e88-1e7c-4117-8cfa-6431b1c60b5e)(label(Var))(mold((out \ + c808791b-791c-4340-94b4-23bcf027103a)(label(Var))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 4e3e4ddd-946c-4afa-ad49-4dc4096d8f9d)(label(\"(\"\")\"))(mold((out \ - Exp)(in_(Exp))(nibs(((shape(Concave 1))(sort Exp))((shape \ + 66ba6264-558c-45bc-9dde-a6f0e0820b6d)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape(Concave 2))(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - e9180871-be73-4a92-a949-010ae5b1a3f8)(label(\"\\\"bro\\\"\"))(mold((out \ + 7df83f37-87bf-4ca7-be5b-76684bd9b70a)(label(\"\\\"bro\\\"\"))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort \ Exp))))))(shards(0))(children())))))))))))))))))))))))(Secondary((id \ - 88a4c943-608e-454a-94ad-7dcc08046493)(content(Whitespace\" \ + ec814595-1e64-49d1-afcf-91e3ff70e2c2)(content(Whitespace\" \ \"))))))))))))(ancestors())))(caret Outer))"; backup_text = "# Lambda Calculus via evaluation by substitution #\n\n\ @@ -15824,9 +16957,9 @@ let startup : PersistentData.t = let exp_equal: (Exp, Exp) -> Bool =\n\ fun es ->\n\ case es\n\ - | Var(x), Var(y) => x $== y\n\ + | Var(x), Var(y) => x$== y\n\ | Lam(x1, e1), Lam(x2, e2) =>\n\ - \ x1 $== x2 && exp_equal(e1, e2)\n\ + \ x1$== x2 && exp_equal(e1, e2)\n\ | Ap(e1, e2), Ap(e3, e4) =>\n\ \ exp_equal(e1, e3) && exp_equal(e2, e4)\n\ | _ => false end in\n\n\ @@ -15835,7 +16968,7 @@ let startup : PersistentData.t = fun v, name, e ->\n\ case e\n\ | Var(n) =>\n\ - \ (if n $== name then v else e)\n\ + \ (if n$== name then v else e)\n\ | Lam(x, body) =>\n\ \ Lam(x, subst(v,name, body))\n\ | Ap(e1,e2) =>\n\ @@ -15843,1620 +16976,1629 @@ let startup : PersistentData.t = # Evaluation can result in either an Exp or an Error #\n\ type Result =\n\ + Error(String)\n\ - + Ok(Exp) \n\ + + Ok(Exp) \n\ in\n\n\ let result_equal: (Result, Result) -> Bool =\n\ fun rs ->\n\ case rs\n\ | Ok(e1), Ok(e2) => exp_equal(e1, e2)\n\ - | Error(e1), Error(e2) => e1 $== e2\n\ + | Error(e1), Error(e2) => e1$== e2\n\ | _ => false end in\n\n\ # Evaluation by substitution #\n\ - let eval: Exp -> Result =\n\ + # Evaluation by substitution #\n\ + let go: Exp -> Result =\n\ fun e ->\n\ case e\n\ | Var(n) => Error(\"Free Variable\")\n\ | Lam(x, body) => Ok(Lam(x, body))\n\ | Ap(e1,e2) =>\n\ - case eval(e1)\n\ + case go(e1)\n\ | Ok(Lam(x, body))=>\n\ - case eval(e2)\n\ + case go(e2)\n\ | Error(err) => Error(err)\n\ - | Ok(arg) => eval(subst(arg, x, body)) end\n\ + | Ok(arg) => go(subst(arg, x, body)) end\n\ | _ => Error(\"Not a Function\") end end in\n\n\ test result_equal(\n\ - eval(Var(\"yo\")),\n\ + go(Var(\"yo\")),\n\ Error(\"Free Variable\")) end;\n\n\ test result_equal(\n\ - eval(Ap(Var(\"no\"), Lam(\"bro\", Var(\"bro\")))),\n\ + go(Ap(Var(\"no\"), Lam(\"bro\", Var(\"bro\")))),\n\ Error(\"Not a Function\")) end;\n\n\ test result_equal(\n\ - eval(Lam(\"yo\", Var(\"yo\"))),\n\ + go(Lam(\"yo\", Var(\"yo\"))),\n\ Ok(Lam(\"yo\", Var(\"yo\")))) end;\n\n\ test result_equal(\n\ - eval(Ap(Lam(\"yo\", Var(\"yo\")), Lam(\"bro\", Var(\"bro\")))),\n\ + go(Ap(Lam(\"yo\", Var(\"yo\")), Lam(\"bro\", Var(\"bro\")))),\n\ Ok(Lam(\"bro\", Var(\"bro\")))) end"; } ); ( "Polymorphism", { zipper = "((selection((focus Left)(content())(mode \ - Normal)))(backpack())(relatives((siblings(((Secondary((id \ - ce06e01f-9b12-4ea1-8549-c5615ca7e52a)(content(Comment\"# \ + Normal)))(backpack())(relatives((siblings(()((Secondary((id \ + f531d966-9656-4cd1-82eb-4a80ce2a0e92)(content(Comment\"# \ Polymorphism #\"))))(Secondary((id \ - 3b3f93ba-ca3c-4c1b-8346-2d68f5504958)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - abf1a875-4891-4386-8c1c-a77ad171a596)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - e8268e68-25db-4119-aaf2-c1e01ab024a0)(content(Comment\"# We \ + 5d4daeae-ecdc-47bb-9992-ce5024c2275a)(content(Whitespace\"\\n\"))))(Secondary((id \ + f0d8f788-9aab-4b69-a3f9-3cd9a1a70a34)(content(Whitespace\"\\n\"))))(Secondary((id \ + cc230dc8-58b5-4cb5-8aa5-0bfbe1177102)(content(Comment\"# We \ can take types as parameters to type functions, \ #\"))))(Secondary((id \ - 70f57795-15c2-4826-b2d4-b1c2414b09fc)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 28bfb176-1ada-450a-9a2e-9ee4f68b9271)(content(Comment\"# and \ + e3ed5d2e-ab27-412f-943e-879e38ac559b)(content(Whitespace\"\\n\"))))(Secondary((id \ + 4c6236c2-fcd4-436a-8b7c-3d43650efc34)(content(Comment\"# and \ use them in annoatations in the body: #\"))))(Secondary((id \ - 6c16f965-ddc2-4208-8161-9d17a4f71e84)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - dbc1d50f-0873-4a56-becd-184560be6a16)(label(let = \ + a619a88d-7e97-42da-86e7-01cf8dae47f1)(content(Whitespace\"\\n\"))))(Tile((id \ + 8fe814f0-7895-4bcf-8682-048682dafad6)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 16))(sort Exp))))))(shards(0 1 \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - 3265ecf6-f14c-4851-87bd-29b1c48ad60d)(content(Whitespace\" \ + 7a2fbf23-0e73-48d9-8acb-c44e9de98ab0)(content(Whitespace\" \ \"))))(Tile((id \ - 2f057ddc-b7b4-4a90-8772-0f54a9e6a0f1)(label(id))(mold((out \ + 09c2d8c4-44bd-46ac-88e1-4b59ac422cd0)(label(id))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ - 9e9a0675-cf88-464e-a5b2-22ec197d871a)(content(Whitespace\" \ + 3e02eb03-cc7e-4bf5-aa55-ad0711844d4f)(content(Whitespace\" \ \")))))((Secondary((id \ - 7c246b01-e879-4704-ab40-1ad600b6a05d)(content(Whitespace\" \ + 74d633aa-7732-4047-942f-27acd258c1f2)(content(Whitespace\" \ \"))))(Tile((id \ - 357bc39e-7763-4d16-856a-30f2fdb89cd2)(label(typfun \ + b26bcb03-3d9a-4c2d-be3f-114342660b72)(label(typfun \ ->))(mold((out Exp)(in_(TPat))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 13))(sort Exp))))))(shards(0 \ + Exp))((shape(Concave 14))(sort Exp))))))(shards(0 \ 1))(children(((Secondary((id \ - f9f6be49-c063-4799-a630-a15c13dc2416)(content(Whitespace\" \ + fed3d945-d2ba-4c7d-882d-fea46a9cfc64)(content(Whitespace\" \ \"))))(Tile((id \ - d45a8f80-0658-42a7-bff7-6bfbf36e910d)(label(A))(mold((out \ + 97a3afb8-5ba2-41ca-ba64-e1a9927ae4d5)(label(A))(mold((out \ TPat)(in_())(nibs(((shape Convex)(sort TPat))((shape \ Convex)(sort \ TPat))))))(shards(0))(children())))(Secondary((id \ - 9f37693a-1d0d-4720-a547-0bde3a0cf043)(content(Whitespace\" \ + fce66ca9-fac6-4fd4-a549-98523b937dac)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 0f5c9f28-98cf-4704-be01-3789b89325ad)(content(Whitespace\" \ + 7229523f-57df-4078-ae8f-537742066b36)(content(Whitespace\" \ \"))))(Tile((id \ - c41ee313-ae0d-46e3-8763-3c0003823bf6)(label(fun \ + f343ddc7-57cf-4625-b9b8-d42e4265375a)(label(fun \ ->))(mold((out Exp)(in_(Pat))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 13))(sort Exp))))))(shards(0 \ + Exp))((shape(Concave 14))(sort Exp))))))(shards(0 \ 1))(children(((Secondary((id \ - 5a50ead3-2382-4702-8edc-82df727a9f98)(content(Whitespace\" \ + e3bf119b-c817-467f-800c-6169bff4819b)(content(Whitespace\" \ \"))))(Tile((id \ - 95012d29-d892-46f6-9d41-9d5b6a1991ea)(label(x))(mold((out \ + 2a54e776-4210-4996-893c-280d9d0544dd)(label(x))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ - 8134e2f9-624a-43ff-9e7e-f4f2fb3c44db)(content(Whitespace\" \ + 1e085266-26a8-4803-bdd9-737e13c30194)(content(Whitespace\" \ \"))))(Tile((id \ - e9602009-d959-44c3-bae1-2fcca11436e0)(label(:))(mold((out \ - Pat)(in_())(nibs(((shape(Concave 11))(sort \ - Pat))((shape(Concave 11))(sort \ + c936896e-5dff-49bf-aa98-11b4ce862761)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ Typ))))))(shards(0))(children())))(Secondary((id \ - d8b777e0-ebea-423b-99cd-6777245529d4)(content(Whitespace\" \ + f6b1032e-1e9e-433e-86ab-456f90af4222)(content(Whitespace\" \ \"))))(Tile((id \ - 1e025399-f3a3-40e9-b623-4269d2b4ee01)(label(A))(mold((out \ + d5a47c6d-d24d-4ef1-a060-606484b965d5)(label(A))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ - 89d852f5-e16c-4b7c-af4b-064b73a7d0b0)(content(Whitespace\" \ + bdcc8870-b74b-4553-977b-757a485b10e5)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 56b281c4-857e-4223-b818-b33e503e6340)(content(Whitespace\" \ + 2072eb8a-d2ee-49a6-b6ec-7cafbbde3033)(content(Whitespace\" \ \"))))(Tile((id \ - fc41c74e-bd60-4cf6-8400-aa6cd0b485d2)(label(x))(mold((out \ + 5dca5191-0403-436d-a497-f652cbad5254)(label(x))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Secondary((id \ - b4b1ea56-6958-44fc-89bd-b6f22e6bade3)(content(Whitespace\" \ + b4cb6907-0c38-4b67-ad96-45b705bfae1a)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 5c77f088-a1f3-4ba8-b7ef-efe73f27f855)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - d7c28f98-90c1-46ca-9827-7fb78625c981)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - a979ad79-2705-4ca1-9cf2-cccfec5e0086)(content(Comment\"# Such \ + 6aff849b-59d0-46a0-b781-8678637e1073)(content(Whitespace\"\\n\"))))(Secondary((id \ + dd8ae2d5-654a-4b51-9417-480b68a56dc1)(content(Whitespace\"\\n\"))))(Secondary((id \ + 8d899bc1-ee49-450e-a084-5ac90ffefc82)(content(Comment\"# Such \ functions are applied like so: #\"))))(Secondary((id \ - 5c84aefa-4652-4c4c-89ff-f05f4da85b58)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 2e888173-4ece-4010-a674-13a32957493e)(label(let = \ + a5a251b0-eeff-4256-9c72-996faea5a498)(content(Whitespace\"\\n\"))))(Tile((id \ + 2a93c2ca-b6ab-4a7a-87b0-839aa512a691)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 16))(sort Exp))))))(shards(0 1 \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - 32c1835b-c27f-4ccf-be61-a270b6e9c5ba)(content(Whitespace\" \ + 9c13bf6a-f462-4648-a65f-2ad55c680536)(content(Whitespace\" \ \"))))(Tile((id \ - 1c2ef7e4-4439-4110-976e-41a1e8ff3d6b)(label(ex1))(mold((out \ + 97c53ee2-470d-4e7d-b812-4d4a69455557)(label(ex1))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ - 859ef193-f93b-4ae5-b070-4731bf77bc97)(content(Whitespace\" \ + 91b09e76-1e5b-4933-80c5-0b9f239a109f)(content(Whitespace\" \ \")))))((Secondary((id \ - ddb1f2b6-3fe6-4079-a75d-dcaebe48bc6f)(content(Whitespace\" \ + cb270ebd-2836-4130-8fad-aeaa67b7f980)(content(Whitespace\" \ \"))))(Tile((id \ - 8439b029-0b7c-47cb-9867-c4c16ed4e733)(label(id))(mold((out \ + 7877499d-8e57-4741-a58f-ff125003f013)(label(id))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - c5fe892a-4d64-4346-95bd-056a11c3f7ad)(label(@< >))(mold((out \ - Exp)(in_(Typ))(nibs(((shape(Concave 1))(sort Exp))((shape \ + bd57d181-948f-4fb2-8bde-9561b1683c7d)(label(@< >))(mold((out \ + Exp)(in_(Typ))(nibs(((shape(Concave 2))(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - 7079f97d-6950-4fd4-b76e-f6924cd0ed7e)(label(Int))(mold((out \ + b605dff8-7b5d-41d7-b163-ed66ada5dad6)(label(Int))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort Typ))))))(shards(0))(children()))))))))(Tile((id \ - 35b79c01-e4db-4671-a26a-ec0a7933c24f)(label(\"(\"\")\"))(mold((out \ - Exp)(in_(Exp))(nibs(((shape(Concave 1))(sort Exp))((shape \ + 23a880e4-666f-41fa-acb7-edc3faafe278)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape(Concave 2))(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - 83c93244-e705-4189-a816-70dd13a963ec)(label(1))(mold((out \ + abd95a67-518c-43cd-b0b0-09139ea11f68)(label(1))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort \ Exp))))))(shards(0))(children()))))))))(Secondary((id \ - 7e153b1d-8ee5-4f89-a01a-1242f0565511)(content(Whitespace\" \ + 6e67188c-d54f-4182-b6e4-e20be7409fe7)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 5d0ec35e-42f0-41e6-810c-b4163164e51e)(content(Whitespace\" \ + c856a4ab-7681-4169-85cc-4003aa80bc52)(content(Whitespace\" \ \"))))(Secondary((id \ - fdb7e231-ff3c-4d22-a8d2-308db57999e4)(content(Comment\"# 1 \ + d01b7960-22ce-4418-92ef-1be2bb1c0fbc)(content(Comment\"# 1 \ #\"))))(Secondary((id \ - a4b7e97a-83dd-492f-ae20-a84b2a979e30)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 8c74bef9-7177-4774-89aa-805787cf673f)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 7309f6e2-2d49-45af-b7c6-0ec75a57fc2b)(content(Comment\"# We \ + 777d62f8-331f-4d1e-8a5a-1a09a9f89ec3)(content(Whitespace\"\\n\"))))(Secondary((id \ + 90e879b8-483e-4c4c-b233-2b31b7c2dfb7)(content(Whitespace\"\\n\"))))(Secondary((id \ + 491a90e6-ead6-42a9-8284-279180c8c580)(content(Comment\"# We \ can annotate the type of a type function with a forall. \ #\"))))(Secondary((id \ - 4fda5632-5de3-4c5d-b424-bf16d704f35a)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - d1ace50b-2196-477e-aeda-e84f61901017)(label(let = \ + c624f13c-9188-4c91-ace5-e7224e6a6dbc)(content(Whitespace\"\\n\"))))(Tile((id \ + 1af4a4d0-b52a-4ec9-979a-9ae451f1f848)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 16))(sort Exp))))))(shards(0 1 \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - b1df318d-3e75-4630-8f19-d3cbc69bb8ee)(content(Whitespace\" \ + a719a29e-7014-4e0c-b5e9-cfdfe8d414f5)(content(Whitespace\" \ \"))))(Tile((id \ - 7a283681-40a7-483c-ab85-ab4916479faa)(label(const))(mold((out \ + c2aabeb4-a488-452f-88a5-0e19c623103c)(label(const))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ - 69a7673c-e766-4409-852e-03c46fbbbf56)(content(Whitespace\" \ + 81273931-7fe2-47cb-a084-f4b062107fab)(content(Whitespace\" \ \"))))(Tile((id \ - f5115707-8100-478a-bf56-748777fdd0c3)(label(:))(mold((out \ - Pat)(in_())(nibs(((shape(Concave 11))(sort \ - Pat))((shape(Concave 11))(sort \ + 03fb0ac4-7aa9-445f-a553-93f4f07d6e8d)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ Typ))))))(shards(0))(children())))(Secondary((id \ - 8bc19b04-eb77-4c2a-9668-4350e26a309d)(content(Whitespace\" \ + 7b7acab2-079f-41d6-a0e4-baaa4d119467)(content(Whitespace\" \ \"))))(Tile((id \ - a7889e83-9fe8-49ad-9bef-44e8ce448a64)(label(forall \ + 0980446a-d625-4b8f-990a-e68e1654e767)(label(forall \ ->))(mold((out Typ)(in_(TPat))(nibs(((shape Convex)(sort \ - Typ))((shape(Concave 13))(sort Typ))))))(shards(0 \ + Typ))((shape(Concave 14))(sort Typ))))))(shards(0 \ 1))(children(((Secondary((id \ - f70ea1f6-288e-407f-8594-1736b20cce67)(content(Whitespace\" \ + a3659d37-0062-4269-ab07-8d0d7b8495d4)(content(Whitespace\" \ \"))))(Tile((id \ - 57bed8d9-e4fb-47da-b21b-fe51fb8ee9e6)(label(A))(mold((out \ + 880b2494-aae9-4110-8880-1f3ef78c91e4)(label(A))(mold((out \ TPat)(in_())(nibs(((shape Convex)(sort TPat))((shape \ Convex)(sort \ TPat))))))(shards(0))(children())))(Secondary((id \ - 48e84944-6794-4ec4-9809-f8c9689fd797)(content(Whitespace\" \ + 9afdb2cc-c50c-438d-b204-af497695d4c6)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 0d8e46dc-456d-471e-9387-04fe16526ad6)(content(Whitespace\" \ + 86b64f50-4921-4a9b-8724-dbf6044084fc)(content(Whitespace\" \ \"))))(Tile((id \ - 913ff727-11a1-4e0d-83fc-99e4de6e34f3)(label(forall \ + f22c1d66-073c-41f8-8af0-aa16e606fa9f)(label(forall \ ->))(mold((out Typ)(in_(TPat))(nibs(((shape Convex)(sort \ - Typ))((shape(Concave 13))(sort Typ))))))(shards(0 \ + Typ))((shape(Concave 14))(sort Typ))))))(shards(0 \ 1))(children(((Secondary((id \ - fea1b479-fbd8-4564-8a3a-93e7e3d5374b)(content(Whitespace\" \ + 41e37e8e-f6b4-4dfa-adb5-c0ee132c4dc2)(content(Whitespace\" \ \"))))(Tile((id \ - d97d38b4-0e17-4bb8-b342-50937dff5896)(label(B))(mold((out \ + d61481c8-74a7-4f04-a2f6-427060e232b2)(label(B))(mold((out \ TPat)(in_())(nibs(((shape Convex)(sort TPat))((shape \ Convex)(sort \ TPat))))))(shards(0))(children())))(Secondary((id \ - e43565a7-cbb9-45aa-ab46-5cda424a47c5)(content(Whitespace\" \ + 4efbad43-f2cf-408e-afbf-d5bffbaf1a6c)(content(Whitespace\" \ \")))))))))(Secondary((id \ - f9ead65c-4436-4958-898c-a7ed360b5b46)(content(Whitespace\" \ + 51b65168-3574-45e5-8451-55997f736b2d)(content(Whitespace\" \ \"))))(Tile((id \ - d6a5887c-ef92-4773-9429-919995401912)(label(A))(mold((out \ + ac21fbdf-6530-4b72-b1fb-74abf3975f88)(label(A))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ - c5801121-b4f8-4751-bca0-6b48d487a7e6)(content(Whitespace\" \ + aaf75b4a-c5ec-4f37-b2c6-6b4f15dcae18)(content(Whitespace\" \ \"))))(Tile((id \ - a3f602fe-03e9-4b18-8c75-2699369b969e)(label(->))(mold((out \ - Typ)(in_())(nibs(((shape(Concave 6))(sort \ - Typ))((shape(Concave 6))(sort \ + ffe8fd86-e515-4f69-a4d6-38e4e7ae4d74)(label(->))(mold((out \ + Typ)(in_())(nibs(((shape(Concave 5))(sort \ + Typ))((shape(Concave 5))(sort \ Typ))))))(shards(0))(children())))(Secondary((id \ - 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5897403d-b63d-4cc9-b9c2-4507b56a530f)(content(Whitespace\" \ \")))))))))(Secondary((id \ - a5c9177a-1a19-4bf5-968b-79dcd8a5f1ae)(content(Whitespace\" \ + f1d2d2bc-6d1c-47cf-9285-6c7be2bbea63)(content(Whitespace\" \ \"))))(Tile((id \ - 21645f30-7293-4698-a5ef-c03a43418311)(label(\"(\"\")\"))(mold((out \ + 87c4686c-9c90-45d4-8ca3-76d1a11b0fda)(label(\"(\"\")\"))(mold((out \ Typ)(in_(Typ))(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort Typ))))))(shards(0 1))(children(((Tile((id \ - 2236339d-9e54-45ca-b4f0-a2adcf62fdd4)(label(Nil))(mold((out \ + 6d33f00c-fc5f-40f4-be57-abbb5b34d0d9)(label(Nil))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ - 2eda9a70-f5e3-4430-8ac3-94060fd5b62a)(content(Whitespace\" \ + 38d2b064-d7cf-47ce-9617-9de757dffa26)(content(Whitespace\" \ \"))))(Tile((id \ - 724193cc-c749-44c9-86c9-24c6d5f02b21)(label(+))(mold((out \ - Typ)(in_())(nibs(((shape(Concave 10))(sort \ - 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\ + d8141f6d-983b-4e7e-a3e4-ae8d9161dfa7)(label(Int))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort Typ))))))(shards(0))(children())))(Tile((id \ - fffa4b09-8032-4007-a8e9-c1b4c9b3e4cf)(label(,))(mold((out \ - Typ)(in_())(nibs(((shape(Concave 14))(sort \ - Typ))((shape(Concave 14))(sort \ + 28f2b782-dbfc-4077-bd76-1fbf1645c838)(label(,))(mold((out \ + Typ)(in_())(nibs(((shape(Concave 15))(sort \ + Typ))((shape(Concave 15))(sort \ Typ))))))(shards(0))(children())))(Secondary((id \ - 61db4da2-294b-4285-96e3-718cb15577c8)(content(Whitespace\" \ + dc4423b7-c82e-4185-943d-e1f5648ea120)(content(Whitespace\" \ \"))))(Tile((id \ - 9692e5ad-a529-43ef-a693-413e0ab21a31)(label(A))(mold((out \ + e5d2acce-68db-448d-8cc0-bf4984154edc)(label(A))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort \ Typ))))))(shards(0))(children())))))))))))))(Secondary((id \ - 990cc418-00f2-4c98-9395-ad95bca66884)(content(Whitespace\" \ + 96cf1a82-f8a8-4d80-8913-085df0c08c13)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 3701484f-c796-4d38-bce7-4f25b4c3637d)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 193cfb02-bcdb-47e2-80c5-4775c7f11a82)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 8c0f2c04-fc2c-4fdf-8f0c-83644d1be509)(content(Comment\"# \ + ce5f884f-b166-4229-82dc-8f63f57adea9)(content(Whitespace\"\\n\"))))(Secondary((id \ + caf3425f-2a3b-41a2-a7c1-54b114516486)(content(Whitespace\"\\n\"))))(Secondary((id \ + c6048be2-bd6c-4125-81ce-882a9995f8b8)(content(Comment\"# \ Hazel does not (yet) support higher-kinded or existential \ types, #\"))))(Secondary((id \ - 4810f7f2-213a-465d-9b61-81cf18482fa8)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 0eaf40c5-5a8b-4cbb-aa19-18ba099847eb)(content(Comment\"# So \ + f599444a-c756-430c-b95e-dfb37ebc5ba3)(content(Whitespace\"\\n\"))))(Secondary((id \ + a4cb6fa4-95c4-4a1e-83e0-aee6faf28274)(content(Comment\"# So \ we cannot implement our own polymorphic lists. \ #\"))))(Secondary((id \ - 579ceeeb-258a-4089-a115-5627e2eaea58)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 7bfbd599-e516-45a7-a725-cb39be5c8729)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 887616c9-6707-4e70-ab3d-62996ce73e70)(content(Comment\"# Now \ + 459721ed-2da6-4305-84fb-05174d296fb3)(content(Whitespace\"\\n\"))))(Secondary((id \ + 8a4f841b-1d46-456e-83fd-6cc8e0def87f)(content(Whitespace\"\\n\"))))(Secondary((id \ + de5094a7-d1b1-43b7-80a2-baa03c9ac327)(content(Comment\"# Now \ anything that returns an element of the least fixed point \ matches MyList. #\"))))(Secondary((id \ - 6f06209e-4913-4da3-ae91-5bd283668594)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 33ed3a5b-0867-43d7-8cc2-2c8ca4c758e7)(label(let = \ + 0fc57d97-2f81-496e-a0ed-5a29f98f041c)(content(Whitespace\"\\n\"))))(Tile((id \ + aa27eca1-91a4-4b37-af52-4696c18b7134)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 16))(sort Exp))))))(shards(0 1 \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - 0370f42e-bd6c-490a-bb7d-920d2f8a8aae)(content(Whitespace\" \ + e0c4d089-4099-4a1a-83ff-3bd6c3cae9e9)(content(Whitespace\" \ \"))))(Tile((id \ - 5bae080b-2019-4ffd-a2a9-2a972fcda28d)(label(x))(mold((out \ + aac7f4f6-67c9-45b6-bf86-fd0a783fa2d6)(label(x))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ - 4079c066-6ef0-4310-83c6-56fe7fd7670e)(content(Whitespace\" \ + a15942a7-b0d3-486e-9ad6-21c51ff59e86)(content(Whitespace\" \ \"))))(Tile((id \ - a0c477e1-9ef3-4b38-a67c-d5d22e96471d)(label(:))(mold((out \ - Pat)(in_())(nibs(((shape(Concave 11))(sort \ - Pat))((shape(Concave 11))(sort \ + 1143ad5c-81f3-4cee-a0bb-c86feff32bda)(label(:))(mold((out \ + Pat)(in_())(nibs(((shape(Concave 12))(sort \ + Pat))((shape(Concave 12))(sort \ Typ))))))(shards(0))(children())))(Secondary((id \ - 93cd7df1-2b4d-4582-acf7-2cb0d46f6313)(content(Whitespace\" \ + 07ed8ab7-19f9-4ab5-88e8-23238dc52fbe)(content(Whitespace\" \ \"))))(Tile((id \ - e62970f7-e979-49fb-bde6-c008d8d79a70)(label(MyList))(mold((out \ + a6e8c11f-c7ac-49e0-8f04-dfbc17d94680)(label(MyList))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ - 1b69d275-5bd5-489b-a340-7aafdfd14d12)(content(Whitespace\" \ + 75005215-aa4e-4590-b0e8-7618b5c239b1)(content(Whitespace\" \ \")))))((Secondary((id \ - 5c867417-e06d-4873-b84d-041e25dcb2d0)(content(Whitespace\" \ + 06154ff2-caa2-46c8-b2af-3d2aaafe9b01)(content(Whitespace\" \ \"))))(Tile((id \ - 2cf5af86-df22-4aba-a044-17d75a3ae989)(label(Cons))(mold((out \ + 84156c26-cb86-4c86-aec5-9eb23512914e)(label(Cons))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 7e122a6b-5f64-4a7e-90ae-0878e0d82f03)(label(\"(\"\")\"))(mold((out \ - Exp)(in_(Exp))(nibs(((shape(Concave 1))(sort Exp))((shape \ + 9140b606-ad9e-4efe-887b-dd85869dd8fc)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape(Concave 2))(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - 1d783d64-398f-4ad6-9eae-b3490775e34c)(label(1))(mold((out \ + 230d17fc-4ed9-424f-8234-0e104187d4a5)(label(1))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - df60de96-d925-4ca9-beca-a392fa9d3a33)(label(,))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 14))(sort \ - Exp))((shape(Concave 14))(sort \ + d9cbd3c6-b30c-42c9-a5af-e7db45d3c674)(label(,))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 15))(sort \ + Exp))((shape(Concave 15))(sort \ Exp))))))(shards(0))(children())))(Secondary((id \ - a798be71-5b99-4f2e-a8e2-e923f9609370)(content(Whitespace\" \ + 9b41f61a-4f33-4471-a151-502a75aa797f)(content(Whitespace\" \ \"))))(Tile((id \ - 8565ea1f-2353-458d-9439-7f379d71cebd)(label(Cons))(mold((out \ + cca56564-49cb-4d2c-a41b-90138f5ed45b)(label(Cons))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 7ece0aa1-030f-42ec-98ef-b2628aac965c)(label(\"(\"\")\"))(mold((out \ - Exp)(in_(Exp))(nibs(((shape(Concave 1))(sort Exp))((shape \ + 0723f810-c901-4d35-b8c3-879dc47f0011)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape(Concave 2))(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - e755b115-0361-453e-b274-9f9cb8a0c262)(label(2))(mold((out \ + 308c52b4-8761-4bba-92f9-6d7e551c8e7b)(label(2))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 4459b0c1-70f4-4101-a896-21725d8c2a4e)(label(,))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 14))(sort \ - Exp))((shape(Concave 14))(sort \ + 84174d3d-d8cb-402b-847c-a1ca74a01edd)(label(,))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 15))(sort \ + Exp))((shape(Concave 15))(sort \ Exp))))))(shards(0))(children())))(Secondary((id \ - 9bc6d0d7-59d4-4cff-819a-6fa718e28414)(content(Whitespace\" \ + 826ba090-6484-407d-8f9d-4fc82aa5e262)(content(Whitespace\" \ \"))))(Tile((id \ - 9bcc25fd-a616-49f1-9f53-f12a36e09354)(label(Cons))(mold((out \ + 6526cc0e-21e6-4999-8165-317606413606)(label(Cons))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - e5ad642e-1071-4a7b-ae6f-d6c8b4b34403)(label(\"(\"\")\"))(mold((out \ - Exp)(in_(Exp))(nibs(((shape(Concave 1))(sort Exp))((shape \ + f5509196-25c5-4078-9f93-79a844ac6a01)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape(Concave 2))(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - fcd291b3-e052-402b-be90-a4a138f94cce)(label(3))(mold((out \ + cd772d9a-9849-4bdd-b1ce-c112929a6037)(label(3))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - bab8fe07-56b3-4a03-8a70-cad1d19c41ce)(label(,))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 14))(sort \ - Exp))((shape(Concave 14))(sort \ + b18eca82-fdaa-47f9-a692-dcae6d2d7b9f)(label(,))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 15))(sort \ + Exp))((shape(Concave 15))(sort \ Exp))))))(shards(0))(children())))(Secondary((id \ - 952bc037-e9e7-42a4-9dd8-24f64cbaedd9)(content(Whitespace\" \ + bdb4f1fe-b646-4038-a5c6-02fd5180eae6)(content(Whitespace\" \ \"))))(Tile((id \ - 63e70629-8a00-4987-adcc-d9b7edb62ecc)(label(Nil))(mold((out \ + 5b3dc9a2-776a-4f30-a5e4-9ea629c4fc8f)(label(Nil))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort \ Exp))))))(shards(0))(children()))))))))))))))))))(Secondary((id \ - 3c1a3bf1-ed31-4739-885e-ad254fc292f2)(content(Whitespace\" \ + cd14adaf-2eaf-4683-b212-c3f1ae40c258)(content(Whitespace\" \ \")))))))))(Secondary((id \ - b75b8ab1-8759-45b5-ad5b-ed90197258da)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 935b835c-261d-47fc-bee8-068e25da32a8)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - fb36a038-d3c2-48ec-9310-1ccb658b327a)(content(Comment\"# Note \ + d3c31f12-2f54-4ffe-ac8e-8af9952b4e44)(content(Whitespace\"\\n\"))))(Secondary((id \ + 45e15030-54bf-4bf6-bb2e-71d3f1393882)(content(Whitespace\"\\n\"))))(Secondary((id \ + 149652ce-dc20-4064-9798-ae70ad885b09)(content(Comment\"# Note \ that if the sum is the top level operator, \ #\"))))(Secondary((id \ - 3c729241-60ac-46a3-86db-92a070ffa4d5)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - f7670b91-4175-4a41-b92a-232fd61e8eec)(content(Comment\"# type \ + c432fee2-53b2-46f9-b952-28c6e199c3d3)(content(Whitespace\"\\n\"))))(Secondary((id \ + 86024019-cc4a-4063-931b-96e183d13bcc)(content(Comment\"# type \ aliases are implicitly least fixed points on their own name: \ #\"))))(Secondary((id \ - ff8533bf-ba1e-4237-8c1c-e3130b234e64)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - e940b831-775d-4d20-8c4e-cf380df7c704)(label(type = \ + 02a76b43-546d-4831-9e4f-8224ccbd3f4f)(content(Whitespace\"\\n\"))))(Tile((id \ + 6d7a7d09-7c09-42ca-af90-ca118d62e09a)(label(type = \ in))(mold((out Exp)(in_(TPat Typ))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 16))(sort Exp))))))(shards(0 1 \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - fa4039e4-3ac6-4d02-9df8-449e895958cd)(content(Whitespace\" \ + f1ae62e5-5035-4370-b152-33d926dfcb7d)(content(Whitespace\" \ \"))))(Tile((id \ - 05f24c94-0119-4bd5-b234-a1dbdaeab975)(label(MyList2))(mold((out \ + 156beede-4adc-4099-8bfb-e2392bbb984b)(label(MyList2))(mold((out \ TPat)(in_())(nibs(((shape Convex)(sort TPat))((shape \ Convex)(sort \ TPat))))))(shards(0))(children())))(Secondary((id \ - a5939fcf-4a82-49d3-a9dc-8d899ad579f6)(content(Whitespace\" \ + 64b19283-c87f-4578-a9eb-cf6c88a7140d)(content(Whitespace\" \ \")))))((Secondary((id \ - 4e843e4a-0c21-4bd3-9163-bad05c819bc8)(content(Whitespace\" \ + c56603ae-3f6f-49ac-b092-9636774b47db)(content(Whitespace\" \ \"))))(Tile((id \ - 8f4764bd-552d-47b3-a75f-8177eacbfad3)(label(Nil))(mold((out \ + c608445a-7dc1-4b4d-b59b-476eae965de8)(label(Nil))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort Typ))))))(shards(0))(children())))(Secondary((id \ - 2b1728e8-6ba7-4cbb-9064-aec652c83d87)(content(Whitespace\" \ + 318b2a8a-adf4-44d0-921e-20f264679c64)(content(Whitespace\" \ \"))))(Tile((id \ - 6585a36d-b5e9-4a63-8d45-bca7e5c38cf0)(label(+))(mold((out \ - Typ)(in_())(nibs(((shape(Concave 10))(sort \ - Typ))((shape(Concave 10))(sort \ + 5cd528ef-218c-42a7-a034-6c726453671c)(label(+))(mold((out \ + Typ)(in_())(nibs(((shape(Concave 11))(sort \ + Typ))((shape(Concave 11))(sort \ Typ))))))(shards(0))(children())))(Secondary((id \ - 77c58ade-ef24-46bd-8fad-1fe0dacbc953)(content(Whitespace\" \ + effc4dbd-344f-45b7-8f6a-a933b0ab1b15)(content(Whitespace\" \ \"))))(Tile((id \ - a97829e0-ec9c-4941-affb-26a072f73fc5)(label(Cons))(mold((out \ + 534989eb-ef91-4e5b-9e06-1a6ce71bd4b1)(label(Cons))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort Typ))))))(shards(0))(children())))(Tile((id \ - 12e14808-3cec-40de-88dc-d9d030c3e0a8)(label(\"(\"\")\"))(mold((out \ - Typ)(in_(Typ))(nibs(((shape(Concave 1))(sort Typ))((shape \ + 38dcfa59-8b96-4eef-8f2f-db936f62adde)(label(\"(\"\")\"))(mold((out \ + Typ)(in_(Typ))(nibs(((shape(Concave 2))(sort Typ))((shape \ Convex)(sort Typ))))))(shards(0 1))(children(((Tile((id \ - b501c4ea-e896-49a6-a03e-e15a8d8e9a51)(label(Int))(mold((out \ + 3acee723-61df-4844-99c8-33376981b6b8)(label(Int))(mold((out \ Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape \ Convex)(sort Typ))))))(shards(0))(children())))(Tile((id \ 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282a4121-76db-46b2-92f2-c0b3bea39dab)(content(Whitespace\" \ + 8a6d6443-ad77-4538-a473-fc7984a46623)(content(Whitespace\" \ \")))))))))(Secondary((id \ - d2bace67-f8aa-4fb7-b767-ff056b2db439)(content(Whitespace\" \ + 0d200042-cf30-41bb-bc17-e7ec2102adbb)(content(Whitespace\" \ \"))))(Tile((id \ - 52d40c83-e37a-4e99-a9f9-cce2a9bee532)(label(h))(mold((out \ + 8c8d8699-5d50-4559-a777-258dc39138af)(label(h))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Secondary((id \ - 726272aa-84f1-4832-bce7-abf746dd38ac)(content(Whitespace\" \ + 7b07f85a-77c6-4892-9b37-ed58ef37de5b)(content(Whitespace\" \ \"))))(Tile((id \ - cdc66ee5-157b-46bd-bd7b-1f5adf1eaf00)(label(::))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 6))(sort \ - Exp))((shape(Concave 6))(sort \ + 5d697673-224c-4286-b050-2d7b22d45f68)(label(::))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 7))(sort \ + Exp))((shape(Concave 7))(sort \ Exp))))))(shards(0))(children())))(Secondary((id \ - 6a2d26fd-953a-4bd7-96af-01a5e67c5164)(content(Whitespace\" \ + abc17ad0-806c-4460-b56f-2d409e1e148c)(content(Whitespace\" \ \"))))(Tile((id \ - 3d383ccc-98af-43c0-811c-71cf543f3560)(label(list_of_mylist))(mold((out \ + aaf1bfc4-35db-48dd-bda7-b1998e888b62)(label(list_of_mylist))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 34f0131a-6046-42b7-acc3-0e9b115598e9)(label(\"(\"\")\"))(mold((out \ - Exp)(in_(Exp))(nibs(((shape(Concave 1))(sort Exp))((shape \ + 4dcc8cc7-da9c-4075-9941-84b547b75443)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape(Concave 2))(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - 7644fb73-3d7b-4647-89a1-17ac8db02acf)(label(t))(mold((out \ + 74b76516-fa73-4e40-88ea-373f0bd66560)(label(t))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort \ Exp))))))(shards(0))(children()))))))))(Secondary((id \ - 4c34a3ca-0ad2-4452-8353-edc564632dd3)(content(Whitespace\" \ + 954678b7-044c-44ae-8009-7ffeaadeb8a2)(content(Whitespace\" \ \"))))(Secondary((id \ - b46b62aa-f261-440b-a185-d0d676172b7e)(content(Whitespace\" \ + 9b358a1d-5b2a-4b15-a585-4b48232dd712)(content(Whitespace\" \ \"))))(Secondary((id \ - a48cde36-a585-4160-9422-90e3f070e845)(content(Whitespace\"\\226\\143\\142\")))))))))(Secondary((id \ - cd5ed745-ec98-409e-ac1f-234b381dce78)(content(Whitespace\" \ + ba59b233-f10e-4c73-915b-a8b8661a612b)(content(Whitespace\" \ + \"))))(Secondary((id \ + e69a6392-8b62-4f85-8f81-38ed98e7372f)(content(Whitespace\" \ + \"))))(Secondary((id \ + 7a3e1339-6277-42a6-a5a9-6eddf0fdfe2a)(content(Whitespace\"\\n\")))))))))(Secondary((id \ + f537135f-30be-4360-a5b6-90269136e275)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 6dece3b9-a529-490e-91f2-12e76091b87f)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 287d9620-78ca-4128-9b32-8f9cb6b58760)(label(let = \ + 2dd2bf49-93f0-487e-abfc-eb01031c27b2)(content(Whitespace\"\\n\"))))(Tile((id \ + adb827e5-6130-4050-bd5e-2c7d4389a53d)(label(let = \ in))(mold((out Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 16))(sort Exp))))))(shards(0 1 \ + Exp))((shape(Concave 17))(sort Exp))))))(shards(0 1 \ 2))(children(((Secondary((id \ - 80255e8c-d69c-49e8-a4da-becb2c97c9a6)(content(Whitespace\" \ + fa0bf5f6-5a3b-44e8-8bbe-ec3ada77bb93)(content(Whitespace\" \ \"))))(Tile((id \ - 5e33ed39-557f-4503-a948-ffc0a793cd4d)(label(ex5))(mold((out \ + c016161b-23fd-4267-a75a-43218f4b0317)(label(ex5))(mold((out \ Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape \ Convex)(sort Pat))))))(shards(0))(children())))(Secondary((id \ - 9fbd2e14-8f09-4035-8020-e8f44fba8526)(content(Whitespace\" \ + 20a4148b-853f-484d-8423-bae1dc00286b)(content(Whitespace\" \ \")))))((Secondary((id \ - f767e5a7-54ab-44d3-a224-fffdadf9da4a)(content(Whitespace\" \ + 9e848c9f-27b0-4b08-ab1b-24b05c16cd00)(content(Whitespace\" \ \"))))(Tile((id \ - ad84dbab-bb06-43c8-8920-1b9e5e8c9cd8)(label(list_of_mylist))(mold((out \ + 5b494e56-3450-4893-a1ff-780b3264f923)(label(list_of_mylist))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - cefbaa1c-b1dc-4728-a64d-1663b18eec41)(label(\"(\"\")\"))(mold((out \ - Exp)(in_(Exp))(nibs(((shape(Concave 1))(sort Exp))((shape \ + 43da4f1c-8e84-42c8-9cc9-97d6ebeee657)(label(\"(\"\")\"))(mold((out \ + Exp)(in_(Exp))(nibs(((shape(Concave 2))(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - 8dd0ee06-28a5-424b-93b3-2c269447b2fa)(label(x))(mold((out \ + f559334b-0f30-4e33-be02-af706c8f4d96)(label(x))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort \ Exp))))))(shards(0))(children()))))))))(Secondary((id \ - c24e59ed-e80f-4816-afcc-d222b126c80a)(content(Whitespace\" \ + 42b7ffd5-8f17-4ded-aba5-2eadb5821520)(content(Whitespace\" \ \")))))))))(Secondary((id \ - 140a3fe3-246f-4a21-bf2d-aac3c7ea1eab)(content(Whitespace\" \ + fb69fc73-8a28-48a3-aeee-3a75e1cdedb8)(content(Whitespace\" \ \"))))(Secondary((id \ - d006bb40-713e-4973-9d8b-34ff0316612c)(content(Comment\"# [1, \ + 7a2e9eaa-4405-457f-9e63-36eac807087e)(content(Comment\"# [1, \ 2, 3] #\"))))(Secondary((id \ - 2fff78bc-2182-4db7-bfa8-33fe02a69a5b)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 1096a58b-888f-47e9-9318-313d0f728a9c)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 26bec031-02af-4b4d-967f-a3b8fa91866b)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - ec44021a-5905-4176-8a43-e4b18ecee191)(content(Comment\"# All \ + b687ad12-d0bb-4f0d-bde1-0bcb776e4443)(content(Whitespace\"\\n\"))))(Secondary((id \ + cda2e5c7-45a8-4879-88dc-9b1b651cdca4)(content(Whitespace\"\\n\"))))(Secondary((id \ + d8cc89a9-5bf4-4b78-81a0-b1c5d9451ad4)(content(Whitespace\"\\n\"))))(Secondary((id \ + a8c91397-927d-46e0-b6ae-8b74ac2a8ad2)(content(Comment\"# All \ output from examples: #\"))))(Secondary((id \ - a54fbe78-5b70-4bff-a1b0-f75d699e2d17)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 7f3190eb-b200-4e27-b89e-64483682f7cb)(label(\"(\"\")\"))(mold((out \ + 3b97ec16-3f61-4f68-b248-aaca867a2a49)(content(Whitespace\"\\n\"))))(Tile((id \ + 179da491-661b-4ba4-a24e-7d00e4062471)(label(\"(\"\")\"))(mold((out \ Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0 1))(children(((Tile((id \ - 8a74a004-7d34-4e27-8fa7-bc1464a894d7)(label(ex1))(mold((out \ + eb8715c6-7afe-4f23-84cf-31c9c391506d)(label(ex1))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 4ecc4b06-6a0d-449d-a7a9-507babe76cf8)(label(,))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 14))(sort \ - Exp))((shape(Concave 14))(sort \ + 7a46cceb-444c-4343-8d87-a55cd2c1eedc)(label(,))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 15))(sort \ + Exp))((shape(Concave 15))(sort \ Exp))))))(shards(0))(children())))(Secondary((id \ - a14aabb1-2f9e-405f-a6b1-49e947e6f8f0)(content(Whitespace\" \ + eed590f1-fb2f-4a68-ac6b-c4e93fb9f7e8)(content(Whitespace\" \ \"))))(Tile((id \ - bb8c31bc-af07-43ea-aa54-cebe3b7fe4c7)(label(ex2))(mold((out \ + 07c52a26-01b7-4d87-8cdf-b657273e67e8)(label(ex2))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - e365c1ab-868b-419e-96e8-c11185577df8)(label(,))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 14))(sort \ - Exp))((shape(Concave 14))(sort \ + e2c29b4c-3e9b-443f-888b-f5df11670119)(label(,))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 15))(sort \ + Exp))((shape(Concave 15))(sort \ Exp))))))(shards(0))(children())))(Secondary((id \ - adc45428-7b5c-4e79-9f5d-a70170063fc5)(content(Whitespace\" \ + 443e38d3-fa67-4415-8b28-5ee13f05f3f6)(content(Whitespace\" \ \"))))(Tile((id \ - f25fdd38-87ca-44b2-bd55-3b1c13e31c51)(label(ex3))(mold((out \ + 5cffb2ac-001a-42a6-8ff6-22fd5cb26efc)(label(ex3))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 848d336b-5c6a-4c2f-848d-474fdb03b8d7)(label(,))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 14))(sort \ - Exp))((shape(Concave 14))(sort \ + 1522405c-6b51-47bb-aa60-89671a27d71a)(label(,))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 15))(sort \ + Exp))((shape(Concave 15))(sort \ Exp))))))(shards(0))(children())))(Secondary((id \ - 6dfa74ec-c592-42a4-a583-96e241120cef)(content(Whitespace\" \ + e5154891-4ad3-4d95-8601-a311f10de5d0)(content(Whitespace\" \ \"))))(Tile((id \ - 521e9214-e5ca-4c1d-995c-1d0b12a4aa20)(label(ex4))(mold((out \ + 97f8fd65-6b1c-430f-b73c-50db1333c457)(label(ex4))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort Exp))))))(shards(0))(children())))(Tile((id \ - 4a995d1a-3021-45dd-a4d7-13cff4af4385)(label(,))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 14))(sort \ - Exp))((shape(Concave 14))(sort \ + 6bd8095b-89b6-419f-9de1-19c5e746c4a9)(label(,))(mold((out \ + Exp)(in_())(nibs(((shape(Concave 15))(sort \ + Exp))((shape(Concave 15))(sort \ Exp))))))(shards(0))(children())))(Secondary((id \ - f335f93b-9ff4-47f8-8043-301b1f88d1f7)(content(Whitespace\" \ + 44c1f515-be13-4026-80b2-48556eee832b)(content(Whitespace\" \ \"))))(Tile((id \ - 6d11e3ff-91bd-4a63-8233-0f2ff4c37428)(label(ex5))(mold((out \ + 268a3ed0-8342-423d-a603-7e3b19243afa)(label(ex5))(mold((out \ Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape \ Convex)(sort \ - Exp))))))(shards(0))(children())))))))))()))(ancestors())))(caret \ + Exp))))))(shards(0))(children())))))))))))(ancestors())))(caret \ Outer))"; backup_text = "# Polymorphism #\n\n\ @@ -17484,7 +18626,7 @@ let startup : PersistentData.t = typfun A -> typfun B -> fun f : (A -> B) -> fun l : [A] -> \n\ case l\n\ | h :: t => f(h) :: map@@(f)(t)\n\ - | _ => emptylist@ \n\ + | _ => emptylist@ \n\ end in\n\ let ex4 = map@@(string_of_int)([1,2,3]) in # \ [\"1\", \"2\", \"3\"] #\n\n\n\ @@ -17507,27 +18649,27 @@ let startup : PersistentData.t = let list_of_mylist : (MyList -> [Int]) = fun myl : MyList -> \n\ case myl \n\ | Nil => []\n\ - | Cons(h, t) => h :: list_of_mylist(t) \n\ + | Cons(h, t) => h :: list_of_mylist(t) \n\ end in\n\ let ex5 = list_of_mylist(x) in # [1, 2, 3] #\n\n\n\ # All output from examples: #\n\ (ex1, ex2, ex3, ex4, ex5)"; } ); - ( "Programming Expressively", + ( "Expressive Programming", { zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Grout((id \ - 73cb2f1d-94b4-42eb-9d77-a832748556b0)(shape \ + 527b01da-5acd-4de7-99a0-02510f2fbe0f)(shape \ Convex))))))(ancestors())))(caret Outer))"; backup_text = " "; } ); - ( "Composing Arithmetic Expressions", + ( "Composing Expressions", { zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Grout((id \ - 41444a61-1cf6-408b-82c6-464f3ca6750e)(shape \ + 3767c92f-8a0e-4b82-8407-7e33c55a07be)(shape \ Convex))))))(ancestors())))(caret Outer))"; backup_text = " "; } ); @@ -17536,7 +18678,7 @@ let startup : PersistentData.t = zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Grout((id \ - c7e3b9bd-efaa-41f2-800d-9986a6e814d6)(shape \ + 293ef06a-03d2-4770-8282-f6bbc4aeea08)(shape \ Convex))))))(ancestors())))(caret Outer))"; backup_text = " "; } ); @@ -17545,7 +18687,7 @@ let startup : PersistentData.t = zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Grout((id \ - 92e68905-30cc-415b-b920-6323180c56d1)(shape \ + 878e0a53-88e7-489c-8f30-b60405bb8eb7)(shape \ Convex))))))(ancestors())))(caret Outer))"; backup_text = " "; } ); @@ -17554,7 +18696,7 @@ let startup : PersistentData.t = zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Grout((id \ - 661cbe22-ffdc-4fa3-b227-f7b56a1c8ed6)(shape \ + 67f58c5b-14f7-4b5d-9478-1e66a9bb97ba)(shape \ Convex))))))(ancestors())))(caret Outer))"; backup_text = " "; } ); @@ -17563,7 +18705,7 @@ let startup : PersistentData.t = zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Grout((id \ - f213697c-e203-41c4-8888-fc12e3ac46bf)(shape \ + a48ecbfe-f027-4482-b40c-d59c7a79b52e)(shape \ Convex))))))(ancestors())))(caret Outer))"; backup_text = " "; } ); @@ -17572,7 +18714,7 @@ let startup : PersistentData.t = zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Grout((id \ - 3d8e1707-1e20-4160-946e-73cdb9e98ee1)(shape \ + fa020b7e-8025-47eb-b6ce-5b5797358e67)(shape \ Convex))))))(ancestors())))(caret Outer))"; backup_text = " "; } ); @@ -17581,7 +18723,7 @@ let startup : PersistentData.t = zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Grout((id \ - f49430b2-1265-4e87-a6d6-795eb57c37f8)(shape \ + c19d2704-759a-401a-af23-b6c5263f7c7b)(shape \ Convex))))))(ancestors())))(caret Outer))"; backup_text = " "; } ); @@ -17590,7 +18732,7 @@ let startup : PersistentData.t = zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Grout((id \ - e2b7d6b9-5b95-4fad-9278-60097f30375f)(shape \ + 5eb4e750-954c-46e7-a785-d8af9e1b8e40)(shape \ Convex))))))(ancestors())))(caret Outer))"; backup_text = " "; } ); @@ -17599,13 +18741,28 @@ let startup : PersistentData.t = zipper = "((selection((focus Left)(content())(mode \ Normal)))(backpack())(relatives((siblings(()((Grout((id \ - b60e7d0e-e290-4b23-b03c-7fe121fb5dcd)(shape \ + a1407558-57b7-45ea-b4d6-83771ae62b46)(shape \ Convex))))))(ancestors())))(caret Outer))"; backup_text = " "; } ); ], [ + ("scratch_ADT Dynamics", Evaluation); + ("scratch_ADT Statics", Evaluation); ("scratch_Basic Reference", Evaluation); + ("scratch_Booleans and Types", Evaluation); + ("scratch_Casting", Evaluation); + ("scratch_Composing Arithmetic Expressions", Evaluation); + ("scratch_Compositionality", Evaluation); + ("scratch_Computing Equationally", Evaluation); + ("scratch_Conditional Expressions", Evaluation); + ("scratch_Functions", Evaluation); + ("scratch_Polymorphism", Evaluation); ("scratch_Programming Expressively", Evaluation); + ("scratch_Projectors", Evaluation); + ("scratch_Scope", Evaluation); + ("scratch_Shadowing", Evaluation); + ("scratch_Types & static errors", Evaluation); + ("scratch_Variables", Evaluation); ] ); } diff --git a/src/haz3lweb/Keyboard.re b/src/haz3lweb/Keyboard.re index bad937c531..7e4e655f26 100644 --- a/src/haz3lweb/Keyboard.re +++ b/src/haz3lweb/Keyboard.re @@ -1,9 +1,233 @@ open Haz3lcore; +open Util; -let is_digit = s => Re.Str.(string_match(regexp("^[0-9]$"), s, 0)); -let is_f_key = s => Re.Str.(string_match(regexp("^F[0-9][0-9]*$"), s, 0)); +let is_digit = s => StringUtil.(match(regexp("^[0-9]$"), s)); +let is_f_key = s => StringUtil.(match(regexp("^F[0-9][0-9]*$"), s)); -let handle_key_event = (k: Key.t): option(Update.t) => { +type shortcut = { + update_action: option(UpdateAction.t), + hotkey: option(string), + label: string, + mdIcon: option(string), + section: option(string), +}; + +let meta = (sys: Key.sys): string => { + switch (sys) { + | Mac => "cmd" + | PC => "ctrl" + }; +}; + +let mk_shortcut = + (~hotkey=?, ~mdIcon=?, ~section=?, label, update_action): shortcut => { + {update_action: Some(update_action), hotkey, label, mdIcon, section}; +}; + +let instructor_shortcuts: list(shortcut) = [ + mk_shortcut( + ~mdIcon="download", + ~section="Export", + "Export All Persistent Data", + Export(ExportPersistentData), + ), + mk_shortcut( + ~mdIcon="download", + ~section="Export", + "Export Exercise Module", + Export(ExerciseModule) // TODO Would we rather skip contextual stuff for now or include it and have it fail + ), + mk_shortcut( + ~mdIcon="download", + ~section="Export", + "Export Transitionary Exercise Module", + Export(TransitionaryExerciseModule) // TODO Would we rather skip contextual stuff for now or include it and have it fail + ), + mk_shortcut( + ~mdIcon="download", + ~section="Export", + "Export Grading Exercise Module", + Export(GradingExerciseModule) // TODO Would we rather skip contextual stuff for now or include it and have it fail + ), +]; + +// List of shortcuts configured to show up in the command palette and have hotkey support +let shortcuts = (sys: Key.sys): list(shortcut) => + [ + mk_shortcut(~mdIcon="undo", ~hotkey=meta(sys) ++ "+z", "Undo", Undo), + mk_shortcut( + ~hotkey=meta(sys) ++ "+shift+z", + ~mdIcon="redo", + "Redo", + Redo, + ), + mk_shortcut( + ~hotkey="F12", + ~mdIcon="arrow_forward", + ~section="Navigation", + "Go to Definition", + PerformAction(Jump(BindingSiteOfIndicatedVar)), + ), + mk_shortcut( + ~hotkey="shift+tab", + ~mdIcon="swipe_left_alt", + ~section="Navigation", + "Go to Previous Hole", + PerformAction(Move(Goal(Piece(Grout, Left)))), + ), + mk_shortcut( + ~mdIcon="swipe_right_alt", + ~section="Navigation", + "Go To Next Hole", + PerformAction(Move(Goal(Piece(Grout, Right)))), + // Tab is overloaded so not setting it here + ), + mk_shortcut( + ~hotkey=meta(sys) ++ "+d", + ~mdIcon="select_all", + ~section="Selection", + "Select current term", + PerformAction(Select(Term(Current))), + ), + mk_shortcut( + ~hotkey=meta(sys) ++ "+p", + ~mdIcon="backpack", + "Pick up selected term", + PerformAction(Pick_up), + ), + mk_shortcut( + ~mdIcon="select_all", + ~hotkey=meta(sys) ++ "+a", + ~section="Selection", + "Select All", + PerformAction(Select(All)), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Statics", + UpdateAction.Set(Statics), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Completion", + UpdateAction.Set(Assist), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Show Whitespace", + UpdateAction.Set(SecondaryIcons), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Print Benchmarks", + UpdateAction.Set(Benchmark), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Toggle Dynamics", + UpdateAction.Set(Dynamics), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Show Elaboration", + UpdateAction.Set(Elaborate), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Show Function Bodies", + UpdateAction.Set(Evaluation(ShowFnBodies)), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Show Case Clauses", + UpdateAction.Set(Evaluation(ShowCaseClauses)), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Show fixpoints", + UpdateAction.Set(Evaluation(ShowFixpoints)), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Show Casts", + UpdateAction.Set(Evaluation(ShowCasts)), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Show Lookup Steps", + UpdateAction.Set(Evaluation(ShowLookups)), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Show Stepper Filters", + UpdateAction.Set(Evaluation(ShowFilters)), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Show Hidden Steps", + UpdateAction.Set(Evaluation(ShowHiddenSteps)), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Show Docs Sidebar", + UpdateAction.Set(ExplainThis(ToggleShow)), + ), + mk_shortcut( + ~section="Settings", + ~mdIcon="tune", + "Toggle Show Docs Feedback", + UpdateAction.Set(ExplainThis(ToggleShowFeedback)), + ), + mk_shortcut( + ~hotkey=meta(sys) ++ "+/", + ~mdIcon="assistant", + "TyDi Assistant", + PerformAction(Buffer(Set(TyDi))) // I haven't figured out how to trigger this in the editor + ), + mk_shortcut( + ~mdIcon="download", + ~section="Export", + "Export Scratch Slide", + Export(ExportScratchSlide), + ), + mk_shortcut( + ~mdIcon="download", + ~section="Export", + "Export Submission", + Export(Submission) // TODO Would we rather skip contextual stuff for now or include it and have it fail + ), + mk_shortcut( + // ctrl+k conflicts with the command palette + ~section="Diagnostics", + ~mdIcon="refresh", + "Reparse Current Editor", + PerformAction(Reparse), + ), + mk_shortcut( + ~mdIcon="timer", + ~section="Diagnostics", + ~hotkey="F7", + "Run Benchmark", + Benchmark(Start), + ), + ] + @ (if (ExerciseSettings.show_instructor) {instructor_shortcuts} else {[]}); + +let handle_key_event = (k: Key.t): option(UpdateAction.t) => { let now = (a: Action.t): option(UpdateAction.t) => Some(PerformAction(a)); switch (k) { @@ -19,7 +243,6 @@ let handle_key_event = (k: Key.t): option(Update.t) => { | {key: D(key), sys: _, shift: Down, meta: Up, ctrl: Up, alt: Up} when is_f_key(key) => switch (key) { - | "F7" => Some(Benchmark(Start)) | _ => Some(DebugConsole(key)) } | {key: D(key), sys: _, shift, meta: Up, ctrl: Up, alt: Up} => @@ -35,7 +258,7 @@ let handle_key_event = (k: Key.t): option(Update.t) => { | (Up, "Escape") => now(Unselect(None)) | (Up, "Tab") => Some(TAB) | (Up, "F12") => now(Jump(BindingSiteOfIndicatedVar)) - | (Down, "Tab") => Some(MoveToNextHole(Left)) + | (Down, "Tab") => now(Move(Goal(Piece(Grout, Left)))) | (Down, "ArrowLeft") => now(Select(Resize(Local(Left(ByToken))))) | (Down, "ArrowRight") => now(Select(Resize(Local(Right(ByToken))))) | (Down, "ArrowUp") => now(Select(Resize(Local(Up)))) @@ -51,8 +274,6 @@ let handle_key_event = (k: Key.t): option(Update.t) => { } | {key: D(key), sys: Mac, shift: Down, meta: Down, ctrl: Up, alt: Up} => switch (key) { - | "Z" - | "z" => Some(Redo) | "ArrowLeft" => now(Select(Resize(Extreme(Left(ByToken))))) | "ArrowRight" => now(Select(Resize(Extreme(Right(ByToken))))) | "ArrowUp" => now(Select(Resize(Extreme(Up)))) @@ -61,8 +282,6 @@ let handle_key_event = (k: Key.t): option(Update.t) => { } | {key: D(key), sys: PC, shift: Down, meta: Up, ctrl: Down, alt: Up} => switch (key) { - | "Z" - | "z" => Some(Redo) | "ArrowLeft" => now(Select(Resize(Local(Left(ByToken))))) | "ArrowRight" => now(Select(Resize(Local(Right(ByToken))))) | "ArrowUp" => now(Select(Resize(Local(Up)))) @@ -77,9 +296,7 @@ let handle_key_event = (k: Key.t): option(Update.t) => { | "d" => now(Select(Term(Current))) | "p" => Some(PerformAction(Pick_up)) | "a" => now(Select(All)) - | "k" => Some(ReparseCurrentEditor) - | "/" => Some(Assistant(Prompt(TyDi))) - | _ when is_digit(key) => Some(SwitchScratchSlide(int_of_string(key))) + | "/" => Some(PerformAction(Buffer(Set(TyDi)))) | "ArrowLeft" => now(Move(Extreme(Left(ByToken)))) | "ArrowRight" => now(Move(Extreme(Right(ByToken)))) | "ArrowUp" => now(Move(Extreme(Up))) @@ -92,9 +309,7 @@ let handle_key_event = (k: Key.t): option(Update.t) => { | "d" => now(Select(Term(Current))) | "p" => Some(PerformAction(Pick_up)) | "a" => now(Select(All)) - | "k" => Some(ReparseCurrentEditor) - | "/" => Some(Assistant(Prompt(TyDi))) - | _ when is_digit(key) => Some(SwitchScratchSlide(int_of_string(key))) + | "/" => Some(PerformAction(Buffer(Set(TyDi)))) | "ArrowLeft" => now(Move(Local(Left(ByToken)))) | "ArrowRight" => now(Move(Local(Right(ByToken)))) | "Home" => now(Move(Extreme(Up))) @@ -107,13 +322,18 @@ let handle_key_event = (k: Key.t): option(Update.t) => { | "e" => now(Move(Extreme(Right(ByToken)))) | _ => None } - | {key: D(key), sys, shift: Up, meta: Up, ctrl: Up, alt: Down} => - switch (sys, key) { - | (_, "ArrowLeft") => now(MoveToBackpackTarget(Left(ByToken))) - | (_, "ArrowRight") => now(MoveToBackpackTarget(Right(ByToken))) - | (_, "Alt") => Some(SetMeta(ShowBackpackTargets(true))) - | (_, "ArrowUp") => now(MoveToBackpackTarget(Up)) - | (_, "ArrowDown") => now(MoveToBackpackTarget(Down)) + | {key: D("f"), sys: PC, shift: Up, meta: Up, ctrl: Up, alt: Down} => + Some(PerformAction(Project(ToggleIndicated(Fold)))) + | {key: D("ƒ"), sys: Mac, shift: Up, meta: Up, ctrl: Up, alt: Down} => + /* Curly ƒ is what holding option turns f into on Mac */ + Some(PerformAction(Project(ToggleIndicated(Fold)))) + | {key: D(key), sys: _, shift: Up, meta: Up, ctrl: Up, alt: Down} => + switch (key) { + | "ArrowLeft" => now(MoveToBackpackTarget(Left(ByToken))) + | "ArrowRight" => now(MoveToBackpackTarget(Right(ByToken))) + | "Alt" => Some(SetMeta(ShowBackpackTargets(true))) + | "ArrowUp" => now(MoveToBackpackTarget(Up)) + | "ArrowDown" => now(MoveToBackpackTarget(Down)) | _ => None } | _ => None diff --git a/src/haz3lweb/Log.re b/src/haz3lweb/Log.re index 83876619ef..7c87a640f6 100644 --- a/src/haz3lweb/Log.re +++ b/src/haz3lweb/Log.re @@ -1,6 +1,6 @@ /* Logging system for actions. Persists log via IndexedDB */ -open Sexplib.Std; +open Util; let is_action_logged: UpdateAction.t => bool = fun @@ -8,27 +8,22 @@ let is_action_logged: UpdateAction.t => bool = | Save | InitImportAll(_) | InitImportScratchpad(_) - | ExportPersistentData + | Export(_) | FinishImportAll(_) | FinishImportScratchpad(_) | Benchmark(_) - | DebugConsole(_) => false + | DebugConsole(_) + | Startup => false | Reset | TAB - | Assistant(_) | Set(_) | SwitchScratchSlide(_) | SwitchDocumentationSlide(_) | SwitchEditor(_) | ResetCurrentEditor - | ReparseCurrentEditor | PerformAction(_) - | Cut - | Copy - | Paste(_) | Undo | Redo - | MoveToNextHole(_) | UpdateResult(_) | ToggleStepper(_) | StepperAction(_, StepForward(_) | StepBackward) diff --git a/src/haz3lweb/LogEntry.re b/src/haz3lweb/LogEntry.re index 948c88779e..bf7d9dfd59 100644 --- a/src/haz3lweb/LogEntry.re +++ b/src/haz3lweb/LogEntry.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), yojson, sexp)] type t = (float, UpdateAction.t); diff --git a/src/haz3lweb/Main.re b/src/haz3lweb/Main.re index e1268431af..af8058b770 100644 --- a/src/haz3lweb/Main.re +++ b/src/haz3lweb/Main.re @@ -1,28 +1,12 @@ +open Util; open Js_of_ocaml; -open Incr_dom; open Haz3lweb; +open Bonsai.Let_syntax; let scroll_to_caret = ref(true); let edit_action_applied = ref(true); let last_edit_action = ref(JsUtil.timestamp()); -let observe_font_specimen = (id, update) => - ResizeObserver.observe( - ~node=JsUtil.get_elem_by_id(id), - ~f= - (entries, _) => { - let specimen = Js.to_array(entries)[0]; - let rect = specimen##.contentRect; - update( - Haz3lweb.FontMetrics.{ - row_height: rect##.bottom -. rect##.top, - col_width: rect##.right -. rect##.left, - }, - ); - }, - (), - ); - let restart_caret_animation = () => // necessary to trigger reflow // @@ -35,7 +19,7 @@ let restart_caret_animation = () => | _ => () }; -let apply = (model, action, state, ~schedule_action): Model.t => { +let apply = (model, action, ~schedule_action): Model.t => { restart_caret_animation(); if (UpdateAction.is_edit(action)) { last_edit_action := JsUtil.timestamp(); @@ -47,7 +31,7 @@ let apply = (model, action, state, ~schedule_action): Model.t => { last_edit_action := JsUtil.timestamp(); switch ( try({ - let new_model = Update.apply(model, action, state, ~schedule_action); + let new_model = Update.apply(model, action, ~schedule_action); Log.update(action); new_model; }) { @@ -61,9 +45,7 @@ let apply = (model, action, state, ~schedule_action): Model.t => { ) { | Ok(model) => model | Error(FailedToPerform(err)) => - // TODO(andrew): reinstate this history functionality print_endline(Update.Failure.show(FailedToPerform(err))); - //{...model, history: ActionHistory.failure(err, model.history)}; model; | Error(err) => print_endline(Update.Failure.show(err)); @@ -71,73 +53,63 @@ let apply = (model, action, state, ~schedule_action): Model.t => { }; }; -module App = { - module Model = Model; - module Action = Update; - module State = State; - - let on_startup = (~schedule_action, m: Model.t) => { - let _ = - observe_font_specimen("font-specimen", fm => - schedule_action(Haz3lweb.Update.SetMeta(FontMetrics(fm))) - ); - - JsUtil.focus_clipboard_shim(); - - /* initialize state. */ - let state = State.init(); - - /* Initial evaluation on a worker */ - Update.schedule_evaluation(~schedule_action, m); +let app = + Bonsai.state_machine0( + (module Model), + (module Update), + ~apply_action= + (~inject, ~schedule_event) => + apply(~schedule_action=x => schedule_event(inject(x))), + ~default_model=Model.load(Model.blank), + ); - Os.is_mac := - Dom_html.window##.navigator##.platform##toUpperCase##indexOf( - Js.string("MAC"), - ) - >= 0; - Async_kernel.Deferred.return(state); +/* This subcomponent is used to run an effect once when the app starts up, + After the first draw */ +let on_startup = effect => { + let%sub startup_completed = Bonsai.toggle'(~default_model=false); + let%sub after_display = { + switch%sub (startup_completed) { + | {state: false, set_state, _} => + let%arr effect = effect + and set_state = set_state; + Bonsai.Effect.Many([set_state(true), effect]); + | {state: true, _} => Bonsai.Computation.return(Ui_effect.Ignore) + }; }; + Bonsai.Edge.after_display(after_display); +}; - let create = - ( - model: Incr.t(Haz3lweb.Model.t), - ~old_model as _: Incr.t(Haz3lweb.Model.t), - ~inject, - ) => { - open Incr.Let_syntax; - let%map model = model; - /* Note: mapping over the old_model here may - trigger an additional redraw */ - Component.create( - ~apply_action=apply(model), - model, - Haz3lweb.Page.view(~inject, model), - ~on_display=(_, ~schedule_action) => { - if (edit_action_applied^ - && JsUtil.timestamp() - -. last_edit_action^ > 1000.0) { - /* If an edit action has been applied, but no other edit action - has been applied for 1 second, save the model. */ - edit_action_applied := false; - print_endline("Saving..."); - schedule_action(Update.Save); - }; - if (scroll_to_caret.contents) { - scroll_to_caret := false; - JsUtil.scroll_cursor_into_view_if_needed(); - }; - }, +let view = { + let%sub app = app; + let%sub () = { + on_startup( + Bonsai.Value.map(~f=((_model, inject)) => inject(Startup), app), ); }; + let%sub after_display = { + let%arr (_model, inject) = app; + if (scroll_to_caret.contents) { + scroll_to_caret := false; + JsUtil.scroll_cursor_into_view_if_needed(); + }; + if (edit_action_applied^ + && JsUtil.timestamp() + -. last_edit_action^ > 1000.0) { + /* If an edit action has been applied, but no other edit action + has been applied for 1 second, save the model. */ + edit_action_applied := false; + print_endline("Saving..."); + inject(Update.Save); + } else { + Ui_effect.Ignore; + }; + }; + let%sub () = Bonsai.Edge.after_display(after_display); + let%arr (model, inject) = app; + Haz3lweb.Page.view(~inject, model); }; switch (JsUtil.Fragment.get_current()) { | Some("debug") => DebugMode.go() -| _ => - Incr_dom.Start_app.start( - (module App), - ~debug=false, - ~bind_to_element_with_id="container", - ~initial_model=Model.load(Model.blank), - ) +| _ => Bonsai_web.Start.start(view, ~bind_to_element_with_id="container") }; diff --git a/src/haz3lweb/Model.re b/src/haz3lweb/Model.re index 65c5d519c0..e4939b3af0 100644 --- a/src/haz3lweb/Model.re +++ b/src/haz3lweb/Model.re @@ -1,4 +1,5 @@ -open Sexplib.Std; +open Util; + open Haz3lcore; /* MODEL: @@ -32,28 +33,26 @@ let ui_state_init = { mousedown: false, }; +[@deriving sexp] type t = { editors: Editors.t, settings: Settings.t, results: ModelResults.t, - statics: CachedStatics.t, explainThisModel: ExplainThisModel.t, ui_state, }; -let cutoff = (===); +let equal = (===); -let mk = (editors, results, statics) => { +let mk = (editors, results) => { editors, settings: Init.startup.settings, results, - statics, explainThisModel: ExplainThisModel.init, ui_state: ui_state_init, }; -let blank = - mk(Editors.Scratch(0, []), ModelResults.empty, CachedStatics.empty); +let blank = mk(Editors.Scratch(0, []), ModelResults.empty); let load_editors = (~settings, ~mode: Settings.mode, ~instructor_mode: bool) @@ -68,6 +67,7 @@ let load_editors = | Exercises => let (n, specs, exercise) = Store.Exercise.load( + ~settings, ~specs=ExerciseSettings.exercises, ~instructor_mode, ); @@ -90,13 +90,12 @@ let load = (init_model: t): t => { let explainThisModel = Store.ExplainThisModel.load(); let (editors, results) = load_editors( - ~settings=settings.core.evaluation, + ~settings=settings.core, ~mode=settings.mode, ~instructor_mode=settings.instructor_mode, ); let ui_state = init_model.ui_state; - let statics = Editors.mk_statics(~settings, editors); - {editors, settings, results, statics, explainThisModel, ui_state}; + {editors, settings, results, explainThisModel, ui_state}; }; let save = ({editors, settings, explainThisModel, results, _}: t) => { @@ -109,16 +108,16 @@ let save_and_return = (model: t) => { save(model); Ok(model); }; + let reset = (model: t): t => { /* Reset model to default, including in localstorage, but don't otherwise erase localstorage, allowing e.g. api keys to persist */ - let settings = Store.Settings.init(); - ignore(settings); + let settings = Store.Settings.init().core; ignore(Store.ExplainThisModel.init()); - ignore(Store.Scratch.init(~settings=settings.core.evaluation)); - ignore(Store.Documentation.init(~settings=settings.core.evaluation)); - ignore(Store.Exercise.init(~instructor_mode=true)); + ignore(Store.Scratch.init(~settings)); + ignore(Store.Documentation.init(~settings)); + ignore(Store.Exercise.init(~settings, ~instructor_mode=true)); let new_model = load(blank); { ...new_model, diff --git a/src/haz3lweb/NinjaKeys.re b/src/haz3lweb/NinjaKeys.re new file mode 100644 index 0000000000..acce5c4ff4 --- /dev/null +++ b/src/haz3lweb/NinjaKeys.re @@ -0,0 +1,57 @@ +open Js_of_ocaml; +open Util; + +/* + Configuration of the command palette using the https://github.com/ssleptsov/ninja-keys web component. + */ + +let from_shortcut = + (schedule_action: UpdateAction.t => unit, shortcut: Keyboard.shortcut) + : { + . + "handler": Js.readonly_prop(unit => unit), + "id": Js.readonly_prop(string), + "mdIcon": Js.readonly_prop(Js.optdef(string)), + "hotkey": Js.readonly_prop(Js.optdef(string)), + "title": Js.readonly_prop(string), + "section": Js.readonly_prop(Js.optdef(string)), + } => { + [%js + { + val id = shortcut.label; + val title = shortcut.label; + val mdIcon = Js.Optdef.option(shortcut.mdIcon); + val hotkey = Js.Optdef.option(shortcut.hotkey); + val section = Js.Optdef.option(shortcut.section); + val handler = + () => { + let foo = shortcut.update_action; + switch (foo) { + | Some(update) => schedule_action(update) + | None => + print_endline("Could not find action for " ++ shortcut.label) + }; + } + }]; +}; + +let options = (schedule_action: UpdateAction.t => unit) => { + Array.of_list( + List.map( + from_shortcut(schedule_action), + Keyboard.shortcuts(Os.is_mac^ ? Mac : PC), + ), + ); +}; + +let elem = () => JsUtil.get_elem_by_id("ninja-keys"); + +let initialize = opts => Js.Unsafe.set(elem(), "data", Js.array(opts)); + +let open_command_palette = (): unit => { + Js.Unsafe.meth_call( + elem(), + "open", + [||] // Can't use ##.open because open is a reserved keyword + ); +}; diff --git a/src/haz3lweb/PersistentData.re b/src/haz3lweb/PersistentData.re index 6e7b1a4419..8b606f4d17 100644 --- a/src/haz3lweb/PersistentData.re +++ b/src/haz3lweb/PersistentData.re @@ -1,4 +1,5 @@ -open Sexplib.Std; +open Util; + open Haz3lcore; [@deriving (show({with_path: false}), sexp, yojson)] diff --git a/src/haz3lweb/ScratchSlide.re b/src/haz3lweb/ScratchSlide.re index 09860711ed..554beab53d 100644 --- a/src/haz3lweb/ScratchSlide.re +++ b/src/haz3lweb/ScratchSlide.re @@ -8,49 +8,45 @@ type persistent_state = PersistentZipper.t; let scratch_key = n => "scratch_" ++ n; -let persist = (editor: Editor.t) => { +let persist = (editor: Editor.t): persistent_state => { PersistentZipper.persist(editor.state.zipper); }; -let unpersist = (zipper: persistent_state) => { +let unpersist = (zipper: persistent_state, ~settings: CoreSettings.t): state => { let zipper = PersistentZipper.unpersist(zipper); - Editor.init(zipper, ~read_only=false); + Editor.init(zipper, ~read_only=false, ~settings); }; -let serialize = (state: state) => { +let serialize = (state: state): string => { persist(state) |> sexp_of_persistent_state |> Sexplib.Sexp.to_string; }; -let deserialize = (data: string) => { - Sexplib.Sexp.of_string(data) |> persistent_state_of_sexp |> unpersist; +let deserialize = (data: string, ~settings: CoreSettings.t): state => { + Sexplib.Sexp.of_string(data) + |> persistent_state_of_sexp + |> unpersist(~settings); }; -let deserialize_opt = (data: string) => { +let deserialize_opt = + (data: string, ~settings: CoreSettings.t): option(state) => { let sexp = try(Some(Sexplib.Sexp.of_string(data) |> persistent_state_of_sexp)) { | _ => None }; - sexp |> Option.map(sexp => sexp |> unpersist); + sexp |> Option.map(sexp => sexp |> unpersist(~settings)); }; -let export = (state: state) => { +let export = (state: state): Yojson.Safe.t => { state |> persist |> yojson_of_persistent_state; }; -let import = (data: string) => { - data |> Yojson.Safe.from_string |> persistent_state_of_yojson |> unpersist; +let import = (data: string, ~settings: CoreSettings.t): state => { + data + |> Yojson.Safe.from_string + |> persistent_state_of_yojson + |> unpersist(~settings); }; -let export_init = (state: state) => { +let export_init = (state: state): string => { state |> persist |> show_persistent_state; }; - -let mk_statics = - (~settings: Settings.t, editor: Editor.t, ctx_init: Ctx.t) - : CachedStatics.statics => { - let term = MakeTerm.from_zip_for_sem(editor.state.zipper) |> fst; - let info_map = Interface.Statics.mk_map_ctx(settings.core, ctx_init, term); - let error_ids = - Statics.Map.error_ids(editor.state.meta.term_ranges, info_map); - {term, info_map, error_ids}; -}; diff --git a/src/haz3lweb/SerializedExamples.ml b/src/haz3lweb/SerializedExamples.ml deleted file mode 100644 index a9a06cdc0e..0000000000 --- a/src/haz3lweb/SerializedExamples.ml +++ /dev/null @@ -1,6602 +0,0 @@ -let intro : ScratchSlide.persistent_state = - { - zipper = - "((selection((focus \ - Left)(content())))(backpack())(relatives((siblings(((Secondary((id \ - b9251f54-0572-4fe1-8cac-62fb931a53b2)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - ccf2ec6f-12f5-4ef7-929a-7c012d318017)(content(Comment\"# Fill the hole \ - below to see how the result changes #\"))))(Secondary((id \ - 6276ade7-a655-4502-a46e-e72c4177bfc6)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 1f723cf6-4652-4cb9-89b5-661813257eae)(label(fun ->))(mold((out \ - Exp)(in_(Pat))(nibs(((shape Convex)(sort Exp))((shape(Concave 13))(sort \ - Exp))))))(shards(0 1))(children(((Secondary((id \ - 55148166-9c62-4ea8-8cf5-043aabe0e0b8)(content(Whitespace\" \ - \"))))(Tile((id \ - 96bcf1dd-82d6-43ce-ba9c-664c4c068615)(label(parameter))(mold((out \ - Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape Convex)(sort \ - Pat))))))(shards(0))(children())))(Secondary((id \ - a07c8043-d0c0-4069-879c-c33dee22847d)(content(Whitespace\" \ - \")))))))))(Grout((id 45147365-5339-4904-aabe-8290175e5e39)(shape \ - Convex)))(Secondary((id \ - 00473032-3cde-499f-ae11-4708be84b390)(content(Whitespace\" \ - \"))))(Secondary((id \ - 5eb554ba-4942-488f-9826-abade5f042df)(content(Whitespace\" \ - \"))))(Secondary((id \ - 6d1a22f3-90d2-4146-9620-43a7b7d9ccf5)(content(Whitespace\" \ - \"))))(Secondary((id \ - 158bc283-207e-48dc-8698-0127fa160027)(content(Whitespace\" \ - \"))))(Secondary((id \ - 8276ac3c-a531-4514-a115-2920b4b042ab)(content(Whitespace\" \ - \")))))((Secondary((id \ - 0fb51e6f-b503-4644-948e-2c732b0d7449)(content(Whitespace\"\\226\\143\\142\")))))))(ancestors((((id \ - f775bd7f-924f-4f6e-971b-faf4bfa5e7bf)(label(let = in))(mold((out \ - Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 16))(sort Exp))))))(shards((0 1)(2)))(children((((Secondary((id \ - d8980118-1d06-488a-8d30-70fcaef3b222)(content(Whitespace\" \ - \"))))(Tile((id \ - 0fba90cc-14a6-4875-8202-2ad99c8bd32d)(label(your_function))(mold((out \ - Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape Convex)(sort \ - Pat))))))(shards(0))(children())))(Secondary((id \ - cdc8c1f4-8083-471e-8eda-8930ec220ec5)(content(Whitespace\" \ - \"))))))())))(((Secondary((id \ - fae0774c-bdf8-4c16-ac1b-c50a5055ca24)(content(Comment\"# Welcome to \ - Hazel! #\"))))(Secondary((id \ - 123e0d9d-ccc1-43ee-a103-198ddcfae6da)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 025eef96-0b83-4c26-a631-c21bc7072426)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 1f5ba227-90b2-4e6b-91de-6e51a762cbb3)(content(Comment\"# This is a \ - program cell, which consists of a structured editor \ - #\"))))(Secondary((id \ - a22c4492-9a92-4edb-bb41-c5682786b8b1)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - c5273d3b-06b3-44f1-8354-00e22148aebe)(content(Comment\"# at the top and \ - its evaluated result at the bottom. Right now, #\"))))(Secondary((id \ - 7ce45bad-c2c5-43fe-8961-94fc4946ced0)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - ceffe652-5515-4c66-81e9-5938fac19452)(content(Comment\"# that result \ - has a question mark, as the program is incomplete! \ - #\"))))(Secondary((id \ - 0984263c-d942-4067-8f4a-90e6ca915037)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 72e18dcf-bc6a-4d6a-9efa-e78bec8fded8)(content(Whitespace\"\\226\\143\\142\")))))((Secondary((id \ - 5c6b47d0-7e57-453c-ae6f-8b0ae564772e)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - b4e68023-dfe1-4c0f-837e-a6bfaf6f2072)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 357a9315-e11e-45bd-a53f-f6b6f0feb682)(content(Comment\"# Here in \ - Scratch Mode, you can use the upper left arrows to \ - #\"))))(Secondary((id \ - 921b3b05-452d-46e5-b8d5-8685d269cbdc)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - c9cf2328-c2fc-4848-810c-d9185f0a8f37)(content(Comment\"# switch between \ - blank cells where you can store programs. #\"))))(Secondary((id \ - aa945ef1-522b-4660-aedb-c128b76d2982)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - c79a6006-21b0-4106-b78d-cb8ba4495536)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - c9d02ee3-46a3-493a-8698-88bcea88c1a9)(content(Comment\"# Select \ - Documentation Mode from the upper left dialog to pick from \ - #\"))))(Secondary((id \ - 92c2e652-d433-49c9-8e8d-32a9a84f5698)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 27b9d738-b928-4f10-a684-07f76110935c)(content(Comment\"# a list of \ - references for Hazel language and editor features. \ - #\"))))(Secondary((id \ - cd239f32-f9c9-4365-9e78-4d053c43b23e)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - b64056cb-5c7c-4445-88cb-b46323c3c6fb)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - f1b08303-7966-443a-b963-5e24d80f523b)(content(Comment\"# Select \ - Exercise for a small functional programming tutorial. \ - #\"))))(Secondary((id \ - ab8fcf3e-d7ec-487c-8bf3-36ab715f4323)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 50a218b1-3d72-4f84-9fd9-482994d25118)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 08025fa9-be2c-48e3-a05b-2f678af6685f)(label(your_function))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Tile((id \ - 334de073-5f71-44e9-87ed-009942123797)(label(\"(\"\")\"))(mold((out \ - Exp)(in_(Exp))(nibs(((shape(Concave 1))(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0 1))(children(((Tile((id \ - 15b1c8c9-af39-4613-a436-417ce09ef2c5)(label(\"\\\"argument\\\"\"))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children()))))))))(Secondary((id \ - d558bece-07ea-4d53-b9f2-8ba388a1a283)(content(Whitespace\" \ - \"))))(Tile((id \ - d93d43ee-e791-409a-886d-bc1cd6329b87)(label(+))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 5))(sort Exp))((shape(Concave 5))(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - 0cff6d10-120f-43f2-bdce-3e33fb6f9cd7)(content(Whitespace\" \ - \"))))(Tile((id \ - a560ecfa-e4aa-4775-a478-b9ee8e347c6c)(label(1))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - 5d2e9e0b-1fa0-4ce8-9f23-d78f444a4884)(content(Whitespace\"\\226\\143\\142\")))))))))))(caret \ - Outer))"; - backup_text = - "# Welcome to Hazel! #\n\n\ - # This is a program cell, which consists of a structured editor #\n\ - # at the top and its evaluated result at the bottom. Right now, #\n\ - # that result has a question mark, as the program is incomplete! #\n\n\ - let your_function =\n\ - # Fill the hole below to see how the result changes #\n\ - fun parameter -> \n\ - in\n\n\ - # Here in Scratch Mode, you can use the upper left arrows to #\n\ - # switch between blank cells where you can store programs. #\n\n\ - # Select Documentation Mode from the upper left dialog to pick from #\n\ - # a list of references for Hazel language and editor features. #\n\n\ - # Select Exercise for a small functional programming tutorial. #\n\n\ - your_function(\"argument\") + 1\n"; - } - -let lang_ref : ScratchSlide.persistent_state = - { - zipper = - "((selection((focus \ - Left)(content())))(backpack())(relatives((siblings(((Secondary((id \ - 730349ac-e60d-4709-880c-dd589d7c101a)(content(Comment\"# Hazel Language \ - Quick Reference #\"))))(Secondary((id \ - 49dc2ef0-9035-4241-9454-c61f36819a8d)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 041559ff-afa2-4048-a74d-a17fada7722a)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 0afac91c-68c7-493c-b662-9e8857497774)(content(Comment\"# Empty holes \ - stand for missing expressions, patterns, or types #\"))))(Secondary((id \ - 2fc656e6-3eee-4881-a3de-adb9cbd9658f)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 89590b3e-217a-4b40-a95e-fe7f9f4a782e)(label(let = in))(mold((out \ - Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 16))(sort Exp))))))(shards(0 1 2))(children(((Secondary((id \ - ffb9c1b1-a047-408c-a38e-c0d413dab783)(content(Whitespace\" \ - \"))))(Tile((id \ - 8bbeb975-5b79-4116-b879-4fda936742c4)(label(empty_hole))(mold((out \ - Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape Convex)(sort \ - Pat))))))(shards(0))(children())))(Secondary((id \ - 3c417b09-25af-42cd-8145-ac78bf0953a5)(content(Whitespace\" \ - \")))))((Grout((id d1f97dd0-a8f9-4920-b802-eae9fb75ed70)(shape \ - Convex)))(Secondary((id \ - adcf5a35-edef-43d1-94eb-5da5e89416f5)(content(Whitespace\" \ - \"))))(Secondary((id \ - c796602b-34f2-43cd-8da7-3c72e50ab1da)(content(Whitespace\" \ - \"))))(Secondary((id \ - 19e522ea-b089-4889-b551-010504de631e)(content(Whitespace\" \ - \")))))))))(Secondary((id \ - 198a76fd-8df5-4bb0-9b63-53a983d0db4b)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 59c740ca-a615-4122-b5f8-22e1cbac5898)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 6df41542-18c0-4fdc-bda7-c904b83c0609)(content(Comment\"# Integers \ - #\"))))(Secondary((id \ - 41b32d62-837d-4b13-8776-364198e07ea8)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - d80b1d9f-cbe2-46ae-84a4-80fc374737ea)(label(let = in))(mold((out \ - Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 16))(sort Exp))))))(shards(0 1 2))(children(((Secondary((id \ - 5946b974-f91c-4f5d-b341-c482680ce716)(content(Whitespace\" \ - \"))))(Tile((id \ - 46fea074-f37b-4986-b0f1-d0b3b6f91f4b)(label(int_lits))(mold((out \ - Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape Convex)(sort \ - Pat))))))(shards(0))(children())))(Secondary((id \ - 611f6504-ff1a-4a3d-8d80-90b100334744)(content(Whitespace\" \ - \"))))(Tile((id \ - 9ce47d22-54cb-4297-8bd5-a568eb1cc0f0)(label(:))(mold((out \ - Pat)(in_())(nibs(((shape(Concave 11))(sort Pat))((shape(Concave \ - 11))(sort Typ))))))(shards(0))(children())))(Secondary((id \ - 4cc0d2d3-d055-4c66-a1e7-f719778a15d3)(content(Whitespace\" \ - \"))))(Tile((id \ - ccf4a8f9-20b7-4288-9752-3550b1ba4000)(label(Int))(mold((out \ - Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape Convex)(sort \ - Typ))))))(shards(0))(children())))(Secondary((id \ - 18602542-b079-472e-aa9d-c36f12ccd2fb)(content(Whitespace\" \ - \")))))((Secondary((id \ - b5e05450-0b26-4117-a5bf-1d4e2a1433a8)(content(Whitespace\" \ - \"))))(Tile((id \ - eac9f3b2-903d-40ec-a22d-88fcb915f572)(label(1))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - a054b1bc-bc8a-4ebd-9bb6-bf4c4c7f15e7)(content(Whitespace\" \ - \")))))))))(Secondary((id \ - 83b39678-45a1-4734-a395-13cd51c98fa7)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - babb54a1-0f72-4523-97b8-463c4fe84107)(label(let = in))(mold((out \ - Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 16))(sort Exp))))))(shards(0 1 2))(children(((Secondary((id \ - 29a28da9-1be2-48f3-8e8e-69898cfb354f)(content(Whitespace\" \ - \"))))(Tile((id \ - 66439099-9690-4957-93ed-bea104dffb6f)(label(negation))(mold((out \ - Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape Convex)(sort \ - Pat))))))(shards(0))(children())))(Secondary((id \ - df90f7c7-e936-4197-a475-2e815bc34507)(content(Whitespace\" \ - \")))))((Secondary((id \ - ab0250b5-eaf7-4a82-a94b-49029d060db5)(content(Whitespace\" \ - \"))))(Tile((id \ - 143aefd1-15d5-48a1-a98a-bbd01ef572d7)(label(-))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape(Concave 2))(sort \ - Exp))))))(shards(0))(children())))(Tile((id \ - 083dcc77-d37e-4671-ba14-3e7e9686bdc7)(label(1))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - 0f543d14-f1ff-498f-8fd0-fb239592eaa5)(content(Whitespace\" \ - \")))))))))(Secondary((id \ - aa31fe00-7df3-487d-8b15-222aa43adb1a)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 30bbd09e-f382-4a72-acea-a85cf5f7fef5)(label(let = in))(mold((out \ - Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 16))(sort Exp))))))(shards(0 1 2))(children(((Secondary((id \ - 133796c3-d6df-49af-bacb-9f70b7bc7384)(content(Whitespace\" \ - \"))))(Tile((id \ - 68b715a2-a0e6-44aa-a430-3b27a70799f7)(label(arithmetic))(mold((out \ - Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape Convex)(sort \ - Pat))))))(shards(0))(children())))(Secondary((id \ - 4886d833-0f8f-4b37-990f-d3c37fddcba7)(content(Whitespace\" \ - \")))))((Secondary((id \ - f50acb7d-b186-49aa-9a8c-57a0a24a44b8)(content(Whitespace\" \ - \"))))(Tile((id \ - 2b249c3b-ce53-4495-a161-6bd5c3892b9f)(label(1))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Tile((id \ - 348e2fe7-189a-41cc-95d1-14f0b7996bfb)(label(*))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 4))(sort Exp))((shape(Concave 4))(sort \ - Exp))))))(shards(0))(children())))(Tile((id \ - 844c7db4-ba8f-4f17-87ad-878d4bd17e30)(label(2))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - feba3b62-3607-42c9-95e6-db2939b96fa3)(content(Whitespace\" \ - \"))))(Tile((id \ - 9006a5e7-b926-445d-b563-a45557932cff)(label(+))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 5))(sort Exp))((shape(Concave 5))(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - a7f455d7-1de4-4f08-a466-8add97175cf9)(content(Whitespace\" \ - \"))))(Tile((id \ - 8fddaf22-32d1-4344-9d3c-5654345ff194)(label(8))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Tile((id \ - 0d68cccc-d91e-44e1-a1cd-9acab10ea3e0)(label(/))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 4))(sort Exp))((shape(Concave 4))(sort \ - 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91a26142-fec9-4202-8083-ce43ee859ef1)(content(Whitespace\"\\226\\143\\142\")))))))))(Secondary((id \ - 1b844c00-c103-4352-9ffd-545597fcbab9)(content(Whitespace\" \ - \"))))(Secondary((id \ - 152260e3-cadf-47bd-891e-630e295f2b11)(content(Whitespace\" \ - \"))))(Secondary((id \ - c39fdd63-77af-4314-ac6d-b2d2ca456223)(content(Whitespace\" \ - \"))))(Secondary((id \ - 14d295c3-8e01-45cc-ba09-05686c68717f)(content(Whitespace\" \ - \"))))(Secondary((id \ - b89b26d6-0e17-436c-a3f5-2bfda761556f)(content(Whitespace\"\\226\\143\\142\")))))))))(Secondary((id \ - 9f2c44f5-9592-4493-be4e-2fab4c1bc6d1)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - fdda5cd2-dfd8-42ef-a015-36fdf6ceff5c)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 47be7d24-9c1b-4d99-a506-186d09caca38)(content(Comment\"# Strings \ - #\"))))(Secondary((id \ - e5920639-6f72-462f-9ace-472f697ec5c9)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - fc57de4a-8eb2-41e9-a00a-7e80557c1151)(label(let = in))(mold((out \ - 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750f6a54-6a20-4199-af48-61167bfac6b0)(label(let = in))(mold((out \ - Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 16))(sort Exp))))))(shards(0 1 2))(children(((Secondary((id \ - da76aec1-c42c-4335-bade-aaa9cf6d64fb)(content(Whitespace\" \ - \"))))(Tile((id \ - 9a31cf84-5cc6-47b9-9216-e1f7a41a85d9)(label(string_equality))(mold((out \ - Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape Convex)(sort \ - Pat))))))(shards(0))(children())))(Secondary((id \ - dcb9b766-a27e-4230-8bf5-412ecef84807)(content(Whitespace\" \ - \")))))((Secondary((id \ - 161f081f-7857-4822-b311-4ce3ceec5fec)(content(Whitespace\" \ - \"))))(Tile((id \ - acef69a6-c5ec-491a-aeee-40e2269f20bf)(label(string_lits))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - 9ca3be7e-d452-411f-b881-7c5cdd47bfd6)(content(Whitespace\" \ - \"))))(Tile((id \ - 139cbd33-8e7b-4662-97d4-52cd6972d008)(label($==))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 8))(sort Exp))((shape(Concave 8))(sort \ - 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run programs with non-empty holes) #\"))))(Secondary((id \ - 7ddbefad-5673-491f-9701-8355a1921825)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - f5209603-f090-4226-87cd-8d00c02ac94c)(label(let = in))(mold((out \ - Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 16))(sort Exp))))))(shards(0 1 2))(children(((Secondary((id \ - 88cb0475-2152-486d-ac5d-413d1eb4b9c2)(content(Whitespace\" \ - \"))))(Tile((id \ - 2cf2e135-06e7-4ced-b965-42e6f33dfe08)(label(non_empty_hole))(mold((out \ - Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape Convex)(sort \ - Pat))))))(shards(0))(children())))(Secondary((id \ - e24f67ab-c23c-434a-a5b9-7dc6b41c22c3)(content(Whitespace\" \ - \"))))(Tile((id \ - 079133be-35b9-49c7-bfb8-6bd61f6a6618)(label(:))(mold((out \ - Pat)(in_())(nibs(((shape(Concave 11))(sort Pat))((shape(Concave \ - 11))(sort Typ))))))(shards(0))(children())))(Secondary((id \ - 41719850-1c9a-450b-b9cb-b831000c7ad5)(content(Whitespace\" \ - \"))))(Tile((id \ - 66fa6d78-d1ba-47fa-a859-0d307344784b)(label(Int))(mold((out \ - Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape Convex)(sort \ - Typ))))))(shards(0))(children())))(Secondary((id \ - 129584a6-02f7-44e4-afad-e15e6c93914f)(content(Whitespace\" \ - \")))))((Secondary((id \ - a90054e6-70d5-4e71-a16c-9e1e5b029164)(content(Whitespace\" \ - \"))))(Tile((id \ - 59760a21-433b-4652-b4e7-356c092764d6)(label(true))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - fa7fd5bb-899f-4777-b3f2-e0727a70d8df)(content(Whitespace\" \ - \")))))))))(Secondary((id \ - 92842ab4-35e8-4fa0-b405-1347fdab0d87)(content(Whitespace\" \ - \"))))(Secondary((id \ - 8cfd5cf2-dc3b-49af-a85f-5273fea40f84)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 55309b27-b446-44f5-bfb6-d1681645a40f)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - ed111d1b-8d83-496c-b6f1-c662495f0280)(label(2))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - 3856e751-c1ff-441e-bc58-bf6df6832fea)(content(Whitespace\" \ - \"))))(Tile((id \ - 5e441477-8d3b-40c9-9ef6-85cf64d4d495)(label(+))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 5))(sort Exp))((shape(Concave 5))(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - bdb433dc-43b2-436d-aabd-cf4eb0b59abc)(content(Whitespace\" \ - \"))))(Tile((id \ - 82eb3ff2-38ef-470c-b4ce-3f0058df33fc)(label(2))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - b74bd612-434d-4e6b-9a63-d3404c195ed6)(content(Whitespace\"\\226\\143\\142\")))))()))(ancestors())))(caret \ - Outer))"; - backup_text = - "# Hazel Language Quick Reference #\n\n\ - # Empty holes stand for missing expressions, patterns, or types #\n\ - let empty_hole = in\n\n\ - # Integers #\n\ - let int_lits : Int = 1 in\n\ - let negation = -1 in\n\ - let arithmetic = 1*2 + 8/4 in\n\ - let int_comparison = (10 == 10, 1 < 2, 2 <= 3, 3 > 2, 2 >= 1) in\n\n\ - # Floating Point Numbers #\n\ - let float_lits : Float = 1.5 in\n\ - let float_artih = 1. *. 2. +. 8. /. 4. in\n\ - let float_comparison = (10. ==. 10., 1. <. 2., 2. <=. 3., 3. >. 2., 2. \ - >=. 1.) in\n\n\ - # Booleans #\n\ - let booleans : (Bool, Bool) = (true, false) in\n\ - let conditionals =\n\ - let (x, y) = (2 + 2, 3 + 3) in\n\ - if y > x then 1 \n\ - else 2 \n\ - in\n\n\ - # Tuples #\n\ - let tuples : (Int, Bool, (Bool, Int)) = (1, true, (false, 3)) in\n\ - let (a, b, (c, d)) = tuples in\n\n\ - # Functions #\n\ - let y : (Int, Int, Int) -> Int =\n\ - fun (m, x, b) -> m * x + b \n\ - in\n\n\ - # Recursive Functions (arrow type annotation required) #\n\ - let double_recursively : Int -> Int =\n\ - fun n ->\n\ - if n == 0 then 0 \n\ - else double_recursively(n - 1) + 2 \n\ - in\n\n\ - # Lists #\n\ - let empty_list : [Int] = [] in\n\ - let non_empty_list : [Int] = 1::2::3::[] in\n\ - let list_literals : [Int] = [1, 2, 3] in\n\ - let length : [Int] -> Int =\n\ - fun xs ->\n\ - case xs\n\ - | [] => 0\n\ - | hd::tl => 1 + length(tl) \n\ - end \n\ - in\n\ - let has_at_least_two_elements : [Int] -> Bool =\n\ - fun xs ->\n\ - case xs\n\ - | [] => false\n\ - | hd::[] => false\n\ - | a::b::[] => true \n\ - end \n\ - in\n\n\ - # Strings #\n\ - let string_lits = \"Hello, world!\" in \n\ - let string_equality = string_lits $== \"Hello, world!\" in \n\n\ - # Non-empty holes are the red dotted boxes around errors #\n\ - # (you can still run programs with non-empty holes) #\n\ - let non_empty_hole : Int = true in \n\n\ - 2 + 2\n"; - } - -let basic_type_egs : ScratchSlide.persistent_state = - { - zipper = - "((selection((focus \ - Left)(content())))(backpack())(relatives((siblings(((Secondary((id \ - c2043ff7-8503-42d5-926b-ee72d7a9cf07)(content(Comment\"#Types and type \ - error examples#\"))))(Secondary((id \ - 234ce64b-d629-4f52-ba66-116edbcf266c)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 1f97626c-5e23-44cb-97dc-33909ae61f00)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - f52f9d2e-07a9-46ee-9b0d-7f452d1ded35)(label(let = in))(mold((out \ - Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 16))(sort Exp))))))(shards(0 1 2))(children(((Secondary((id \ - a2acb93a-8751-49ef-a473-ebc30a8f2b80)(content(Whitespace\" \ - \"))))(Tile((id \ - 2b148577-f026-4b59-8cf6-ddeb689b37f5)(label(_))(mold((out \ - Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape Convex)(sort \ - Pat))))))(shards(0))(children())))(Secondary((id \ - a436171a-1674-4d9d-aadf-4f202e27d8dc)(content(Whitespace\" \ - \")))))((Secondary((id \ - 434db6b8-5a17-4ea2-b44c-80b945771c07)(content(Whitespace\" \ - \"))))(Tile((id \ - 12e72cde-88c9-47c4-9a69-5b533c62498c)(label(unbound))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - 9ab88627-8297-4ec4-9843-1ccc57ff1ed1)(content(Whitespace\" \ - \")))))))))(Secondary((id \ - 7232ce1d-878b-4bfb-ba66-0ae36cceac75)(content(Whitespace\" \ - \"))))(Secondary((id \ - 28591e5e-0830-475e-b30d-adbbae27fd67)(content(Comment \ - #err#))))(Secondary((id \ - 3cf8c4b9-2843-4a94-91b8-33381f2576e7)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - be9a3885-aa4d-49f2-9020-98ec0507b8c9)(label(let = in))(mold((out \ - Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 16))(sort Exp))))))(shards(0 1 2))(children(((Secondary((id \ - f7908a7f-5b40-4333-a696-477bae785881)(content(Whitespace\" \ - \"))))(Tile((id \ - 2d05b473-7e04-43f9-8976-c02f4664d532)(label(Undefined))(mold((out \ - Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape Convex)(sort \ - Pat))))))(shards(0))(children())))(Secondary((id \ - edc67136-8a7f-4515-a39f-07217b6759b1)(content(Whitespace\" \ - \")))))((Secondary((id \ - 10c1af6b-c987-4201-bd17-b1be0981dd22)(content(Whitespace\" \ - \"))))(Tile((id \ - a82aedef-fd17-4637-a180-ba3929bd78e0)(label(Undefined))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - 69020ba5-e1b9-4119-9fed-ff32319486a7)(content(Whitespace\" \ - \")))))))))(Secondary((id \ - 1da1d71a-0fbe-45ea-8956-d9ab9ccb43df)(content(Whitespace\" \ - \"))))(Secondary((id \ - 0d0ac9d1-e9aa-46aa-9b8b-3fb3a163234d)(content(Comment\"# 2x \ - err#\"))))(Secondary((id \ - 4ed74594-a4b5-4e66-ab2b-e2793dd66163)(content(Whitespace\" \ - \"))))(Secondary((id \ - 5196890e-0727-400f-b399-f66886052b36)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 05c853a2-7441-4def-97bb-f365dee86795)(label(let = in))(mold((out \ - Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 16))(sort Exp))))))(shards(0 1 2))(children(((Secondary((id \ - fd75cdf6-0ebc-4147-9200-a3fd3246d006)(content(Whitespace\" \ - \"))))(Tile((id \ - cd2400cd-71a2-4131-a559-1af9980efbcd)(label(true))(mold((out \ - Pat)(in_())(nibs(((shape Convex)(sort Pat))((shape Convex)(sort \ - Pat))))))(shards(0))(children())))(Secondary((id \ - c3bbc117-f5bb-4e9f-932a-6b831fc56316)(content(Whitespace\" \ - \")))))((Secondary((id \ - 5e9e07bc-cdb3-4ec7-bcfe-dfc30ae77247)(content(Whitespace\" \ - \"))))(Tile((id \ - 04349459-8992-4c2a-b732-ff9a57e7ee81)(label(2))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - c26276fc-07f7-4e68-8568-82a44cf9e788)(content(Whitespace\" \ - \")))))))))(Secondary((id \ - 561258e1-7e56-47ab-99a6-6948ca1ca060)(content(Whitespace\" \ - \"))))(Secondary((id \ - 05d9b650-ffd2-4999-a85a-4bf371b9fff9)(content(Comment \ - #err#))))(Secondary((id \ - 9716f9e1-195b-4cb4-bf3e-0f15de9b8dc6)(content(Whitespace\" \ - \"))))(Secondary((id \ - 87120080-ccc4-4e30-abcf-a373671ed9e9)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 74222fff-923d-4219-ab77-92d473faa51c)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 76fe6c6f-a21a-4d9e-b308-e7bb1ba9d4d9)(label(let = in))(mold((out \ - Exp)(in_(Pat Exp))(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 16))(sort Exp))))))(shards(0 1 2))(children(((Grout((id \ - 3ee97b06-b7e3-41b6-ad8d-03ce25681fec)(shape Convex)))(Secondary((id \ - ace18a48-edf6-4878-b1da-f5f4a3ed7e45)(content(Whitespace\" \ - \"))))(Secondary((id \ - 5fb41e67-6173-4f99-9f63-b5f139f4290a)(content(Whitespace\" \ - \"))))(Secondary((id \ - f42b818b-f0a9-4230-85e7-65b2db5c93e8)(content(Whitespace\" \ - \")))))((Secondary((id \ - 014e24ec-d83a-4e2b-a0dc-a6aed99e1549)(content(Whitespace\" \ - \"))))(Tile((id 77ed3661-972b-4367-b16d-4748f1d4b59f)(label(if then \ - else))(mold((out Exp)(in_(Exp Exp))(nibs(((shape Convex)(sort \ - Exp))((shape(Concave 12))(sort Exp))))))(shards(0 1 \ - 2))(children(((Secondary((id \ - 8c9c1c27-2f6e-485a-99fd-2595f5c4b65c)(content(Whitespace\" \ - \"))))(Tile((id \ - 557f069f-2b23-4f79-b515-4f6e7b72d6dc)(label(true))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - 0164c9e6-ae26-4e59-bc45-5e81a4411057)(content(Whitespace\" \ - \")))))((Secondary((id \ - aafe6447-992c-487c-b50c-74e9eb7c09ec)(content(Whitespace\" \ - 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Pat))))))(shards(0))(children())))(Tile((id \ - 4f680010-5ffc-4e1c-b9e3-a061fcb1554b)(label(:))(mold((out \ - Pat)(in_())(nibs(((shape(Concave 11))(sort Pat))((shape(Concave \ - 11))(sort Typ))))))(shards(0))(children())))(Secondary((id \ - 014f3ba2-4d5b-4c4a-a39b-5d9c76c15b91)(content(Whitespace\" \ - \"))))(Tile((id 4d9249cb-d236-44c5-b3d3-c257647121fd)(label([ \ - ]))(mold((out Typ)(in_(Typ))(nibs(((shape Convex)(sort Typ))((shape \ - Convex)(sort Typ))))))(shards(0 1))(children(((Tile((id \ - 22327f4a-4bed-4d89-998f-291f2c7bdfb4)(label(Int))(mold((out \ - Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape Convex)(sort \ - Typ))))))(shards(0))(children()))))))))(Secondary((id \ - 8aa51f35-d8f7-4d2a-a979-9213e994ed36)(content(Whitespace\" \ - \")))))((Secondary((id \ - b7316208-d52e-44cb-b03f-55917c4c17d8)(content(Whitespace\" \ - \"))))(Tile((id \ - f19e7f34-f64e-45bf-b807-54fd5a3803c1)(label(1))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Tile((id \ - 3423b882-53c4-4e91-b1fb-c1799b247e52)(label(::))(mold((out \ - Exp)(in_())(nibs(((shape(Concave 6))(sort Exp))((shape(Concave 6))(sort \ - Exp))))))(shards(0))(children())))(Tile((id \ - 18760f33-67f4-478a-8d46-b867fccb4fab)(label([ ]))(mold((out \ - Exp)(in_(Exp))(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0 1))(children(((Tile((id \ - 69a8f2e4-f319-4d1d-a0c1-8ee4ae299727)(label(2.0))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children()))))))))(Secondary((id \ - 7545443f-d605-44b8-a7fd-13f11cd4c91a)(content(Whitespace\" \ - \")))))))))(Secondary((id \ - b9ecf255-e21b-4016-b078-d3dc00ccc392)(content(Whitespace\" \ - \"))))(Secondary((id \ - a87989b8-2f60-487c-a4b8-874a167f70c4)(content(Comment \ - #err#))))(Secondary((id \ - 218a3f7c-0fa0-4a28-9644-6e4ba7220cc0)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 39cd7f40-a6e9-494a-8a06-90a1658ac498)(label(\"\\\"BYE\\\"\"))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children()))))()))(ancestors())))(caret Outer))"; - backup_text = - "#Types and type error examples#\n\n\ - let _ = unbound in #err#\n\ - let Undefined = Undefined in # 2x err# \n\ - let true = 2 in #err# \n\n\ - let = if true then 1 else 1. in #err# \n\ - let _ = if true then 1 else 1. in #err#\n\ - let _: = if true then 1 else 1. in\n\ - let _: Int = if true then 1 else 1. in #err#\n\ - let _: Fake = if true then 1 else true in #err#\n\ - let _, _ = if true then 1 else 1. in #2x err#\n\ - let _, _ = (if true then 1 else 1.), in #err#\n\ - let _: , _ = (if true then 1 else 1.), in \n\ - let [_] = [(if true then 1 else 1.)] in \n\ - let [_] = (if true then 1 else 1.) in #2x err# \n\n\ - ( )(if true then 1 else 1.);\n\ - 1(if true then 1 else 1.); #err#\n\ - (1)(if true then 1 else 1.); #err#\n\ - (fun -> )(if true then 1 else 1.);\n\ - (fun _ -> )(if true then 1 else 1.);\n\ - (fun _: -> )(if true then 1 else 1.);\n\ - (fun _: Int -> )(if true then 1 else 1.); #err#\n\n\ - let _ = fun x -> if true then 1 else 1. in #err#\n\ - let _: = fun x -> if true then 1 else 1. in\n\ - let _: -> = fun x -> if true then 1 else 1. in\n\ - let _: -> Int = fun x -> if true then 1 else 1. in #err#\n\ - let _: -> [ ] = fun x -> if true then 1 else 1. in #2x err#\n\n\ - ( )::[(if true then 1 else 1.)];\n\ - 1::[(if true then 1 else 1.)]; #err#\n\ - (1, 1)::[(if true then 1 else 1.)]; #2x err#\n\n\ - let = [1, 1., true] in #err: inconsistent#\n\ - let _ = [1, 1., true] in #err: inconsistent#\n\ - let _: = [1, 1., true] in \n\ - let _: [ ] = [1, 1., true] in\n\ - let _: [Int] = [1, 1., true] in #2x err#\n\n\ - let _: [Int] = 1::[2] in\n\ - let _: [Int] = 1.0::[2] in #err#\n\ - let _: [Int] = 1::[2.0] in #err#\n\ - \"BYE\""; - } - -let adt_egs : ScratchSlide.persistent_state = - { - zipper = - "((selection((focus \ - Left)(content())))(backpack())(relatives((siblings(((Secondary((id \ - 57594779-691c-4a07-9a54-72c38d33ef16)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 5247b04c-d7a2-447f-8ab1-dfee15537b5d)(label(+))(mold((out \ - Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape(Concave 10))(sort \ - Typ))))))(shards(0))(children())))(Secondary((id \ - 591d41b4-45d4-4856-ad6a-87c3ca8de936)(content(Whitespace\" \ - \"))))(Tile((id \ - 5abfe9ba-5e23-4bb3-ab6a-228e3bc4d3d9)(label(Um))(mold((out \ - Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape Convex)(sort \ - Typ))))))(shards(0))(children())))(Tile((id \ - 6668638e-2edf-4c7e-b70d-4a1942f3d4b8)(label(\"(\"\")\"))(mold((out \ - Typ)(in_(Typ))(nibs(((shape(Concave 1))(sort Typ))((shape Convex)(sort \ - Typ))))))(shards(0 1))(children(((Tile((id \ - 92ddab41-45a1-4dc3-8c5d-2a9417d26261)(label(Unbound))(mold((out \ - Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape Convex)(sort \ - Typ))))))(shards(0))(children()))))))))(Secondary((id \ - 2b69b05c-d459-4aef-ac15-61422ab2622a)(content(Whitespace\" \ - \"))))(Secondary((id \ - dd0c8aaf-a83e-49f3-adfc-3e1de8eb88f7)(content(Comment\"#err: unbound \ - type var#\"))))(Secondary((id \ - 7a113996-8049-4557-9117-0f337dbff9ee)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - f99d34f2-0861-4b49-aea0-e49e9014ec49)(label(+))(mold((out \ - Typ)(in_())(nibs(((shape(Concave 10))(sort Typ))((shape(Concave \ - 10))(sort Typ))))))(shards(0))(children())))(Secondary((id \ - 571c6f17-f01e-4941-a97d-b65382a0b6cd)(content(Whitespace\" \ - \"))))(Tile((id \ - 2cda9eb4-b565-4e92-9c21-c680a71c5cbe)(label(notvalid))(mold((out \ - Exp)(in_())(nibs(((shape Convex)(sort Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - 3dac48f9-5eb0-4624-90fd-d7625c38cdc4)(content(Whitespace\" \ - \"))))(Secondary((id \ - b7976c5b-8c8a-4cb4-9506-8bf9f5dd15b6)(content(Comment\"#err: \ - invalid#\")))))((Secondary((id \ - 59d60348-8f47-42d9-a4bb-0cb8a339a3e0)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - b0dc58f1-3e2f-4360-b23c-7a326b00584f)(label(+))(mold((out \ - Typ)(in_())(nibs(((shape(Concave 10))(sort Typ))((shape(Concave \ - 10))(sort Typ))))))(shards(0))(children())))(Secondary((id \ - 83c4b84c-5784-474c-bf9c-2f8b71f14d50)(content(Whitespace\" \ - \"))))(Tile((id \ - 43da0980-0cd0-46e1-b681-a6469f2b92e7)(label(Bool))(mold((out \ - Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape Convex)(sort \ - Typ))))))(shards(0))(children())))(Secondary((id \ - 46b7bce6-e801-4001-ba47-2ec5ac2215b7)(content(Whitespace\" \ - \"))))(Secondary((id \ - 4157bbda-ea92-4af4-b77a-6515480f30a7)(content(Comment\"#err: expected \ - cons found type#\"))))(Secondary((id \ - 5f6a8b70-95e4-4565-a5a9-dbe98e22e80b)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 92af8b61-4e86-460c-b902-1d4c0300bf68)(label(+))(mold((out \ - Typ)(in_())(nibs(((shape(Concave 10))(sort Typ))((shape(Concave \ - 10))(sort Typ))))))(shards(0))(children())))(Secondary((id \ - 52215bc5-3e4e-4987-9429-992ad1556941)(content(Whitespace\" \ - \"))))(Tile((id \ - 5194f01c-231b-4d83-b742-a054e76a5396)(label(Int))(mold((out \ - Typ)(in_())(nibs(((shape Convex)(sort Typ))((shape Convex)(sort \ - Typ))))))(shards(0))(children())))(Tile((id \ - 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780a32f5-e4a1-4af6-9a9c-2dbc09b9f669)(content(Comment\"#all lines with \ - trailing err comment should have 1 error#\"))))(Secondary((id \ - 45b71874-3478-434f-b2be-f7f1d1e1c0ce)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 496b0a93-599c-4bd2-b1f6-f2ef05ea8d8c)(content(Comment\"#no other lines \ - should have errors#\"))))(Secondary((id \ - b0de6367-1efa-4be9-a5a8-2be0d2b9b3f8)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 488820d0-fbbd-4b2c-9edb-e52d03402d7a)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 0beb6b37-d8d6-4a29-bccc-4617937604f6)(content(Comment\"#type \ - definitions: no errors#\"))))(Secondary((id \ - 5efc4bf5-c3cb-4d1e-bc0b-19b06c515590)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 2fd0b30b-2842-48bf-943f-007ae5d400c2)(label(type = in))(mold((out \ - Exp)(in_(TPat Typ))(nibs(((shape Convex)(sort Exp))((shape(Concave \ - 16))(sort Exp))))))(shards(0 1 2))(children(((Grout((id \ - 95b2a65d-f369-4149-8976-442bf6f27016)(shape Convex)))(Secondary((id \ - 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folks\\\"\"))(mold((out Exp)(in_())(nibs(((shape Convex)(sort \ - Exp))((shape Convex)(sort \ - Exp))))))(shards(0))(children())))(Secondary((id \ - 90a5fb0d-b434-4eba-8e96-dd84481cde22)(content(Whitespace\"\\226\\143\\142\")))))))))))(caret \ - Outer))"; - backup_text = - "#Non-recursive sum/alias tests#\n\ - #all lines with trailing err comment should have 1 error#\n\ - #no other lines should have errors#\n\n\ - #type definitions: no errors#\n\ - type = in\n\ - type SingleNull = +One in\n\ - type Single = +F(Int) in\n\ - type GoodSum = A + B + C(Int) in\n\ - type Partial = Ok( ) + in\n\ - type DoubleAlias = GoodSum in\n\ - type VerticalLeading =\n\ - + A\n\ - + B(GoodSum)\n\ - + C(Bool->Bool) \n\ - in\n\n\ - #incorrect or incomplete type definitions#\n\ - type badTypeName = in #err: invalid type name#\n\ - type ( , ) = in #err: invalid type name#\n\ - type = badTypeToken in #err: invalid type token#\n\ - type NotASum = NotInSum(Bool) in #err: cons not in sum#\n\ - type Bool = in #err: shadows base type#\n\ - type Dupes =\n\ - + Guy(Bool) #no err#\n\ - + Guy(Int) #err: already used#\n\ - + Guy in #err: already used#\n\ - type BadCons =\n\ - + Um(Unbound) #err: unbound type var#\n\ - + notvalid #err: invalid#\n\ - + Bool #err: expected cons found type#\n\ - + Int(Int) #err: expected cons found type#\n\ - + ( )(Int) #err: expected cons found type#\n\ - + A(Bool)(Int) in #err: expected cons found app#\n\n\ - #sums in compound aliases dont add tags to scope#\n\ - #but compound alias types should propagate analytically#\n\ - type CompoundAlias = (Int, Anonymous + Sum) in \n\ - let _ = (1, Sum) in #err: not defined#\n\ - let _: CompoundAlias = (1, Sum) in #no error#\n\ - type Yorp = Int -> (Inside + Ouside) in\n\ - let _ = fun _ -> Inside in #err: not defined#\n\ - let _: Yorp = fun _ -> Inside in #no error#\n\ - type Gargs = [BigGuy + Small] in\n\ - let _ = BigGuy in #err: not defined#\n\ - let _: Gargs = [BigGuy] in #no error#\n\ - let _: Gargs = BigGuy :: [BigGuy] in #no error#\n\n\ - #unbound tyvars treated as unknown-typehole#\n\ - let a:Bad = 0 in a == 0; #err: not bound#\n\n\ - #non-sum-types cant be recursive#\n\ - type Lol = Lol in #err: not bound#\n\n\ - #no errors: analytic shadowing#\n\ - type Tork1 = +Blob in\n\ - type Tork2 = +Blob in \n\ - let x:Tork1 = Blob in\n\n\ - #exp tests: happy#\n\ - type YoDawg = Yo(Int) + Bo(Int)+ Dawg(Bool) in\n\ - let _ = Yo(1) in\n\ - let _ : YoDawg = Yo(2) in\n\ - let _ : +Yo(Bool) = Yo(true) in\n\ - let _ : (Yo + Dawg, Int) = (Dawg,5) in\n\ - let _ : DoubleAlias = C(4) in\n\n\ - #exp tests: errors#\n\ - let _ = 2(1) in #err: incons with arrow#\n\ - let _ = Undefined(1) in #err: cons undefined#\n\ - let _ = B(\"lol\") in #err: type incons#\n\ - let _ : +Yo(Bool) = Yo in #err: type incons#\n\ - let _ : +Yo = Yo(\"lol\") in #err: type incons#\n\ - let _ : +One = Yo(1) in #err: type incons#\n\n\ - #pat tests: happy (but refutable patterns so weird)#\n\ - let Yo = Bo in #kind of a weird edge#\n\ - let Yo(1) = Dawg(true) in\n\ - let Yo(1): YoDawg = Yo(1) in\n\ - let Yo(1): +Yo(Int) = Yo(1) in \n\ - let Yo: +Yo = Yo in\n\n\ - #pat tests: errors#\n\ - let 2(1) = 3 in #err: incons with arrow#\n\ - let NotDefined(1) = 3 in #err: cons undefined#\n\ - let Yo = Dawg in #err: type incons#\n\ - let Yo(true) = Dawg(true) in #err: type incons#\n\ - let Yo: YoDawg = Yo(1) in #err: type incons#\n\ - let Yo(1): +Yo = Yo in #err: type incons#\n\ - let Yo(1): +Yo(Bool) = Yo(true) in #err: type incons#\n\ - \"Thats all, folks\"\n"; - } - -let adt_dynamics_tests : ScratchSlide.persistent_state = - { - zipper = - "((selection((focus \ - Left)(content())))(backpack())(relatives((siblings(((Secondary((id \ - ede618fd-3a6a-4718-a6f2-fb07d7311e24)(content(Comment\"#recursive sum \ - type dynamics tests#\"))))(Secondary((id \ - f3ba4eee-2d48-4265-b068-22a14424c793)(content(Whitespace\"\\226\\143\\142\"))))(Secondary((id \ - 8c0d0280-8bd7-4ca1-8047-f9582dcb62b4)(content(Comment\"#all calls \ - should evaluate fully with no exns or cast fails#\"))))(Secondary((id \ - 33d03b71-1aba-4b78-ada1-9f738b650371)(content(Whitespace\"\\226\\143\\142\"))))(Tile((id \ - 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Exp))))))(shards(0))(children())))))))))))))(Secondary((id \ - 55ed9628-d3ce-4899-8b80-8fd7ca04c644)(content(Whitespace\"\\226\\143\\142\")))))()))(ancestors())))(caret \ - Outer))"; - backup_text = - "#recursive sum type dynamics tests#\n\ - #all calls should evaluate fully with no exns or cast fails#\n\ - type Exp = Var(String) + Lam(String, Exp) in\n\n\ - let s0 : ( , , ) -> = fun (e,x,v) ->\n\ - case e\n\ - | Var(y) => (if y $== x then v else e)\n\ - | Lam(y, e1) => (if y $== x then e else Lam(y, s0(e1,x,v))) \n\ - end in \n\ - let s1 : ( , , ) -> Exp = fun (e,x,v) ->\n\ - case e\n\ - | Var(y) => (if y $== x then v else e)\n\ - | Lam(y, e1) => (if y $== x then e else Lam(y, s1(e1,x,v))) \n\ - end in \n\ - let s2 : (Exp, , ) -> Exp = fun (e,x,v) ->\n\ - case e\n\ - | Var(y) => (if y $== x then v else e)\n\ - | Lam(y, e1) => (if y $== x then e else Lam(y, s2(e1,x,v))) \n\ - end in \n\ - let s3 : (Exp, , Exp) -> Exp = fun (e,x,v) ->\n\ - case e\n\ - | Var(y) => (if y $== x then v else e)\n\ - | Lam(y, e1) => (if y $== x then e else Lam(y, s3(e1,x,v))) \n\ - end in\n\n\ - let in = Lam(\"b\", Var(\"a\")),\"a\",Var(\"x\") in\n\ - (s0(in), s1(in), s2(in), s3(in))\n"; - } diff --git a/src/haz3lweb/Settings.re b/src/haz3lweb/Settings.re index d64917b0ab..1481b54621 100644 --- a/src/haz3lweb/Settings.re +++ b/src/haz3lweb/Settings.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type mode = diff --git a/src/haz3lweb/SlideContent.re b/src/haz3lweb/SlideContent.re index 064b766744..639f55dd70 100644 --- a/src/haz3lweb/SlideContent.re +++ b/src/haz3lweb/SlideContent.re @@ -6,23 +6,27 @@ let img = create("img"); let slide = (header, content) => div( ~key="slide", - ~attr=Attr.class_("slide"), + ~attrs=[Attr.class_("slide")], [ - h1(~key="header", ~attr=Attr.class_("slide-header"), [text(header)]), - div(~key="content", ~attr=Attr.class_("slide-content"), content), + h1( + ~key="header", + ~attrs=[Attr.class_("slide-header")], + [text(header)], + ), + div(~key="content", ~attrs=[Attr.class_("slide-content")], content), ], ); -let code = content => span(~attr=Attr.class_("code"), [text(content)]); +let code = content => span(~attrs=[Attr.class_("code")], [text(content)]); -let em = content => span(~attr=Attr.class_("em"), [text(content)]); +let em = content => span(~attrs=[Attr.class_("em")], [text(content)]); let get_content = fun - | Documentation("Programming Expressively", _) => + | Documentation("Expressive Programming", _) => Some( slide( - "Programming Expressively", + "Expressive Programming", [ p([ text( @@ -47,10 +51,10 @@ let get_content = ], ), ) - | Documentation("Composing Arithmetic Expressions", _) => + | Documentation("Composing Expressions", _) => Some( slide( - "Composing Arithmetic Expressions", + "Composing Expressions", [ p([ text("Arithmetic expressions are constructed "), diff --git a/src/haz3lweb/Store.re b/src/haz3lweb/Store.re index 0c4ac3fe23..f30a18ab85 100644 --- a/src/haz3lweb/Store.re +++ b/src/haz3lweb/Store.re @@ -1,4 +1,5 @@ open Haz3lcore; +open Util; // A generic key-value store for saving/loading data to/from local storage module Generic = { @@ -113,6 +114,9 @@ module Scratch = { [@deriving (show({with_path: false}), sexp, yojson)] type persistent = PersistentData.scratch; + [@deriving (show({with_path: false}), sexp, yojson)] + type t = (int, list(Editor.t), ModelResults.M.t(ModelResult.t)); + let to_persistent = ((idx, slides, results)): persistent => ( idx, List.map(ScratchSlide.persist, slides), @@ -121,36 +125,42 @@ module Scratch = { |> ModelResults.bindings, ); - let of_persistent = (~settings, (idx, slides, results): persistent) => { + let of_persistent = + (~settings: CoreSettings.t, (idx, slides, results): persistent): t => { ( idx, - List.map(ScratchSlide.unpersist, slides), + List.map(ScratchSlide.unpersist(~settings), slides), results |> List.to_seq |> ModelResults.of_seq - |> ModelResults.map(ModelResult.of_persistent(~settings)), + |> ModelResults.map( + ModelResult.of_persistent(~settings=settings.evaluation), + ), ); }; - let serialize = scratch => { + let serialize = (scratch: t): string => { scratch |> to_persistent |> sexp_of_persistent |> Sexplib.Sexp.to_string; }; - let deserialize = data => { - data |> Sexplib.Sexp.of_string |> persistent_of_sexp |> of_persistent; + let deserialize = (data: string, ~settings: CoreSettings.t): t => { + data + |> Sexplib.Sexp.of_string + |> persistent_of_sexp + |> of_persistent(~settings); }; - let save = (scratch): unit => { + let save = (scratch: t): unit => { JsUtil.set_localstore(save_scratch_key, serialize(scratch)); }; - let init = (~settings) => { + let init = (~settings: CoreSettings.t): t => { let scratch = of_persistent(~settings, Init.startup.scratch); save(scratch); scratch; }; - let load = (~settings) => + let load = (~settings: CoreSettings.t): t => switch (JsUtil.get_localstore(save_scratch_key)) { | None => init(~settings) | Some(data) => @@ -159,8 +169,10 @@ module Scratch = { } }; - let export = (~settings) => serialize(load(~settings)); - let import = (~settings, data) => save(deserialize(~settings, data)); + let export = (~settings: CoreSettings.t): string => + serialize(load(~settings)); + let import = (~settings: CoreSettings.t, data: string): unit => + save(deserialize(~settings, data)); }; module Documentation = { @@ -169,13 +181,20 @@ module Documentation = { [@deriving (show({with_path: false}), sexp, yojson)] type persistent = PersistentData.documentation; + [@deriving (show({with_path: false}), sexp, yojson)] + type t = ( + string, + list((string, Editor.t)), + ModelResults.M.t(ModelResult.t), + ); + let persist = ((name, editor: Editor.t)) => { (name, PersistentZipper.persist(editor.state.zipper)); }; - let unpersist = ((name, zipper)) => { + let unpersist = ((name, zipper), ~settings: CoreSettings.t) => { let zipper = PersistentZipper.unpersist(zipper); - (name, Editor.init(zipper, ~read_only=false)); + (name, Editor.init(zipper, ~read_only=false, ~settings)); }; let to_persistent = ((string, slides, results)): persistent => ( @@ -186,36 +205,42 @@ module Documentation = { |> ModelResults.bindings, ); - let of_persistent = (~settings, (string, slides, results): persistent) => { + let of_persistent = + (~settings: CoreSettings.t, (string, slides, results): persistent): t => { ( string, - List.map(unpersist, slides), + List.map(unpersist(~settings), slides), results |> List.to_seq |> ModelResults.of_seq - |> ModelResults.map(ModelResult.of_persistent(~settings)), + |> ModelResults.map( + ModelResult.of_persistent(~settings=settings.evaluation), + ), ); }; - let serialize = slides => { + let serialize = (slides: t): string => { slides |> to_persistent |> sexp_of_persistent |> Sexplib.Sexp.to_string; }; - let deserialize = data => { - data |> Sexplib.Sexp.of_string |> persistent_of_sexp |> of_persistent; + let deserialize = (~settings: CoreSettings.t, data: string): t => { + data + |> Sexplib.Sexp.of_string + |> persistent_of_sexp + |> of_persistent(~settings); }; - let save = (slides): unit => { + let save = (slides: t): unit => { JsUtil.set_localstore(save_documentation_key, serialize(slides)); }; - let init = (~settings) => { + let init = (~settings: CoreSettings.t): t => { let documentation = of_persistent(~settings, Init.startup.documentation); save(documentation); documentation; }; - let load = (~settings) => + let load = (~settings: CoreSettings.t): t => switch (JsUtil.get_localstore(save_documentation_key)) { | None => init(~settings) | Some(data) => @@ -224,8 +249,10 @@ module Documentation = { } }; - let export = (~settings) => serialize(load(~settings)); - let import = (~settings, data) => save(deserialize(~settings, data)); + let export = (~settings: CoreSettings.t): string => + serialize(load(~settings)); + let import = (~settings: CoreSettings.t, data: string): unit => + save(deserialize(~settings, data)); }; module Exercise = { @@ -249,57 +276,70 @@ module Exercise = { JsUtil.set_localstore(cur_exercise_key, keystring_of_key(key)); }; - let save_exercise = (exercise, ~instructor_mode) => { + let save_exercise = (exercise, ~instructor_mode): unit => { let key = Exercise.key_of_state(exercise); let keystring = keystring_of_key(key); let value = Exercise.serialize_exercise(exercise, ~instructor_mode); JsUtil.set_localstore(keystring, value); }; - let init_exercise = (spec, ~instructor_mode) => { + let init_exercise = + (~settings: CoreSettings.t, spec, ~instructor_mode): state => { let key = Exercise.key_of(spec); let keystring = keystring_of_key(key); - let exercise = Exercise.state_of_spec(spec, ~instructor_mode); + let exercise = Exercise.state_of_spec(spec, ~instructor_mode, ~settings); save_exercise(exercise, ~instructor_mode); JsUtil.set_localstore(cur_exercise_key, keystring); exercise; }; - let load_exercise = (key, spec, ~instructor_mode): Exercise.state => { + let load_exercise = + (~settings: CoreSettings.t, key, spec, ~instructor_mode): Exercise.state => { let keystring = keystring_of_key(key); switch (JsUtil.get_localstore(keystring)) { | Some(data) => let exercise = - try(Exercise.deserialize_exercise(data, ~spec, ~instructor_mode)) { - | _ => init_exercise(spec, ~instructor_mode) + try( + Exercise.deserialize_exercise( + data, + ~spec, + ~instructor_mode, + ~settings, + ) + ) { + | _ => init_exercise(spec, ~instructor_mode, ~settings) }; JsUtil.set_localstore(cur_exercise_key, keystring); exercise; - | None => init_exercise(spec, ~instructor_mode) + | None => init_exercise(spec, ~instructor_mode, ~settings) }; }; - let save = ((n, specs, exercise), ~instructor_mode) => { + let save = ((n, specs, exercise), ~instructor_mode): unit => { let key = key_of(List.nth(specs, n)); let keystring = keystring_of_key(key); save_exercise(exercise, ~instructor_mode); JsUtil.set_localstore(cur_exercise_key, keystring); }; - let init = (~instructor_mode) => { + let init = + (~settings: CoreSettings.t, ~instructor_mode) + : (int, list(spec), state) => { let exercises = { ( 0, ExerciseSettings.exercises, List.nth(ExerciseSettings.exercises, 0) - |> Exercise.state_of_spec(~instructor_mode), + |> Exercise.state_of_spec(~instructor_mode, ~settings), ); }; save(exercises, ~instructor_mode); exercises; }; - let load = (~specs, ~instructor_mode) => { + let load = + (~settings: CoreSettings.t, ~specs, ~instructor_mode) + : (int, list(p(ZipperBase.t)), state) => { switch (JsUtil.get_localstore(cur_exercise_key)) { | Some(keystring) => let key = key_of_keystring(keystring); @@ -308,13 +348,16 @@ module Exercise = { switch (JsUtil.get_localstore(keystring)) { | Some(data) => let exercise = - try(deserialize_exercise(data, ~spec, ~instructor_mode)) { - | _ => init_exercise(spec, ~instructor_mode) + try( + deserialize_exercise(data, ~spec, ~instructor_mode, ~settings) + ) { + | _ => init_exercise(spec, ~instructor_mode, ~settings) }; (n, specs, exercise); | None => // initialize exercise from spec - let exercise = Exercise.state_of_spec(spec, ~instructor_mode); + let exercise = + Exercise.state_of_spec(spec, ~instructor_mode, ~settings); save_exercise(exercise, ~instructor_mode); (n, specs, exercise); } @@ -322,13 +365,19 @@ module Exercise = { // invalid current exercise key saved, load the first exercise let first_spec = List.nth(specs, 0); let first_key = Exercise.key_of(first_spec); - (0, specs, load_exercise(first_key, first_spec, ~instructor_mode)); + ( + 0, + specs, + load_exercise(first_key, first_spec, ~instructor_mode, ~settings), + ); }; - | None => init(~instructor_mode) + | None => init(~instructor_mode, ~settings) }; }; - let prep_exercise_export = (~specs, ~instructor_mode) => { + let prep_exercise_export = + (~specs, ~instructor_mode: bool, ~settings: CoreSettings.t) + : exercise_export => { { cur_exercise: key_of_keystring( @@ -339,15 +388,16 @@ module Exercise = { |> List.map(spec => { let key = Exercise.key_of(spec); let exercise = - load_exercise(key, spec, ~instructor_mode) + load_exercise(key, spec, ~instructor_mode, ~settings) |> Exercise.persistent_state_of_state(~instructor_mode); (key, exercise); }), }; }; - let serialize_exercise_export = (~specs, ~instructor_mode) => { - prep_exercise_export(~specs, ~instructor_mode) + let serialize_exercise_export = + (~specs, ~instructor_mode, ~settings: CoreSettings.t) => { + prep_exercise_export(~specs, ~instructor_mode, ~settings) |> sexp_of_exercise_export |> Sexplib.Sexp.to_string; }; @@ -356,7 +406,8 @@ module Exercise = { serialize_exercise_export(~specs, ~instructor_mode); }; - let import = (data, ~specs, ~instructor_mode) => { + let import = + (data, ~specs, ~instructor_mode: bool, ~settings: CoreSettings.t) => { let exercise_export = data |> deserialize_exercise_export; save_exercise_key(exercise_export.cur_exercise); exercise_export.exercise_data @@ -371,6 +422,7 @@ module Exercise = { persistent_state, ~spec, ~instructor_mode, + ~settings, ), ~instructor_mode, ) diff --git a/src/haz3lweb/Update.re b/src/haz3lweb/Update.re index e9d4f46068..1aacb159f3 100644 --- a/src/haz3lweb/Update.re +++ b/src/haz3lweb/Update.re @@ -1,7 +1,26 @@ +open Util; +open Js_of_ocaml; open Haz3lcore; include UpdateAction; // to prevent circularity +let observe_font_specimen = (id, update) => + ResizeObserver.observe( + ~node=JsUtil.get_elem_by_id(id), + ~f= + (entries, _) => { + let specimen = Js.to_array(entries)[0]; + let rect = specimen##.contentRect; + update( + FontMetrics.{ + row_height: rect##.bottom -. rect##.top, + col_width: rect##.right -. rect##.left, + }, + ); + }, + (), + ); + let update_settings = (a: settings_action, {settings, _} as model: Model.t): Model.t => switch (a) { @@ -186,11 +205,7 @@ let update_settings = let schedule_evaluation = (~schedule_action, model: Model.t): unit => if (model.settings.core.dynamics) { let elabs = - Editors.get_spliced_elabs( - ~settings=model.settings, - model.statics, - model.editors, - ); + Editors.get_spliced_elabs(~settings=model.settings.core, model.editors); let eval_rs = ModelResults.to_evaluate(model.results, elabs); if (!ModelResults.is_empty(eval_rs)) { schedule_action(UpdateResult(eval_rs)); @@ -216,13 +231,47 @@ let schedule_evaluation = (~schedule_action, model: Model.t): unit => }; }; +let on_startup = + (~schedule_action: UpdateAction.t => unit, m: Model.t): Model.t => { + let _ = + observe_font_specimen("font-specimen", fm => + schedule_action(UpdateAction.SetMeta(FontMetrics(fm))) + ); + NinjaKeys.initialize(NinjaKeys.options(schedule_action)); + JsUtil.focus_clipboard_shim(); + /* initialize state. */ + /* Initial evaluation on a worker */ + schedule_evaluation(~schedule_action, m); + Os.is_mac := + Dom_html.window##.navigator##.platform##toUpperCase##indexOf( + Js.string("MAC"), + ) + >= 0; + m; +}; + let update_cached_data = (~schedule_action, update, m: Model.t): Model.t => { - let update_statics = is_edit(update) || reevaluate_post_update(update); let update_dynamics = reevaluate_post_update(update); + /* If we switch editors, or change settings which require statics + * when statics was previously off, we may need updated statics */ + let non_edit_action_requiring_statics_refresh = + update_dynamics + && ( + switch (update) { + | PerformAction(_) => false + | _ => true + } + ); let m = - update_statics || update_dynamics && m.settings.core.statics - ? {...m, statics: Editors.mk_statics(~settings=m.settings, m.editors)} - : m; + if (non_edit_action_requiring_statics_refresh) { + { + ...m, + editors: + Editors.update_current_editor_statics(m.settings.core, m.editors), + }; + } else { + m; + }; if (update_dynamics && m.settings.core.dynamics) { schedule_evaluation(~schedule_action, m); m; @@ -231,22 +280,9 @@ let update_cached_data = (~schedule_action, update, m: Model.t): Model.t => { }; }; -let perform_action = (model: Model.t, a: Action.t): Result.t(Model.t) => - switch ( - model.editors - |> Editors.get_editor - |> Haz3lcore.Perform.go(~settings=model.settings.core, a) - ) { - | Error(err) => Error(FailedToPerform(err)) - | Ok(ed) => - let model = {...model, editors: Editors.put_editor(ed, model.editors)}; - /* Note: Not saving here as saving is costly to do each keystroke, - we wait a second after the last edit action (see Main.re) */ - Ok(model); - }; - let switch_scratch_slide = - (editors: Editors.t, ~instructor_mode, idx: int): option(Editors.t) => + (~settings, editors: Editors.t, ~instructor_mode, idx: int) + : option(Editors.t) => switch (editors) { | Documentation(_) => None | Scratch(n, _) when n == idx => None @@ -256,7 +292,8 @@ let switch_scratch_slide = | Exercises(_, specs, _) => let spec = List.nth(specs, idx); let key = Exercise.key_of(spec); - let exercise = Store.Exercise.load_exercise(key, spec, ~instructor_mode); + let exercise = + Store.Exercise.load_exercise(key, spec, ~instructor_mode, ~settings); Some(Exercises(idx, specs, exercise)); }; @@ -282,13 +319,14 @@ let switch_exercise_editor = this between users. The former is a TODO, currently difficult due to the more complex architecture of Exercises. */ let export_persistent_data = () => { + // TODO Is this parsing and reserializing? let settings = Store.Settings.load(); let data: PersistentData.t = { documentation: - Store.Documentation.load(~settings=settings.core.evaluation) + Store.Documentation.load(~settings=settings.core) |> Store.Documentation.to_persistent, scratch: - Store.Scratch.load(~settings=settings.core.evaluation) + Store.Scratch.load(~settings=settings.core) |> Store.Scratch.to_persistent, settings, }; @@ -301,6 +339,52 @@ let export_persistent_data = () => { ); print_endline("INFO: Persistent data exported to Init.ml"); }; +let export_scratch_slide = (editor: Editor.t): unit => { + let json_data = ScratchSlide.export(editor); + JsUtil.download_json("hazel-scratchpad", json_data); +}; + +let export_exercise_module = (exercise: Exercise.state): unit => { + let module_name = exercise.eds.module_name; + let filename = exercise.eds.module_name ++ ".ml"; + let content_type = "text/plain"; + let contents = Exercise.export_module(module_name, exercise); + JsUtil.download_string_file(~filename, ~content_type, ~contents); +}; + +let export_submission = (~instructor_mode) => + Log.get_and(log => { + let data = Export.export_all(~instructor_mode, ~log); + JsUtil.download_json(ExerciseSettings.filename, data); + }); + +let export_transitionary = (exercise: Exercise.state) => { + // .ml files because show uses OCaml syntax (dune handles seamlessly) + let module_name = exercise.eds.module_name; + let filename = exercise.eds.module_name ++ ".ml"; + let content_type = "text/plain"; + let contents = Exercise.export_transitionary_module(module_name, exercise); + JsUtil.download_string_file(~filename, ~content_type, ~contents); +}; + +let export_instructor_grading_report = (exercise: Exercise.state) => { + // .ml files because show uses OCaml syntax (dune handles seamlessly) + let module_name = exercise.eds.module_name; + let filename = exercise.eds.module_name ++ "_grading.ml"; + let content_type = "text/plain"; + let contents = Exercise.export_grading_module(module_name, exercise); + JsUtil.download_string_file(~filename, ~content_type, ~contents); +}; + +let instructor_exercise_update = + (model: Model.t, fn: Exercise.state => unit): Result.t(Model.t) => { + switch (model.editors) { + | Exercises(_, _, exercise) when model.settings.instructor_mode => + fn(exercise); + Ok(model); + | _ => Error(InstructorOnly) // TODO Make command palette contextual and figure out how to represent that here + }; +}; let ui_state_update = (ui_state: Model.ui_state, update: set_meta, ~schedule_action as _) @@ -313,11 +397,18 @@ let ui_state_update = }; }; -let rec apply = - (model: Model.t, update: t, state: State.t, ~schedule_action) - : Result.t(Model.t) => { +let apply = (model: Model.t, update: t, ~schedule_action): Result.t(Model.t) => { + let perform_action = (model: Model.t, a: Action.t): Result.t(Model.t) => { + switch ( + Editors.perform_action(~settings=model.settings.core, model.editors, a) + ) { + | Error(err) => Error(err) + | Ok(editors) => Ok({...model, editors}) + }; + }; let m: Result.t(Model.t) = switch (update) { + | Startup => Ok(on_startup(~schedule_action, model)) | Reset => Ok(Model.reset(model)) | Set(Evaluation(_) as s_action) => Ok(update_settings(s_action, model)) | Set(s_action) => @@ -356,18 +447,54 @@ let rec apply = ); Ok(model); | FinishImportScratchpad(data) => - let editors = Editors.import_current(model.editors, data); + let editors = + Editors.import_current( + ~settings=model.settings.core, + model.editors, + data, + ); Model.save_and_return({...model, editors}); - | ExportPersistentData => + | Export(ExportPersistentData) => + Model.save(model); export_persistent_data(); Ok(model); + | Export(ExportScratchSlide) => + Model.save(model); + let editor = Editors.get_editor(model.editors); + export_scratch_slide(editor); + Ok(model); + | Export(ExerciseModule) => + Model.save(model); + instructor_exercise_update(model, export_exercise_module); + | Export(Submission) => + Model.save(model); + export_submission(~instructor_mode=model.settings.instructor_mode); + Ok(model); + | Export(TransitionaryExerciseModule) => + Model.save(model); + instructor_exercise_update(model, export_transitionary); + | Export(GradingExerciseModule) => + Model.save(model); + instructor_exercise_update(model, export_instructor_grading_report); | ResetCurrentEditor => let instructor_mode = model.settings.instructor_mode; - let editors = Editors.reset_current(model.editors, ~instructor_mode); + let editors = + Editors.reset_current( + ~settings=model.settings.core, + model.editors, + ~instructor_mode, + ); Model.save_and_return({...model, editors}); | SwitchScratchSlide(n) => let instructor_mode = model.settings.instructor_mode; - switch (switch_scratch_slide(model.editors, ~instructor_mode, n)) { + switch ( + switch_scratch_slide( + ~settings=model.settings.core, + model.editors, + ~instructor_mode, + n, + ) + ) { | None => Error(FailedToSwitch) | Some(editors) => Model.save_and_return({...model, editors}) }; @@ -384,92 +511,31 @@ let rec apply = }; | TAB => /* Attempt to act intelligently when TAB is pressed. - * TODO(andrew): Consider more advanced TAB logic. Instead + * TODO: Consider more advanced TAB logic. Instead * of simply moving to next hole, if the backpack is non-empty * but can't immediately put down, move to next position of * interest, which is closet of: nearest position where can * put down, farthest position where can put down, next hole */ - let z = - model.editors - |> Editors.get_editor - |> ((ed: Editor.t) => ed.state.zipper); - let a = + let z = Editors.get_editor(model.editors).state.zipper; + let action: Action.t = Selection.is_buffer(z.selection) - ? Assistant(AcceptSuggestion) + ? Buffer(Accept) : Zipper.can_put_down(z) - ? PerformAction(Put_down) : MoveToNextHole(Right); - apply(model, a, state, ~schedule_action); - | PerformAction(a) - when model.settings.core.assist && model.settings.core.statics => - let model = UpdateAssistant.reset_buffer(model); - switch (perform_action(model, a)) { - | Ok(model) when Action.is_edit(a) => - UpdateAssistant.apply( - model, - Prompt(TyDi), - ~schedule_action, - ~state, - ~main=apply, - ) - | x => x - }; - | PerformAction(a) => perform_action(model, a) - | ReparseCurrentEditor => - /* This serializes the current editor to text, resets the current - editor, and then deserializes. It is intended as a (tactical) - nuclear option for weird backpack states */ - let ed = Editors.get_editor(model.editors); - let zipper_init = Zipper.init(); - let ed_str = Printer.to_string_editor(ed); - switch (Printer.zipper_of_string(~zipper_init, ed_str)) { - | None => Error(CantReset) - | Some(z) => - //TODO: add correct action to history (Pick_up is wrong) - let editor = Haz3lcore.Editor.new_state(Pick_up, z, ed); - let editors = Editors.put_editor(editor, model.editors); - Ok({...model, editors}); - }; - | Cut => - // system clipboard handling itself is done in Page.view handlers - perform_action(model, Destruct(Left)) - | Copy => - // system clipboard handling itself is done in Page.view handlers - // doesn't change the state but including as an action for logging purposes - Ok(model) - | Paste(clipboard) => - let ed = Editors.get_editor(model.editors); - switch (Printer.paste_into_zip(ed.state.zipper, clipboard)) { - | None => Error(CantPaste) - | Some(z) => - //HACK(andrew): below is not strictly a insert action... - let ed = Haz3lcore.Editor.new_state(Insert(clipboard), z, ed); - let editors = Editors.put_editor(ed, model.editors); - Ok({...model, editors}); - }; + ? Put_down : Move(Goal(Piece(Grout, Right))); + perform_action(model, action); + | PerformAction(a) => + let r = perform_action(model, a); + r; | Undo => - let ed = Editors.get_editor(model.editors); - switch (Haz3lcore.Editor.undo(ed)) { + switch (Editors.update_opt(model.editors, Editor.undo)) { | None => Error(CantUndo) - | Some(ed) => - Ok({...model, editors: Editors.put_editor(ed, model.editors)}) - }; + | Some(editors) => Ok({...model, editors}) + } | Redo => - let ed = Editors.get_editor(model.editors); - switch (Haz3lcore.Editor.redo(ed)) { + switch (Editors.update_opt(model.editors, Editor.redo)) { | None => Error(CantRedo) - | Some(ed) => - Ok({...model, editors: Editors.put_editor(ed, model.editors)}) - }; - | MoveToNextHole(d) => - perform_action(model, Move(Goal(Piece(Grout, d)))) - | Assistant(action) => - UpdateAssistant.apply( - model, - action, - ~schedule_action, - ~state, - ~main=apply, - ) + | Some(editors) => Ok({...model, editors}) + } | Benchmark(Start) => List.iter(schedule_action, Benchmark.actions_1); Benchmark.start(); diff --git a/src/haz3lweb/UpdateAction.re b/src/haz3lweb/UpdateAction.re index 17856fff80..cd2f145f3e 100644 --- a/src/haz3lweb/UpdateAction.re +++ b/src/haz3lweb/UpdateAction.re @@ -1,4 +1,3 @@ -open Sexplib.Std; open Util; open Haz3lcore; @@ -34,15 +33,6 @@ type stepper_action = | StepForward(int) | StepBackward; -[@deriving (show({with_path: false}), sexp, yojson)] -type agent = - | TyDi; - -[@deriving (show({with_path: false}), sexp, yojson)] -type agent_action = - | Prompt(agent) - | AcceptSuggestion; - [@deriving (show({with_path: false}), sexp, yojson)] type set_meta = | Mousedown @@ -55,14 +45,24 @@ type benchmark_action = | Start | Finish; +[@deriving (show({with_path: false}), sexp, yojson)] +type export_action = + | ExportScratchSlide + | ExportPersistentData + | ExerciseModule + | Submission + | TransitionaryExerciseModule + | GradingExerciseModule; + [@deriving (show({with_path: false}), sexp, yojson)] type t = /* meta */ + | Startup | Reset | Set(settings_action) | SetMeta(set_meta) | UpdateExplainThisModel(ExplainThisUpdate.update) - | ExportPersistentData + | Export(export_action) | DebugConsole(string) /* editors */ | ResetCurrentEditor @@ -78,15 +78,9 @@ type t = | TAB | Save | PerformAction(Action.t) - | ReparseCurrentEditor - | Cut - | Copy - | Paste(string) | Undo | Redo - | MoveToNextHole(Direction.t) | Benchmark(benchmark_action) - | Assistant(agent_action) | ToggleStepper(ModelResults.Key.t) | StepperAction(ModelResults.Key.t, stepper_action) | UpdateResult(ModelResults.t); @@ -96,12 +90,9 @@ module Failure = { type t = | CantUndo | CantRedo - | CantPaste - | CantReset - | CantSuggest - | FailedToLoad | FailedToSwitch | FailedToPerform(Action.Failure.t) + | InstructorOnly | Exception(string); }; @@ -135,43 +126,35 @@ let is_edit: t => bool = | ShowBackpackTargets(_) | FontMetrics(_) => false } - | Cut | Undo | Redo - | Paste(_) | SwitchScratchSlide(_) | SwitchDocumentationSlide(_) | ToggleStepper(_) | StepperAction(_) - | ReparseCurrentEditor | FinishImportAll(_) | FinishImportScratchpad(_) | ResetCurrentEditor - | Assistant(AcceptSuggestion) - | Reset => true + | Reset + | TAB => true | UpdateResult(_) | SwitchEditor(_) - | ExportPersistentData + | Export(_) | Save - | Copy | UpdateExplainThisModel(_) | DebugConsole(_) | InitImportAll(_) | InitImportScratchpad(_) - | MoveToNextHole(_) | Benchmark(_) - | TAB - | Assistant(Prompt(_)) => false; + | Startup => false; let reevaluate_post_update: t => bool = fun | PerformAction(a) => Action.is_edit(a) | Set(s_action) => switch (s_action) { - | Assist | Captions | SecondaryIcons - | Statics | ContextInspector | Benchmark | ExplainThis(_) @@ -184,6 +167,8 @@ let reevaluate_post_update: t => bool = ) => false | Elaborate + | Statics + | Assist | Dynamics | InstructorMode | Mode(_) => true @@ -195,33 +180,27 @@ let reevaluate_post_update: t => bool = | ShowBackpackTargets(_) | FontMetrics(_) => false } - | Assistant(AcceptSuggestion) => true - | Assistant(Prompt(_)) => false - | MoveToNextHole(_) | Save - | Copy | InitImportAll(_) | InitImportScratchpad(_) | UpdateExplainThisModel(_) - | ExportPersistentData + | Export(_) | UpdateResult(_) | SwitchEditor(_) | DebugConsole(_) - | TAB | Benchmark(_) => false + | TAB | StepperAction(_, StepForward(_) | StepBackward) | ToggleStepper(_) - | ReparseCurrentEditor | FinishImportAll(_) | FinishImportScratchpad(_) | ResetCurrentEditor | SwitchScratchSlide(_) | SwitchDocumentationSlide(_) | Reset - | Cut - | Paste(_) | Undo - | Redo => true; + | Redo + | Startup => true; let should_scroll_to_caret = fun @@ -247,38 +226,37 @@ let should_scroll_to_caret = | Mouseup | ShowBackpackTargets(_) => false } - | Assistant(Prompt(_)) | UpdateResult(_) | ToggleStepper(_) | StepperAction(_, StepBackward | StepForward(_)) => false - | Assistant(AcceptSuggestion) => true | FinishImportScratchpad(_) | FinishImportAll(_) | ResetCurrentEditor | SwitchEditor(_) | SwitchScratchSlide(_) | SwitchDocumentationSlide(_) - | ReparseCurrentEditor | Reset - | Copy - | Paste(_) - | Cut | Undo | Redo - | MoveToNextHole(_) - | TAB => true + | TAB + | Startup => true | PerformAction(a) => switch (a) { | Move(_) - | MoveToNextHole(_) | Jump(_) - | Select(Resize(_) | Term(_) | Smart | Tile(_)) + | Select(Resize(_) | Term(_) | Smart(_) | Tile(_)) | Destruct(_) | Insert(_) | Pick_up | Put_down | RotateBackpack - | MoveToBackpackTarget(_) => true + | MoveToBackpackTarget(_) + | Buffer(Set(_) | Accept | Clear) + | Paste(_) + | Copy + | Cut + | Reparse => true + | Project(_) | Unselect(_) | Select(All) => false } @@ -286,6 +264,6 @@ let should_scroll_to_caret = | InitImportAll(_) | InitImportScratchpad(_) | UpdateExplainThisModel(_) - | ExportPersistentData + | Export(_) | DebugConsole(_) | Benchmark(_) => false; diff --git a/src/haz3lweb/dune b/src/haz3lweb/dune index 6dcaeb3b1d..d3e42ec636 100644 --- a/src/haz3lweb/dune +++ b/src/haz3lweb/dune @@ -9,8 +9,8 @@ (name workerServer) (modules WorkerServer) (libraries - str - incr_dom + bonsai + bonsai.web virtual_dom.input_widgets util ppx_yojson_conv.expander @@ -18,9 +18,7 @@ haz3lschool pretty omd) - (js_of_ocaml - (flags - (:include js-of-ocaml-flags-%{profile}))) + (js_of_ocaml) (preprocess (pps ppx_yojson_conv @@ -41,7 +39,8 @@ ezjs_idb workerServer str - incr_dom + bonsai + bonsai.web virtual_dom.input_widgets util ppx_yojson_conv.expander @@ -49,32 +48,28 @@ haz3lschool pretty omd) - (js_of_ocaml - (flags - (:include js-of-ocaml-flags-%{profile}))) + (js_of_ocaml) (preprocess (pps - ppx_yojson_conv js_of_ocaml-ppx ppx_let ppx_sexp_conv - ppx_deriving.show))) + ppx_deriving.show + ppx_yojson_conv))) (executable (name main) (modules Main) (libraries ppx_yojson_conv.expander haz3lweb) (modes js) - (js_of_ocaml - (flags - (:include js-of-ocaml-flags-%{profile}))) (preprocess (pps ppx_yojson_conv js_of_ocaml-ppx ppx_let ppx_sexp_conv - ppx_deriving.show))) + ppx_deriving.show + bonsai.ppx_bonsai))) (executable (name worker) @@ -87,13 +82,7 @@ (env (dev (js_of_ocaml - (flags (:standard)))) + (flags :standard --debuginfo --noinline --dynlink --linkall --sourcemap))) (release (js_of_ocaml (flags (:standard))))) - -(rule - (write-file js-of-ocaml-flags-dev "(:standard)")) - -(rule - (write-file js-of-ocaml-flags-release "(:standard)")) diff --git a/src/haz3lweb/exercises/Ex_OddlyRecursive.ml b/src/haz3lweb/exercises/Ex_OddlyRecursive.ml index ab0a0b5ee7..3d4ae0ce35 100644 --- a/src/haz3lweb/exercises/Ex_OddlyRecursive.ml +++ b/src/haz3lweb/exercises/Ex_OddlyRecursive.ml @@ -18,8 +18,7 @@ let exercise : Exercise.spec = { siblings = ( [ - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -58,8 +57,7 @@ let exercise : Exercise.spec = ]; ]; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -136,8 +134,7 @@ let exercise : Exercise.spec = children = []; }; Secondary { id = Id.mk (); content = Whitespace " " }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; ], [] ); ancestors = @@ -264,8 +261,7 @@ let exercise : Exercise.spec = { siblings = ( [ - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -304,8 +300,7 @@ let exercise : Exercise.spec = ]; ]; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -376,10 +371,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; ]; [ Secondary @@ -455,10 +447,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; ]; ]; }; @@ -554,10 +543,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; ]; ]; }; @@ -684,8 +670,7 @@ let exercise : Exercise.spec = ]; }; Secondary { id = Id.mk (); content = Whitespace " " }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; ], [] ); ancestors = @@ -899,8 +884,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -1041,8 +1025,7 @@ let exercise : Exercise.spec = children = []; }; Secondary { id = Id.mk (); content = Whitespace " " }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; ], [ Grout { id = Id.mk (); shape = Convex } ] ); ancestors = []; @@ -1164,10 +1147,7 @@ let exercise : Exercise.spec = ]; [ Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -1219,10 +1199,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; ]; ]; }; @@ -1350,10 +1327,7 @@ let exercise : Exercise.spec = ]; [ Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -1425,10 +1399,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; ]; ]; }; @@ -1556,10 +1527,7 @@ let exercise : Exercise.spec = ]; [ Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -1631,10 +1599,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; ]; ]; }; @@ -1762,10 +1727,7 @@ let exercise : Exercise.spec = ]; [ Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -2026,8 +1988,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); - content = - Whitespace "\226\143\142"; + content = Whitespace "\n"; }; ]; ]; @@ -2170,8 +2131,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); - content = - Whitespace "\226\143\142"; + content = Whitespace "\n"; }; ]; ]; @@ -2314,8 +2274,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); - content = - Whitespace "\226\143\142"; + content = Whitespace "\n"; }; ]; ]; @@ -2434,8 +2393,7 @@ let exercise : Exercise.spec = ]; ]; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; ], [ Grout { id = Id.mk (); shape = Convex } ] ); ancestors = []; @@ -2594,8 +2552,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -2689,8 +2646,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -2830,8 +2786,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -2925,8 +2880,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -3067,8 +3021,7 @@ let exercise : Exercise.spec = children = []; }; Secondary { id = Id.mk (); content = Whitespace " " }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); diff --git a/src/haz3lweb/exercises/Ex_RecursiveFibonacci.ml b/src/haz3lweb/exercises/Ex_RecursiveFibonacci.ml index 1e95c4719d..cdcf9cb651 100644 --- a/src/haz3lweb/exercises/Ex_RecursiveFibonacci.ml +++ b/src/haz3lweb/exercises/Ex_RecursiveFibonacci.ml @@ -30,8 +30,7 @@ let exercise : Exercise.spec = siblings = ( [ Secondary { id = Id.mk (); content = Whitespace " " }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -71,8 +70,7 @@ let exercise : Exercise.spec = ]; }; Secondary { id = Id.mk (); content = Whitespace " " }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -164,10 +162,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; ]; ]; }; @@ -357,10 +352,7 @@ let exercise : Exercise.spec = }; Secondary { id = Id.mk (); content = Whitespace " " }; ], - [ - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; - ] ); + [ Secondary { id = Id.mk (); content = Whitespace "\n" } ] ); ancestors = [ ( { @@ -607,10 +599,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -660,10 +649,7 @@ let exercise : Exercise.spec = { id = Id.mk (); content = Whitespace " " }; Grout { id = Id.mk (); shape = Convex }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; ]; ]; }; @@ -794,10 +780,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -852,10 +835,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -992,8 +972,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); - content = - Whitespace "\226\143\142"; + content = Whitespace "\n"; }; ]; ]; @@ -1136,8 +1115,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); - content = - Whitespace "\226\143\142"; + content = Whitespace "\n"; }; ]; ]; @@ -1383,10 +1361,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; ]; ]; }; @@ -1516,10 +1491,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -1574,10 +1546,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -1719,8 +1688,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); - content = - Whitespace "\226\143\142"; + content = Whitespace "\n"; }; ]; ]; @@ -1964,10 +1932,7 @@ let exercise : Exercise.spec = Secondary { id = Id.mk (); content = Whitespace " " }; Secondary - { - id = Id.mk (); - content = Whitespace "\226\143\142"; - }; + { id = Id.mk (); content = Whitespace "\n" }; ]; ]; }; @@ -2118,8 +2083,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -2247,8 +2211,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -2376,8 +2339,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -2505,8 +2467,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -2634,8 +2595,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -2763,8 +2723,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -2892,8 +2851,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -3021,8 +2979,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; Tile { id = Id.mk (); @@ -3150,8 +3107,7 @@ let exercise : Exercise.spec = shards = [ 0 ]; children = []; }; - Secondary - { id = Id.mk (); content = Whitespace "\226\143\142" }; + Secondary { id = Id.mk (); content = Whitespace "\n" }; ], [ Grout { id = Id.mk (); shape = Convex } ] ); ancestors = []; diff --git a/src/haz3lweb/explainthis/Example.re b/src/haz3lweb/explainthis/Example.re index 5bd8a27c77..531f9c0914 100644 --- a/src/haz3lweb/explainthis/Example.re +++ b/src/haz3lweb/explainthis/Example.re @@ -3,16 +3,7 @@ open Haz3lcore; let mk_secondary: string => Piece.t = content => Secondary({id: Id.mk(), content: Whitespace(content)}); -let mk_tile: (Form.t, list(list(Piece.t))) => Piece.t = - //TODO: asserts - (form, children) => - Tile({ - id: Id.mk(), - label: form.label, - mold: form.mold, - shards: List.mapi((i, _) => i, form.label), - children, - }); +let mk_tile = Piece.mk_tile; let mk_ancestor: (Form.t, (list(Segment.t), list(Segment.t))) => Ancestor.t = //TODO: asserts @@ -120,6 +111,7 @@ let typeann = () => mk_monotile(Form.get("typeann")); let mk_typfun = mk_tile(Form.get("typfun")); let mk_fun = mk_tile(Form.get("fun_")); let mk_ap_exp_typ = mk_tile(Form.get("ap_exp_typ")); +let mk_fix = mk_tile(Form.get("fix")); let mk_ap_exp = mk_tile(Form.get("ap_exp")); let mk_ap_pat = mk_tile(Form.get("ap_pat")); let mk_let = mk_tile(Form.get("let_")); diff --git a/src/haz3lweb/explainthis/ExplainThisForm.re b/src/haz3lweb/explainthis/ExplainThisForm.re index fe10130b6b..1f3a54dcf8 100644 --- a/src/haz3lweb/explainthis/ExplainThisForm.re +++ b/src/haz3lweb/explainthis/ExplainThisForm.re @@ -1,4 +1,5 @@ -open Sexplib.Std; +open Util; + open Haz3lcore; // TODO Make unified way of using consistent metavariables for syntactic forms @@ -84,6 +85,8 @@ type example_id = | List(list_examples) | TypFun(typfun_examples) | Fun(fun_examples) + | Fix1 + | Fix2 | Tuple1 | Tuple2 | Let(let_examples) @@ -120,7 +123,9 @@ type example_id = | FilterEval | FilterHide | FilterDebug - | FilterSelector; + | FilterSelector + | Undefined1 + | Undefined2; [@deriving (show({with_path: false}), sexp, yojson)] type example = { @@ -155,6 +160,7 @@ type form_id = | EmptyHoleExp | MultiHoleExp | TrivExp + | UndefinedExp | DeferralExp | BoolExp | IntExp @@ -174,6 +180,7 @@ type form_id = | ModuleExp | DotExp | ModuleVarExp + | FixExp(pat_sub_form_id) | TypFunApExp | FunApExp | ConApExp @@ -181,8 +188,8 @@ type form_id = | IfExp | SeqExp | TestExp - | UnOpExp(Term.UExp.op_un) - | BinOpExp(Term.UExp.op_bin) + | UnOpExp(Operators.op_un) + | BinOpExp(Operators.op_bin) | CaseExp | TyAliasExp | EmptyHolePat @@ -252,6 +259,7 @@ type group_id = | EmptyHoleExp | MultiHoleExp | TrivExp + | UndefinedExp | DeferralExp | BoolExp | IntExp @@ -272,14 +280,15 @@ type group_id = | DotExp | ModuleVarExp | TypFunApExp + | FixExp(pat_sub_form_id) | FunApExp | ConApExp | DeferredApExp | IfExp | SeqExp | TestExp - | UnOpExp(Term.UExp.op_un) - | BinOpExp(Term.UExp.op_bin) + | UnOpExp(Operators.op_un) + | BinOpExp(Operators.op_bin) | CaseExp | TyAliasExp | PipelineExp diff --git a/src/haz3lweb/explainthis/ExplainThisModel.re b/src/haz3lweb/explainthis/ExplainThisModel.re index d48105713c..92ab95a342 100644 --- a/src/haz3lweb/explainthis/ExplainThisModel.re +++ b/src/haz3lweb/explainthis/ExplainThisModel.re @@ -1,4 +1,3 @@ -open Sexplib.Std; module Sexp = Sexplib.Sexp; open Haz3lcore; open ExplainThisForm; diff --git a/src/haz3lweb/explainthis/ExplainThisUpdate.re b/src/haz3lweb/explainthis/ExplainThisUpdate.re index bb3646cdea..8946a4818c 100644 --- a/src/haz3lweb/explainthis/ExplainThisUpdate.re +++ b/src/haz3lweb/explainthis/ExplainThisUpdate.re @@ -1,7 +1,6 @@ -open Sexplib.Std; +open Util; open ExplainThisForm; open ExplainThisModel; -open Util; [@deriving (show({with_path: false}), sexp, yojson)] type update = diff --git a/src/haz3lweb/explainthis/data/FixFExp.re b/src/haz3lweb/explainthis/data/FixFExp.re new file mode 100644 index 0000000000..b106b6be8e --- /dev/null +++ b/src/haz3lweb/explainthis/data/FixFExp.re @@ -0,0 +1,54 @@ +open Haz3lcore; +open ExplainThisForm; +open Example; + +let single = (~pat_id: Id.t, ~body_id: Id.t): Simple.t => { + /* (B) You'll need to add new cases to ExplainThisForm.re for the new form + * to represent a group_id and form_id. This Simple style is specialized + * to singleton groups. In general, the group_id needs to be unique, and + * form_ids need to be unique within a group. These ids are used to track + * ExplainThis persistent state. */ + group_id: FixExp(Base), + form_id: FixExp(Base), + /* (C) The abstract field defines an abstract example illustrating the + * new form. You'll need to provide pairs associating any representative + * subterms of the exemplar (e.g. "e_arg" and "e_fun" below) with the + * concrete subterms of the term the user has selected (here, arg_id + * and fn_id). You'll then need a function to construct a segment + * representing your abstract. This is done in this indirect way so + * as to associate representative and concrete subterms ids for + * syntax highlighting purposes. */ + abstract: + Simple.mk_2(("p", pat_id), ("e", body_id), (p, e) => + [mk_fix([[space(), p, space()]]), space(), e] + ), + /* (D) The explanation which will appear in the sidebar below the abstract */ + explanation: + Printf.sprintf( + "Recursively replaces all occurences of the [*pattern*](%s) inside the [*body*](%s) with the entire [*body*](%s) itself, effectively creating an infinite expression. Unless [*pattern*](%s) is a function, it is likely to evaluate forever.", + pat_id |> Id.to_string, + body_id |> Id.to_string, + body_id |> Id.to_string, + pat_id |> Id.to_string, + ), + /* (E) Additional more concrete examples and associated explanations */ + examples: [ + { + sub_id: Fix1, + term: mk_example("fix x -> x + 1"), + message: {| + Tries to create the infinite expression (((...) + 1) + 1) + 1 but times out + |}, + }, + { + sub_id: Fix2, + term: + mk_example( + "(fix f -> fun x -> \nif x == 0 then \n0 \nelse \nf(x-1) + 2\n) (5)", + ), + message: {| + A recursive function that doubles a given number. + |}, + }, + ], +}; diff --git a/src/haz3lweb/explainthis/data/UndefinedExp.re b/src/haz3lweb/explainthis/data/UndefinedExp.re new file mode 100644 index 0000000000..71ff320576 --- /dev/null +++ b/src/haz3lweb/explainthis/data/UndefinedExp.re @@ -0,0 +1,33 @@ +open ExplainThisForm; +open Example; + +let undefined_ex_1 = { + sub_id: Undefined2, + term: + mk_example( + "let sgn = \nfun num ->\nif num == 0 \nthen undefined \nelse\nif num > 0 \nthen \"+\"\nelse \"-\"\nin\n(sgn(-1), sgn(0), sgn(5))", + ), + message: "The undefined expression can be used in cases where a partial function is undefined.", +}; + +let undefined_ex_2 = { + sub_id: Undefined1, + term: + mk_example( + "let sum : [Int] -> Int =\nfun xs ->\ncase undefined\n| [] => 0\n| hd::tl => \nend\nin\nsum([1,2,3])", + ), + message: "The undefined expression behaves much like a hole during evaluation.", +}; + +let undefined_exp: form = { + let explanation = "Represents an expression that lacks definition."; + { + id: UndefinedExp, + syntactic_form: [exp("undefined")], + expandable_id: None, + explanation, + examples: [undefined_ex_1, undefined_ex_2], + }; +}; + +let undefined_exps: group = {id: UndefinedExp, forms: [undefined_exp]}; diff --git a/src/haz3lweb/util/AttrUtil.re b/src/haz3lweb/util/AttrUtil.re deleted file mode 100644 index ad241bf1fb..0000000000 --- a/src/haz3lweb/util/AttrUtil.re +++ /dev/null @@ -1,21 +0,0 @@ -open Virtual_dom.Vdom.Attr; - -let fstr = f => Printf.sprintf("%f", f); - -let cx = f => create("cx", fstr(f)); -let cy = f => create("cy", fstr(f)); -let rx = f => create("rx", fstr(f)); -let ry = f => create("ry", fstr(f)); - -let x = f => create("x", fstr(f)); -let y = f => create("y", fstr(f)); -let width = f => create("width", fstr(f)); -let height = f => create("height", fstr(f)); - -let stroke_width = f => create("stroke-width", fstr(f)); -let vector_effect = s => create("vector-effect", s); -let filter = s => create("filter", s); - -let offset = f => create("offset", Printf.sprintf("%f%%", 100. *. f)); -let stop_color = s => create("stop-color", s); -let stop_opacity = f => create("stop-opacity", Printf.sprintf("%f", f)); diff --git a/src/haz3lweb/util/Memo.re b/src/haz3lweb/util/Memo.re deleted file mode 100644 index deb3a35264..0000000000 --- a/src/haz3lweb/util/Memo.re +++ /dev/null @@ -1,11 +0,0 @@ -let memoize = (f: 'k => 'v): ('k => 'v) => { - let table: WeakMap.t('k, 'v) = WeakMap.mk(); - k => - switch (WeakMap.get(table, k)) { - | None => - let v = f(k); - let _ = WeakMap.set(table, k, v); - v; - | Some(v) => v - }; -}; diff --git a/src/haz3lweb/util/NodeUtil.re b/src/haz3lweb/util/NodeUtil.re deleted file mode 100644 index f56a2c5acb..0000000000 --- a/src/haz3lweb/util/NodeUtil.re +++ /dev/null @@ -1,6 +0,0 @@ -open Virtual_dom.Vdom; - -let svg = (attrs, children) => - Node.create_svg("svg", ~attr=Attr.many(attrs), children); - -let stop = attrs => Node.create_svg("stop", ~attr=Attr.many(attrs), []); diff --git a/src/haz3lweb/util/SvgUtil.re b/src/haz3lweb/util/SvgUtil.re index 458fdfe371..5809f70432 100644 --- a/src/haz3lweb/util/SvgUtil.re +++ b/src/haz3lweb/util/SvgUtil.re @@ -123,8 +123,7 @@ module Path = { }); Node.create_svg( "path", - ~attr= - Attr.many([Attr.create("d", Buffer.contents(buffer)), ...attrs]), + ~attrs=[Attr.create("d", Buffer.contents(buffer)), ...attrs], [], ); }; diff --git a/src/haz3lweb/util/WorkerServer.re b/src/haz3lweb/util/WorkerServer.re index db84af52ba..debb55a537 100644 --- a/src/haz3lweb/util/WorkerServer.re +++ b/src/haz3lweb/util/WorkerServer.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; [@deriving (sexp, yojson)] type key = string; diff --git a/src/haz3lweb/view/BackpackView.re b/src/haz3lweb/view/BackpackView.re index b2f9424986..3acdcb8c3f 100644 --- a/src/haz3lweb/view/BackpackView.re +++ b/src/haz3lweb/view/BackpackView.re @@ -1,6 +1,45 @@ open Virtual_dom.Vdom; open Node; open Haz3lcore; +open Util; + +/* Assume this doesn't contain projectors */ +let measured_of = seg => Measured.of_segment(seg, Id.Map.empty); + +let text_view = (seg: Segment.t): list(Node.t) => { + module Text = + Code.Text({ + let map = measured_of(seg); + let settings = Init.startup.settings; + let info_map = Id.Map.empty; /* Assume this doesn't contain projectors */ + }); + Text.of_segment([], true, Any, seg); +}; + +let segment_origin = (seg: Segment.t): option(Point.t) => + Option.map( + first => Measured.find_p(first, measured_of(seg)).origin, + ListUtil.hd_opt(seg), + ); + +let segment_last = (seg: Segment.t): option(Point.t) => + Option.map( + last => Measured.find_p(last, measured_of(seg)).last, + ListUtil.last_opt(seg), + ); + +let segment_height = (seg: Segment.t) => + switch (segment_last(seg), segment_origin(seg)) { + | (Some(last), Some(first)) => 1 + last.row - first.row + | _ => 0 + }; + +let segment_width = (seg: Segment.t): int => + IntMap.fold( + (_, {max_col, _}: Measured.Rows.shape, acc) => max(max_col, acc), + measured_of(seg).rows, + 0, + ); let backpack_sel_view = ( @@ -10,44 +49,38 @@ let backpack_sel_view = opacity: float, {focus: _, content, _}: Selection.t, ) => { - module Text = - Code.Text({ - let map = Measured.of_segment(content); - let settings = Init.startup.settings; - }); - // TODO(andrew): Maybe use init sort at caret to prime this + // Maybe use init sort at caret to prime this div( - ~attr= - Attr.many([ - Attr.classes(["code-text", "backpack-selection"]), - Attr.create( - "style", - Printf.sprintf( - "position: absolute; transform-origin: bottom left; transform: translate(%fpx, %fpx) scale(%f); opacity: %f%%;", - x_off, - y_off, - scale, - opacity, - ), + ~attrs=[ + Attr.classes(["code-text", "code", "backpack-selection"]), + Attr.create( + "style", + Printf.sprintf( + "position: absolute; transform-origin: bottom left; transform: translate(%fpx, %fpx) scale(%f); opacity: %f%%;", + x_off, + y_off, + scale, + opacity, ), - ]), + ), + ], // zwsp necessary for containing box to stretch to contain trailing newline - Text.of_segment([], true, Any, content) @ [text(Unicode.zwsp)], + text_view(content) @ [text(Unicode.zwsp)], ); }; let view = ( ~font_metrics: FontMetrics.t, - ~origin: Measured.Point.t, + ~origin: Point.t, {backpack, _} as z: Zipper.t, ) : Node.t => { - //TODO(andrew): clean up this dumpster fire of a function + // This function is a mess let height_head = switch (backpack) { | [] => 0 - | [hd, ..._] => Measured.segment_height(hd.content) + | [hd, ..._] => segment_height(hd.content) }; let can_put_down = switch (Zipper.pop_backpack(z)) { @@ -63,10 +96,10 @@ let view = | Some((_, side, _)) => side | _ => Right }; - DecUtil.caret_adjust(side, shape); + DecUtil.shape_adjust(side, shape); }; let caret_adj_px = - //TODO(andrew): figure out why we need this mystery pixel below + // Figure out why we need this mystery pixel below (-1.) +. caret_adj *. font_metrics.col_width; let max_disp = 3; /* Maximum vertical backpack displacement */ let vertical_disp = origin.row <= max_disp ? origin.row : max_disp; @@ -91,14 +124,14 @@ let view = let (_, _, _, selections) = List.fold_left( ((idx, y_offset, opacity, vs), s: Selection.t) => { - let base_height = Measured.segment_height(s.content); + let base_height = segment_height(s.content); let scale = scale_fn(idx); let x_offset = x_fn(idx); let new_y_offset = y_offset -. dy_fn(idx, base_height); let v = backpack_sel_view(x_offset, new_y_offset, scale, opacity, s); let new_idx = idx + 1; let new_opacity = opacity -. opacity_reduction; - //TODO(andrew): am i making this difficult by going backwards? + // Am i making this difficult by going backwards? (new_idx, new_y_offset, new_opacity, List.cons(v, vs)); }, (init_idx, init_y_offset, init_opacity, []), @@ -106,17 +139,16 @@ let view = ); let selections_view = div( - ~attr= - Attr.many([ - Attr.create("style", selections_style), - Attr.classes(["backpack"]), - ]), + ~attrs=[ + Attr.create("style", selections_style), + Attr.classes(["backpack"]), + ], selections, ); let length = switch (backpack) { | [] => 0 - | [hd, ..._] => Measured.segment_width(hd.content) + | [hd, ..._] => segment_width(hd.content) }; let joiner_style = @@ -130,20 +162,18 @@ let view = ); let joiner = div( - ~attr= - Attr.many([ - Attr.create("style", joiner_style), - Attr.classes(["backpack-joiner"]), - ]), + ~attrs=[ + Attr.create("style", joiner_style), + Attr.classes(["backpack-joiner"]), + ], [], ); - //TODO(andrew): break out backpack decoration into its own module let genie_view = DecUtil.code_svg( ~font_metrics, ~origin={row: 0, col: 0}, ~base_cls=["restructuring-genie"], - ~path_cls=["restructuring-genie-path"], + ~path_cls=["backpack-genie"], SvgUtil.Path.[ M({x: 0., y: 0.}), V({y: (-1.0)}), @@ -161,15 +191,12 @@ let view = +. 1., ); div( - ~attr= - Attr.many([ - Attr.classes( - ["backpack"] @ (can_put_down ? [] : ["cant-put-down"]), - ), - ]), + ~attrs=[ + Attr.classes(["backpack"] @ (can_put_down ? [] : ["cant-put-down"])), + ], [ selections_view, - div(~attr=Attr.create("style", genie_style), [genie_view]), + div(~attrs=[Attr.create("style", genie_style)], [genie_view]), ] @ (backpack != [] ? [joiner] : []), ); diff --git a/src/haz3lweb/view/Cell.re b/src/haz3lweb/view/Cell.re index 818e69837b..65c01e1a6f 100644 --- a/src/haz3lweb/view/Cell.re +++ b/src/haz3lweb/view/Cell.re @@ -1,3 +1,4 @@ +open Util; open Virtual_dom.Vdom; open Haz3lcore; open Node; @@ -6,7 +7,7 @@ let get_goal = (~font_metrics: FontMetrics.t, ~target_id, e) => { let rect = JsUtil.get_elem_by_id(target_id)##getBoundingClientRect; let goal_x = float_of_int(e##.clientX); let goal_y = float_of_int(e##.clientY); - Measured.Point.{ + Point.{ row: Float.to_int((goal_y -. rect##.top) /. font_metrics.row_height), col: Float.( @@ -17,19 +18,17 @@ let get_goal = (~font_metrics: FontMetrics.t, ~target_id, e) => { let mousedown_overlay = (~inject, ~font_metrics, ~target_id) => div( - ~attr= - Attr.many( - Attr.[ - id("mousedown-overlay"), - on_mouseup(_ => inject(Update.SetMeta(Mouseup))), - on_mousemove(e => { - let goal = get_goal(~font_metrics, ~target_id, e); - inject( - Update.PerformAction(Select(Resize(Goal(Point(goal))))), - ); - }), - ], - ), + ~attrs= + Attr.[ + id("mousedown-overlay"), + on_mouseup(_ => inject(Update.SetMeta(Mouseup))), + on_mousemove(e => { + let goal = get_goal(~font_metrics, ~target_id, e); + inject( + Update.PerformAction(Select(Resize(Goal(Point(goal))))), + ); + }), + ], [], ); @@ -44,7 +43,6 @@ let mousedown_handler = switch (JsUtil.ctrl_held(evt), JsUtil.num_clicks(evt)) { | (true, _) => let goal = get_goal(~font_metrics, ~target_id, evt); - let events = [ inject(PerformAction(Move(Goal(Point(goal))))), inject(PerformAction(Jump(BindingSiteOfIndicatedVar))), @@ -52,37 +50,38 @@ let mousedown_handler = Virtual_dom.Vdom.Effect.Many(events); | (false, 1) => let goal = get_goal(~font_metrics, ~target_id, evt); + /* Note that we only trigger drag mode (set mousedown) + * when the left mouse button (aka button 0) is pressed */ Virtual_dom.Vdom.Effect.Many( List.map( inject, Update.( - [SetMeta(Mousedown)] + (JsUtil.mouse_button(evt) == 0 ? [SetMeta(Mousedown)] : []) @ mousedown_updates @ [PerformAction(Move(Goal(Point(goal))))] ), ), ); - | (false, 2) => inject(PerformAction(Select(Tile(Current)))) - | (false, 3 | _) => inject(PerformAction(Select(Smart))) + | (false, n) => inject(PerformAction(Select(Smart(n)))) }; let narrative_cell = (content: Node.t) => div( - ~attr=Attr.class_("cell"), - [div(~attr=Attr.class_("cell-chapter"), [content])], + ~attrs=[Attr.class_("cell")], + [div(~attrs=[Attr.class_("cell-chapter")], [content])], ); let simple_cell_item = (content: list(Node.t)) => - div(~attr=Attr.classes(["cell-item"]), content); + div(~attrs=[Attr.classes(["cell-item"])], content); let caption = (~rest: option(string)=?, bolded: string) => div( - ~attr=Attr.many([Attr.classes(["cell-caption"])]), + ~attrs=[Attr.classes(["cell-caption"])], [strong([text(bolded)])] @ (rest |> Option.map(text) |> Option.to_list), ); let simple_cell_view = (items: list(t)) => - div(~attr=Attr.class_("cell"), items); + div(~attrs=[Attr.class_("cell")], items); let test_status_icon_view = (~font_metrics, insts, ms: Measured.Shards.t): option(t) => @@ -90,65 +89,62 @@ let test_status_icon_view = | [(_, {origin: _, last}), ..._] => let status = insts |> TestMap.joint_status |> TestStatus.to_string; let pos = DecUtil.abs_position(~font_metrics, last); - Some( - div( - ~attr=Attr.many([Attr.classes(["test-result", status]), pos]), - [], - ), - ); + Some(div(~attrs=[Attr.classes(["test-result", status]), pos], [])); | _ => None }; let test_result_layer = - (~font_metrics, ~measured: Measured.t, test_results: TestResults.t) - : list(t) => - List.filter_map( - ((id, insts)) => - switch (Id.Map.find_opt(id, measured.tiles)) { - | Some(ms) => test_status_icon_view(~font_metrics, insts, ms) - | None => None - }, - test_results.test_map, + (~font_metrics, ~measured: Measured.t, test_results: TestResults.t): t => + Web.div_c( + "test-decos", + List.filter_map( + ((id, insts)) => + switch (Id.Map.find_opt(id, measured.tiles)) { + | Some(ms) => test_status_icon_view(~font_metrics, insts, ms) + | None => None + }, + test_results.test_map, + ), ); let deco = ( - ~font_metrics, - ~show_backpack_targets, + ~inject, + ~ui_state, ~selected, - ~error_ids, ~test_results: option(TestResults.t), ~highlights: option(ColorSteps.colorMap), - { - state: { - zipper, - meta: {term_ranges, segment, measured, terms, tiles, _}, - _, - }, - _, - }: Editor.t, + z, + meta: Editor.Meta.t, ) => { module Deco = Deco.Deco({ - let map = measured; - let terms = terms; - let term_ranges = term_ranges; - let tiles = tiles; - let font_metrics = font_metrics; - let show_backpack_targets = show_backpack_targets; - let error_ids = error_ids; + let ui_state = ui_state; + let meta = meta; + let highlights = highlights; }); - let decos = selected ? Deco.all(zipper, segment) : Deco.err_holes(zipper); + let decos = selected ? Deco.all(z) : Deco.always(); let decos = - switch (test_results) { - | None => decos - | Some(test_results) => - decos @ test_result_layer(~font_metrics, ~measured, test_results) // TODO move into decos - }; - switch (highlights) { - | Some(colorMap) => - decos @ Deco.color_highlights(ColorSteps.to_list(colorMap)) - | _ => decos + decos + @ [ + ProjectorView.all( + z, + ~meta, + ~inject, + ~font_metrics=ui_state.font_metrics, + ), + ]; + switch (test_results) { + | None => decos + | Some(test_results) => + decos + @ [ + test_result_layer( + ~font_metrics=ui_state.font_metrics, + ~measured=meta.syntax.measured, + test_results, + ), + ] // TODO move into decos }; }; @@ -180,7 +176,7 @@ let live_eval = switch (result.evaluation, result.previous) { | (ResultOk(res), _) => ProgramResult.get_dhexp(res) | (ResultPending, ResultOk(res)) => ProgramResult.get_dhexp(res) - | _ => result.elab + | _ => result.elab.d }; let dhcode_view = DHCode.view( @@ -191,28 +187,32 @@ let live_eval = ~font_metrics, ~width=80, ~result_key, + ~infomap=Id.Map.empty, dhexp, ); let exn_view = switch (result.evaluation) { | ResultFail(err) => [ - div(~attr=Attr.classes(["error-msg"]), [text(error_msg(err))]), + div( + ~attrs=[Attr.classes(["error-msg"])], + [text(error_msg(err))], + ), ] | _ => [] }; div( - ~attr=Attr.classes(["cell-item", "cell-result"]), + ~attrs=[Attr.classes(["cell-item", "cell-result"])], exn_view @ [ div( - ~attr=Attr.classes(["status", status_of(result.evaluation)]), + ~attrs=[Attr.classes(["status", status_of(result.evaluation)])], [ - div(~attr=Attr.classes(["spinner"]), []), - div(~attr=Attr.classes(["eq"]), [text("≡")]), + div(~attrs=[Attr.classes(["spinner"])], []), + div(~attrs=[Attr.classes(["eq"])], [text("≡")]), ], ), div( - ~attr=Attr.classes(["result", status_of(result.evaluation)]), + ~attrs=[Attr.classes(["result", status_of(result.evaluation)])], [dhcode_view], ), Widgets.toggle(~tooltip="Show Stepper", "s", false, _ => @@ -243,15 +243,15 @@ let footer = ~settings=settings.core.evaluation, ~font_metrics, ~result_key, + ~read_only=false, s, ) }; let editor_view = ( - ~inject, - ~ui_state as - {font_metrics, show_backpack_targets, mousedown, _}: Model.ui_state, + ~inject: UpdateAction.t => Ui_effect.t(unit), + ~ui_state: Model.ui_state, ~settings: Settings.t, ~target_id: string, ~mousedown_updates: list(Update.t)=[], @@ -262,30 +262,41 @@ let editor_view = ~footer: option(list(Node.t))=?, ~highlights: option(ColorSteps.colorMap), ~overlayer: option(Node.t)=None, - ~error_ids: list(Id.t), ~sort=Sort.root, + ~override_statics: option(Editor.CachedStatics.t)=?, editor: Editor.t, ) => { - let code_text_view = Code.view(~sort, ~font_metrics, ~settings, editor); + let Model.{font_metrics, mousedown, _} = ui_state; + let meta = + /* For exercises modes */ + switch (override_statics) { + | None => editor.state.meta + | Some(statics) => {...editor.state.meta, statics} + }; + let mousedown_overlay = + selected && mousedown + ? [mousedown_overlay(~inject, ~font_metrics, ~target_id)] : []; + let code_text_view = + Code.view(~sort, ~font_metrics, ~settings, editor.state.zipper, meta); let deco_view = deco( - ~font_metrics, - ~show_backpack_targets, + ~inject, + ~ui_state, ~selected, - ~error_ids, ~test_results, ~highlights, - editor, + editor.state.zipper, + meta, ); + let code_view = div( - ~attr= - Attr.many([Attr.id(target_id), Attr.classes(["code-container"])]), - [code_text_view] @ deco_view @ Option.to_list(overlayer), + ~attrs=[Attr.id(target_id), Attr.classes(["code-container"])], + [code_text_view] + @ deco_view + @ Option.to_list(overlayer) + @ mousedown_overlay, ); - let mousedown_overlay = - selected && mousedown - ? [mousedown_overlay(~inject, ~font_metrics, ~target_id)] : []; let on_mousedown = locked ? _ => @@ -297,20 +308,20 @@ let editor_view = ~mousedown_updates, ); div( - ~attr= + ~attrs=[ Attr.classes([ "cell", selected ? "selected" : "deselected", locked ? "locked" : "unlocked", ]), + ], [ div( - ~attr= - Attr.many([ - Attr.classes(["cell-item"]), - Attr.on_mousedown(on_mousedown), - ]), - Option.to_list(caption) @ mousedown_overlay @ [code_view], + ~attrs=[ + Attr.classes(["cell-item"]), + Attr.on_mousedown(on_mousedown), + ], + Option.to_list(caption) @ [code_view], ), ] @ (footer |> Option.to_list |> List.concat), @@ -318,7 +329,7 @@ let editor_view = }; let report_footer_view = content => { - div(~attr=Attr.classes(["cell-item", "cell-report"]), content); + div(~attrs=[Attr.classes(["cell-item", "cell-report"])], content); }; let test_report_footer_view = (~inject, ~test_results: option(TestResults.t)) => { @@ -327,7 +338,9 @@ let test_report_footer_view = (~inject, ~test_results: option(TestResults.t)) => let panel = (~classes=[], content, ~footer: option(t)) => { simple_cell_view( - [div(~attr=Attr.classes(["cell-item", "panel"] @ classes), content)] + [ + div(~attrs=[Attr.classes(["cell-item", "panel"] @ classes)], content), + ] @ Option.to_list(footer), ); }; @@ -335,8 +348,8 @@ let panel = (~classes=[], content, ~footer: option(t)) => { let title_cell = title => { simple_cell_view([ div( - ~attr=Attr.class_("title-cell"), - [div(~attr=Attr.class_("title-text"), [text(title)])], + ~attrs=[Attr.class_("title-cell")], + [div(~attrs=[Attr.class_("title-text")], [text(title)])], ), ]); }; @@ -365,10 +378,11 @@ let locked_no_statics = ~target_id, ~footer=[], ~test_results=None, - ~error_ids=[], ~overlayer=Some(expander_deco), ~sort, - segment |> Zipper.unzip |> Editor.init(~read_only=true), + segment + |> Zipper.unzip + |> Editor.init(~settings=CoreSettings.off, ~read_only=true), ), ]; @@ -383,24 +397,25 @@ let locked = ~target_id, ~segment: Segment.t, ) => { - let editor = segment |> Zipper.unzip |> Editor.init(~read_only=true); - let statics = - settings.core.statics - ? ScratchSlide.mk_statics(~settings, editor, Builtins.ctx_init) - : CachedStatics.empty_statics; + let editor = + segment + |> Zipper.unzip + |> Editor.init(~settings=settings.core, ~read_only=true); + let statics = editor.state.meta.statics; let elab = settings.core.elaborate || settings.core.dynamics ? Interface.elaborate( ~settings=settings.core, statics.info_map, - editor.state.meta.view_term, + statics.term, ) - : DHExp.BoolLit(true); + : DHExp.Bool(true) |> DHExp.fresh; + let elab: Elaborator.Elaboration.t = {d: elab}; let result: ModelResult.t = settings.core.dynamics ? Evaluation({ elab, - evaluation: Interface.evaluate(~settings=settings.core, elab), + evaluation: Interface.evaluate(~settings=settings.core, elab.d), previous: ResultPending, }) : NoElab; @@ -425,7 +440,6 @@ let locked = ~target_id, ~footer, ~test_results=ModelResult.test_results(result), - ~error_ids=statics.error_ids, editor, ); }; diff --git a/src/haz3lweb/view/Code.re b/src/haz3lweb/view/Code.re index a68fbbe6a8..608c6fad09 100644 --- a/src/haz3lweb/view/Code.re +++ b/src/haz3lweb/view/Code.re @@ -7,7 +7,7 @@ open Util.Web; let of_delim' = Core.Memo.general( ~cache_size_bound=10000, - ((label, is_in_buffer, sort, is_consistent, is_complete, i)) => { + ((label, is_in_buffer, sort, is_consistent, is_complete, indent, i)) => { let cls = switch (label) { | _ when is_in_buffer => "in-buffer" @@ -15,45 +15,53 @@ let of_delim' = | _ when !is_complete => "incomplete" | [s] when s == Form.explicit_hole => "explicit-hole" | [s] when Form.is_string(s) => "string-lit" - | _ => "default" + | _ => Sort.to_string(sort) }; let plurality = List.length(label) == 1 ? "mono" : "poly"; - let label = is_in_buffer ? AssistantExpander.mark(label) : label; + //let label = is_in_buffer ? AssistantExpander.mark(label) : label; + let token = List.nth(label, i); + /* Add indent to multiline tokens: */ + let token = + StringUtil.num_linebreaks(token) == 0 + ? token : token ++ StringUtil.repeat(indent, Unicode.nbsp); [ span( - ~attr= - Attr.classes(["token", cls, Sort.to_string(sort), plurality]), - [Node.text(List.nth(label, i))], + ~attrs=[Attr.classes(["token", cls, plurality])], + [Node.text(token)], ), ]; }, ); let of_delim = - (is_in_buffer, is_consistent, t: Piece.tile, i: int): list(Node.t) => + (is_in_buffer, is_consistent, indent, t: Piece.tile, i: int) + : list(Node.t) => of_delim'(( t.label, is_in_buffer, t.mold.out, is_consistent, Tile.is_complete(t), + indent, i, )); -let of_grout = [Node.text(Unicode.nbsp)]; +let space = " "; //Unicode.nbsp; + +let of_grout = [Node.text(space)]; let of_secondary = Core.Memo.general( ~cache_size_bound=10000, ((content, secondary_icons, indent)) => if (String.equal(Secondary.get_string(content), Form.linebreak)) { - let str = secondary_icons ? Form.linebreak : ""; + let str = secondary_icons ? ">" : ""; [ span_c("linebreak", [text(str)]), - Node.br(), - Node.text(StringUtil.repeat(indent, Unicode.nbsp)), + Node.text("\n"), + Node.text(StringUtil.repeat(indent, space)), ]; } else if (String.equal(Secondary.get_string(content), Form.space)) { - let str = secondary_icons ? "·" : Unicode.nbsp; - [span_c("secondary", [text(str)])]; + let str = secondary_icons ? "·" : space; + [span_c("whitespace", [text(str)])]; } else if (Secondary.content_is_comment(content)) { [span_c("comment", [Node.text(Secondary.get_string(content))])]; } else { @@ -61,11 +69,26 @@ let of_secondary = } ); -module Text = (M: { - let map: Measured.t; - let settings: Settings.t; - }) => { - let m = p => Measured.find_p(p, M.map); +let of_projector = (p, expected_sort, indent, info_map) => + of_delim'(( + [Projector.placeholder(p, Id.Map.find_opt(p.id, info_map))], + false, + expected_sort, + true, + true, + indent, + 0, + )); + +module Text = + ( + M: { + let map: Measured.t; + let settings: Settings.t; + let info_map: Statics.Map.t; + }, + ) => { + let m = p => Measured.find_p(~msg="Text", p, M.map); let rec of_segment = (buffer_ids, no_sorts, sort, seg: Segment.t): list(Node.t) => { /* note: no_sorts flag is used for backpack view; @@ -92,20 +115,23 @@ module Text = (M: { | Grout(_) => of_grout | Secondary({content, _}) => of_secondary((content, M.settings.secondary_icons, m(p).last.col)) + | Projector(p) => + of_projector(p, expected_sort, m(Projector(p)).origin.col, M.info_map) }; } and of_tile = (buffer_ids, expected_sort: Sort.t, t: Tile.t): list(Node.t) => { let children_and_sorts = List.mapi( (i, (l, child, r)) => - //TODO(andrew): more subtle logic about sort acceptability (child, l + 1 == r ? List.nth(t.mold.in_, i) : Sort.Any), Aba.aba_triples(Aba.mk(t.shards, t.children)), ); let is_consistent = Sort.consistent(t.mold.out, expected_sort); let is_in_buffer = List.mem(t.id, buffer_ids); Aba.mk(t.shards, children_and_sorts) - |> Aba.join(of_delim(is_in_buffer, is_consistent, t), ((seg, sort)) => + |> Aba.join( + of_delim(is_in_buffer, is_consistent, m(Tile(t)).origin.col, t), + ((seg, sort)) => of_segment(buffer_ids, false, sort, seg) ) |> List.concat; @@ -118,30 +144,32 @@ let rec holes = |> List.concat_map( fun | Piece.Secondary(_) => [] + | Projector(_) => [] | Tile(t) => List.concat_map(holes(~map, ~font_metrics), t.children) | Grout(g) => [ EmptyHoleDec.view( ~font_metrics, // TODO(d) fix sort { - measurement: Measured.find_g(g, map), + measurement: Measured.find_g(~msg="Code.holes", g, map), mold: Mold.of_grout(g, Any), }, ), ], ); -let simple_view = - (~font_metrics, ~unselected, ~map, ~settings: Settings.t): Node.t => { +let simple_view = (~font_metrics, ~segment, ~settings: Settings.t): Node.t => { + let map = Measured.of_segment(segment, Id.Map.empty); module Text = Text({ let map = map; let settings = settings; + let info_map = Id.Map.empty; /* Assume this doesn't contain projectors */ }); - let holes = holes(~map, ~font_metrics, unselected); + let holes = holes(~map, ~font_metrics, segment); div( - ~attr=Attr.class_("code"), + ~attrs=[Attr.class_("code")], [ - span_c("code-text", Text.of_segment([], false, Sort.Any, unselected)), + span_c("code-text", Text.of_segment([], false, Sort.Any, segment)), ...holes, ], ); @@ -152,7 +180,7 @@ let of_hole = (~font_metrics, ~measured, g: Grout.t) => EmptyHoleDec.view( ~font_metrics, { - measurement: Measured.find_g(g, measured), + measurement: Measured.find_g(~msg="Code.of_hole", g, measured), mold: Mold.of_grout(g, Any), }, ); @@ -162,15 +190,21 @@ let view = ~sort: Sort.t, ~font_metrics, ~settings: Settings.t, - {state: {meta: {measured, buffer_ids, unselected, holes, _}, _}, _}: Editor.t, + z: Zipper.t, + {syntax: {measured, segment, holes, selection_ids, _}, statics, _}: Editor.Meta.t, ) : Node.t => { module Text = Text({ let map = measured; let settings = settings; + let info_map = statics.info_map; }); - let code = Text.of_segment(buffer_ids, false, sort, unselected); + let buffer_ids = Selection.is_buffer(z.selection) ? selection_ids : []; + let code = Text.of_segment(buffer_ids, false, sort, segment); let holes = List.map(of_hole(~measured, ~font_metrics), holes); - div(~attr=Attr.class_("code"), [span_c("code-text", code), ...holes]); + div( + ~attrs=[Attr.class_("code")], + [span_c("code-text", code), ...holes], + ); }; diff --git a/src/haz3lweb/view/CtxInspector.re b/src/haz3lweb/view/ContextInspector.re similarity index 60% rename from src/haz3lweb/view/CtxInspector.re rename to src/haz3lweb/view/ContextInspector.re index 82ceadc086..672988d049 100644 --- a/src/haz3lweb/view/CtxInspector.re +++ b/src/haz3lweb/view/ContextInspector.re @@ -6,31 +6,30 @@ let jump_to = entry => UpdateAction.PerformAction(Jump(TileId(Haz3lcore.Ctx.get_id(entry)))); let context_entry_view = (~inject, entry: Haz3lcore.Ctx.entry): Node.t => { - let div_name = - div( - ~attr= - Attr.many([ - clss(["name"]), - Attr.on_click(_ => inject(jump_to(entry))), - ]), - ); + let div_name = div(~attrs=[clss(["name"])]); switch (entry) { | VarEntry({name, typ, _}) | ConstructorEntry({name, typ, _}) => - div_c( - "context-entry", + div( + ~attrs=[ + Attr.on_click(_ => inject(jump_to(entry))), + clss(["context-entry", "code"]), + ], [ div_name([text(name)]), - div(~attr=clss(["seperator"]), [text(":")]), + div(~attrs=[clss(["seperator"])], [text(":")]), Type.view(typ), ], ) | TVarEntry({name, kind, _}) => - div_c( - "context-entry", + div( + ~attrs=[ + Attr.on_click(_ => inject(jump_to(entry))), + clss(["context-entry", "code"]), + ], [ div_name([Type.alias_view(name)]), - div(~attr=clss(["seperator"]), [text("::")]), + div(~attrs=[clss(["seperator"])], [text("::")]), Kind.view(kind), ], ) @@ -39,7 +38,7 @@ let context_entry_view = (~inject, entry: Haz3lcore.Ctx.entry): Node.t => { let ctx_view = (~inject, ctx: Haz3lcore.Ctx.t): Node.t => div( - ~attr=clss(["context-entries"]), + ~attrs=[clss(["context-inspector"])], List.map( context_entry_view(~inject), ctx |> Haz3lcore.Ctx.filter_duplicates |> List.rev, @@ -53,10 +52,15 @@ let ctx_sorts_view = (~inject, ci: Haz3lcore.Statics.Info.t) => |> List.map(context_entry_view(~inject)); let view = - (~inject, ~settings: Settings.t, ci: Haz3lcore.Statics.Info.t): Node.t => { + (~inject, ~settings: Settings.t, ci: option(Haz3lcore.Statics.Info.t)) + : Node.t => { let clss = clss( ["context-inspector"] @ (settings.context_inspector ? ["visible"] : []), ); - div(~attr=clss, ctx_sorts_view(~inject, ci)); + switch (ci) { + | Some(ci) when settings.context_inspector => + div(~attrs=[clss], ctx_sorts_view(~inject, ci)) + | _ => div([]) + }; }; diff --git a/src/haz3lweb/view/CursorInspector.re b/src/haz3lweb/view/CursorInspector.re index 71f046786c..90b1180c8e 100644 --- a/src/haz3lweb/view/CursorInspector.re +++ b/src/haz3lweb/view/CursorInspector.re @@ -6,11 +6,11 @@ open Haz3lcore; let errc = "error"; let okc = "ok"; -let div_err = div(~attr=clss([errc])); -let div_ok = div(~attr=clss([okc])); +let div_err = div(~attrs=[clss(["status", errc])]); +let div_ok = div(~attrs=[clss(["status", okc])]); let code_err = (code: string): Node.t => - div(~attr=clss(["code"]), [text(code)]); + div(~attrs=[clss(["code"])], [text(code)]); let explain_this_toggle = (~inject, ~show_explain_this: bool): Node.t => { let tooltip = "Toggle language documentation"; @@ -20,35 +20,35 @@ let explain_this_toggle = (~inject, ~show_explain_this: bool): Node.t => { Virtual_dom.Vdom.Effect.Stop_propagation, ]); div( - ~attr=clss(["explain-this-button"]), + ~attrs=[clss(["explain-this-button"])], [Widgets.toggle(~tooltip, "?", show_explain_this, toggle_explain_this)], ); }; let cls_view = (ci: Info.t): Node.t => div( - ~attr=clss(["syntax-class"]), - [text(ci |> Info.cls_of |> Term.Cls.show)], + ~attrs=[clss(["syntax-class"])], + [text(ci |> Info.cls_of |> Cls.show)], ); let ctx_toggle = (~inject, context_inspector: bool): Node.t => div( - ~attr= - Attr.many([ - Attr.on_click(_ => inject(Update.Set(ContextInspector))), - clss(["gamma"] @ (context_inspector ? ["visible"] : [])), - ]), + ~attrs=[ + Attr.on_click(_ => inject(Update.Set(ContextInspector))), + clss(["gamma"] @ (context_inspector ? ["visible"] : [])), + ], [text("Γ")], ); let term_view = (~inject, ~settings: Settings.t, ci) => { let sort = ci |> Info.sort_of |> Sort.show; div( - ~attr=clss(["ci-header", sort] @ (Info.is_error(ci) ? [errc] : [])), + ~attrs=[ + clss(["ci-header", sort] @ (Info.is_error(ci) ? [errc] : [okc])), + ], [ ctx_toggle(~inject, settings.context_inspector), - CtxInspector.view(~inject, ~settings, ci), - div(~attr=clss(["term-tag"]), [text(sort)]), + div(~attrs=[clss(["term-tag"])], [text(sort)]), explain_this_toggle( ~inject, ~show_explain_this=settings.explainThis.show, @@ -58,7 +58,7 @@ let term_view = (~inject, ~settings: Settings.t, ci) => { ); }; -let elements_noun: Term.Cls.t => string = +let elements_noun: Cls.t => string = fun | Exp(Match | If) => "Branches" | Exp(ListLit) @@ -66,7 +66,7 @@ let elements_noun: Term.Cls.t => string = | Exp(ListConcat) => "Operands" | _ => failwith("elements_noun: Cls doesn't have elements"); -let common_err_view = (cls: Term.Cls.t, err: Info.error_common) => +let common_err_view = (cls: Cls.t, err: Info.error_common) => switch (err) { | NoType(BadToken(token)) => switch (Form.bad_token_cls(token)) { @@ -77,7 +77,7 @@ let common_err_view = (cls: Term.Cls.t, err: Info.error_common) => text("Function argument type"), Type.view(ty), text("inconsistent with"), - Type.view(Prod([])), + Type.view(Prod([]) |> Typ.fresh), ] | NoType(FreeConstructor(name)) => [code_err(name), text("not found")] | Inconsistent(WithArrow(typ)) => [ @@ -97,7 +97,7 @@ let common_err_view = (cls: Term.Cls.t, err: Info.error_common) => ] }; -let common_ok_view = (cls: Term.Cls.t, ok: Info.ok_pat) => { +let common_ok_view = (cls: Cls.t, ok: Info.ok_pat) => { switch (cls, ok) { | (Exp(MultiHole) | Pat(MultiHole), _) => [ text("Expecting operator or delimiter"), @@ -141,12 +141,12 @@ let common_ok_view = (cls: Term.Cls.t, ok: Info.ok_pat) => { }; }; -let typ_ok_view = (cls: Term.Cls.t, ok: Info.ok_typ) => +let typ_ok_view = (cls: Cls.t, ok: Info.ok_typ) => switch (ok) { | Type(_) when cls == Typ(EmptyHole) => [text("Fillable by any type")] | Type(ty) => [Type.view(ty), text("is a type")] | TypeAlias(name, ty_lookup) => [ - Type.view(Var(name)), + Type.view(Var(name) |> Typ.fresh), text("is an alias for"), Type.view(ty_lookup), ] @@ -156,7 +156,7 @@ let typ_ok_view = (cls: Term.Cls.t, ok: Info.ok_typ) => Type.view(Module({inner_ctx, incomplete: false})), ] | Variant(name, sum_ty) => [ - Type.view(Var(name)), + Type.view(Var(name) |> Typ.fresh), text("is a sum type constuctor of type"), Type.view(sum_ty), ] @@ -168,7 +168,10 @@ let typ_ok_view = (cls: Term.Cls.t, ok: Info.ok_typ) => let typ_err_view = (ok: Info.error_typ) => switch (ok) { - | FreeTypeVariable(name) => [Type.view(Var(name)), text("not found")] + | FreeTypeVariable(name) => [ + Type.view(Var(name) |> Typ.fresh), + text("not found"), + ] | BadToken(token) => [ code_err(token), text("not a type or type operator"), @@ -178,7 +181,7 @@ let typ_err_view = (ok: Info.error_typ) => | WantTypeFoundAp => [text("Must be part of a sum type")] | WantModule => [text("Expect a valid module")] | DuplicateConstructor(name) => [ - Type.view(Var(name)), + Type.view(Var(name) |> Typ.fresh), text("already used in this sum"), ] | FreeTypeMember(name) => [ @@ -194,12 +197,12 @@ let typ_err_view = (ok: Info.error_typ) => ] }; -let rec exp_view = (cls: Term.Cls.t, status: Info.status_exp) => +let rec exp_view = (cls: Cls.t, status: Info.status_exp) => switch (status) { | InHole(FreeVariable(name)) => div_err([code_err(name), text("not found")]) | InHole(InexhaustiveMatch(additional_err)) => - let cls_str = Term.Cls.show(cls); + let cls_str = Cls.show(cls); switch (additional_err) { | None => div_err([text(cls_str ++ " is inexhaustive")]) | Some(err) => @@ -231,7 +234,7 @@ let rec exp_view = (cls: Term.Cls.t, status: Info.status_exp) => | NotInHole(Common(ok)) => div_ok(common_ok_view(cls, ok)) }; -let rec pat_view = (cls: Term.Cls.t, status: Info.status_pat) => +let rec pat_view = (cls: Cls.t, status: Info.status_pat) => switch (status) { | InHole(ExpectedModule(token)) => div_err([ @@ -253,13 +256,13 @@ let rec pat_view = (cls: Term.Cls.t, status: Info.status_pat) => | NotInHole(ok) => div_ok(common_ok_view(cls, ok)) }; -let typ_view = (cls: Term.Cls.t, status: Info.status_typ) => +let typ_view = (cls: Cls.t, status: Info.status_typ) => switch (status) { | NotInHole(ok) => div_ok(typ_ok_view(cls, ok)) | InHole(err) => div_err(typ_err_view(err)) }; -let tpat_view = (_: Term.Cls.t, status: Info.status_tpat) => +let tpat_view = (_: Cls.t, status: Info.status_tpat) => switch (status) { | NotInHole(Empty) => div_ok([text("Fillable with a new alias")]) | NotInHole(Var(name)) => div_ok([Type.alias_view(name)]) @@ -267,25 +270,29 @@ let tpat_view = (_: Term.Cls.t, status: Info.status_tpat) => div_err([text("Must begin with a capital letter")]) | InHole(NotAVar(_)) => div_err([text("Expected an alias")]) | InHole(ShadowsType(name, BaseTyp)) => - div_err([text("Can't shadow base type"), Type.view(Var(name))]) + div_err([ + text("Can't shadow base type"), + Type.view(Var(name) |> Typ.fresh), + ]) | InHole(ShadowsType(name, TyAlias)) => - div_err([text("Can't shadow existing alias"), Type.view(Var(name))]) + div_err([ + text("Can't shadow existing alias"), + Type.view(Var(name) |> Typ.fresh), + ]) | InHole(ShadowsType(name, TyVar)) => div_err([ text("Can't shadow existing type variable"), - Type.view(Var(name)), + Type.view(Var(name) |> Typ.fresh), ]) }; -let secondary_view = (cls: Term.Cls.t) => - div_ok([text(cls |> Term.Cls.show)]); +let secondary_view = (cls: Cls.t) => div_ok([text(cls |> Cls.show)]); -let view_of_info = (~inject, ~settings, ci): Node.t => { - let wrapper = status_view => - div( - ~attr=clss(["info"]), - [term_view(~inject, ~settings, ci), status_view], - ); +let view_of_info = (~inject, ~settings, ci): list(Node.t) => { + let wrapper = status_view => [ + term_view(~inject, ~settings, ci), + status_view, + ]; switch (ci) { | Secondary(_) => wrapper(div([])) | InfoExp({cls, status, _}) => wrapper(exp_view(cls, status)) @@ -297,17 +304,21 @@ let view_of_info = (~inject, ~settings, ci): Node.t => { let inspector_view = (~inject, ~settings, ci): Node.t => div( - ~attr=clss(["cursor-inspector"] @ [Info.is_error(ci) ? errc : okc]), - [view_of_info(~inject, ~settings, ci)], + ~attrs=[ + Attr.id("cursor-inspector"), + clss([Info.is_error(ci) ? errc : okc]), + ], + view_of_info(~inject, ~settings, ci), ); -let view = (~inject, ~settings: Settings.t, cursor_info: option(Info.t)) => { - let bar_view = div(~attr=Attr.id("bottom-bar")); +let view = + (~inject, ~settings: Settings.t, editor, cursor_info: option(Info.t)) => { + let bar_view = div(~attrs=[Attr.id("bottom-bar")]); let err_view = err => bar_view([ div( - ~attr=clss(["cursor-inspector", "no-info"]), - [div(~attr=clss(["icon"]), [Icons.magnify]), text(err)], + ~attrs=[Attr.id("cursor-inspector"), clss(["no-info"])], + [div(~attrs=[clss(["icon"])], [Icons.magnify]), text(err)], ), ]); switch (cursor_info) { @@ -316,9 +327,10 @@ let view = (~inject, ~settings: Settings.t, cursor_info: option(Info.t)) => { | Some(ci) => bar_view([ inspector_view(~inject, ~settings, ci), - div( - ~attr=clss(["id"]), - [text(String.sub(Id.to_string(Info.id_of(ci)), 0, 4))], + ProjectorView.Panel.view( + ~inject=a => inject(PerformAction(Project(a))), + editor, + ci, ), ]) }; diff --git a/src/haz3lweb/view/DebugMode.re b/src/haz3lweb/view/DebugMode.re index 67618ee6ee..39cba26eb8 100644 --- a/src/haz3lweb/view/DebugMode.re +++ b/src/haz3lweb/view/DebugMode.re @@ -1,4 +1,5 @@ open Virtual_dom.Vdom; +open Util; [@deriving (show({with_path: false}), sexp, yojson)] type action = @@ -27,13 +28,12 @@ let perform = (action: action): unit => { let btn = (caption, action) => { Node.( button( - ~attr= - Attr.many([ - Attr.on_click(_ => { - perform(action); - Ui_effect.Ignore; - }), - ]), + ~attrs=[ + Attr.on_click(_ => { + perform(action); + Ui_effect.Ignore; + }), + ], [text(caption)], ) ); @@ -48,35 +48,8 @@ let view = { ); }; -module App = { - module Model = { - type t = unit; - let cutoff = (_, _) => false; - }; - module Action = { - type t = unit; - let sexp_of_t = _ => Sexplib.Sexp.unit; - }; - module State = { - type t = unit; - }; - let on_startup = (~schedule_action as _, _) => - Async_kernel.Deferred.return(); - let create = (_, ~old_model as _, ~inject as _) => - Incr_dom.Incr.return() - |> Incr_dom.Incr.map(~f=_ => - Incr_dom.Component.create( - ~apply_action=(_, _, ~schedule_action as _) => (), - (), - view, - ) - ); -}; - let go = () => - Incr_dom.Start_app.start( - (module App), - ~debug=false, + Bonsai_web.Start.start( + Bonsai.Computation.return(view), ~bind_to_element_with_id="container", - ~initial_model=(), ); diff --git a/src/haz3lweb/view/Deco.re b/src/haz3lweb/view/Deco.re index 0f577762e5..a616fe9eb0 100644 --- a/src/haz3lweb/view/Deco.re +++ b/src/haz3lweb/view/Deco.re @@ -1,114 +1,266 @@ open Virtual_dom.Vdom; open Util; +open Util.Web; open Haz3lcore; -module Deco = +type shard_data = (Measured.measurement, Nibs.shapes); + +let sel_shard_svg = + ( + ~index=?, + ~start_shape: PieceDec.tip, + measurement: Measured.measurement, + p: Piece.t, + ) + : (Measured.measurement, (PieceDec.tip, PieceDec.tip)) => ( + measurement, + switch (p) { + | Tile(t) => Mold.nib_shapes(~index?, t.mold) |> PieceDec.tips_of_shapes + | Grout(g) => + Mold.nib_shapes(Mold.of_grout(g, Any)) |> PieceDec.tips_of_shapes + | Secondary(_) => ( + Option.map( + (s: Nib.Shape.t) => + switch (s) { + | Concave(_) => Nib.Shape.Convex + | Convex => Nib.Shape.Concave(0) + }, + start_shape, + ), + None, + ) + | Projector(p) => + ProjectorBase.mold_of(p, Any) + |> Mold.nib_shapes + |> PieceDec.tips_of_shapes + }, +); + +let multiline_shard = + ( + num_lb: int, + {origin, last}: Measured.measurement, + tips: (option(Nib.Shape.t), option(Nib.Shape.t)), + ) => + List.init(num_lb + 1, i => + [ + Some(( + Measured.{ + origin: { + row: origin.row + i, + col: origin.col, + }, + last: { + row: origin.row + i, + col: last.col, + }, + }, + (i == 0 ? fst(tips) : None, i == num_lb ? snd(tips) : None), + )), + None, + ] + ) + |> List.concat; +module HighlightSegment = ( M: { + let measured: Measured.t; + let info_map: Statics.Map.t; let font_metrics: FontMetrics.t; - let map: Measured.t; - let show_backpack_targets: bool; - let terms: TermMap.t; - let term_ranges: TermRanges.t; - let error_ids: list(Id.t); - let tiles: TileMap.t; }, ) => { - let font_metrics = M.font_metrics; - - let tile = id => Id.Map.find(id, M.tiles); - - let caret = (z: Zipper.t): list(Node.t) => { - let origin = Zipper.caret_point(M.map, z); - let shape = Zipper.caret_direction(z); - let side = - switch (Indicated.piece(z)) { - | Some((_, side, _)) => side - | _ => Right - }; - [CaretDec.view(~font_metrics, ~profile={side, origin, shape})]; - }; - - type shard_data = (Measured.measurement, Nibs.shapes); - - let sel_shard_svg = - (~index=?, ~start_shape, measurement: Measured.measurement, p) - : (Measured.measurement, Nibs.shapes) => ( - measurement, - Mold.nib_shapes(~index?, Piece.mold_of(~shape=start_shape, p)), - ); - - let rec sel_of_piece = - (start_shape: Nib.Shape.t, p: Piece.t) - : (Nib.Shape.t, list(option(shard_data))) => { + let find_g = Measured.find_g(~msg="Highlight.of_piece", _, M.measured); + let find_w = Measured.find_w(~msg="Highlight.of_piece", _, M.measured); + let rec of_piece = + (start_shape: PieceDec.tip, p: Piece.t) + : ( + PieceDec.tip, + list( + option( + (Measured.measurement, (PieceDec.tip, PieceDec.tip)), + ), + ), + ) => { let shard_data = switch (p) { - | Tile(t) => sel_of_tile(~start_shape, t) - | Grout(g) => [ - Some(sel_shard_svg(~start_shape, Measured.find_g(g, M.map), p)), - ] + | Tile(t) => of_tile(~start_shape, t) + | Projector(p) => of_projector(~start_shape, p) + | Grout(g) => [Some(sel_shard_svg(~start_shape, find_g(g), p))] | Secondary(w) when Secondary.is_linebreak(w) => [None] | Secondary(w) => [ - Some(sel_shard_svg(~start_shape, Measured.find_w(w, M.map), p)), + Some(( + find_w(w), + (start_shape |> Option.map(Nib.Shape.flip), start_shape), + )), ] }; let start_shape = switch (Piece.nibs(p)) { | None => start_shape - | Some((_, {shape, _})) => shape + | Some((_, {shape, _})) => Some(shape) }; (start_shape, shard_data); } - and sel_of_tile = (~start_shape, t: Tile.t): list(option(shard_data)) => { + and of_tile = (~start_shape, t: Tile.t): list(option(_)) => { let tile_shards = - Measured.find_shards(t, M.map) + Measured.find_shards(~msg="sel_of_tile", t, M.measured) |> List.filter(((i, _)) => List.mem(i, t.shards)) - |> List.map(((index, measurement)) => - [ - Some(sel_shard_svg(~start_shape, ~index, measurement, Tile(t))), - ] - ); - let shape_at = index => snd(Mold.nibs(~index, t.mold)).shape; + |> List.map(((index, m)) => { + let token = List.nth(t.label, index); + switch (StringUtil.num_linebreaks(token)) { + | 0 => [Some(sel_shard_svg(~start_shape, ~index, m, Tile(t)))] + | num_lb => + multiline_shard(num_lb, m, (Some(Convex), Some(Convex))) + }; + }); + let shape_at = index => Some(snd(Mold.nibs(~index, t.mold)).shape); let children_shards = - t.children |> List.mapi(index => sel_of_segment(shape_at(index))); + t.children |> List.mapi(index => of_segment(shape_at(index))); ListUtil.interleave(tile_shards, children_shards) |> List.flatten; } - and sel_of_segment = - (start_shape: Nib.Shape.t, seg: Segment.t): list(option(shard_data)) => { + and of_projector = (~start_shape, p: Base.projector): list(option(_)) => + switch (Measured.find_pr_opt(p, M.measured)) { + | None => failwith("Deco.of_projector: missing measurement") + | Some(_m) => + let ci = Id.Map.find_opt(p.id, M.info_map); + let token = Projector.placeholder(p, ci); + /* Handling this internal to ProjectorsView at the moment because the + * commented-out strategy doesn't work well, since the inserted str8- + * edged lines vertical edge placement doesn't account for whether + * the initial/final rows begin/end as concave/convex, and hence are + * of slightly different lengths than is desirable */ + // multiline_shard( + // StringUtil.num_linebreaks(token), + // m, + // (Some(Convex), Some(Convex)), + // ); + let num_lb = StringUtil.num_linebreaks(token); + if (num_lb == 0) { + [ + Some( + sel_shard_svg( + ~start_shape, + Measured.find_pr(p, M.measured), + Projector(p), + ), + ), + ]; + } else { + List.init(num_lb + 1, _ => None); + }; + } + and of_segment = + (start_shape: PieceDec.tip, seg: Segment.t): list(option(_)) => { seg - |> ListUtil.fold_left_map(sel_of_piece, start_shape) + |> ListUtil.fold_left_map(of_piece, start_shape) |> snd |> List.flatten; } - and selected_pieces = (z: Zipper.t): list(Node.t) => + and go = + (segment: Segment.t, shape_init: PieceDec.tip, classes): list(Node.t) => /* We draw a single deco per row by dividing partionining the shards * into linebreak-seperated segments, then combining the measurements * and shapes of the first and last shard of each segment. Ideally we * could just get this info from the row measurements, but we have no * current way of figuring out shapes for whitespace without traversing */ - sel_of_segment( - fst(Siblings.shapes(z.relatives.siblings)), - z.selection.content, - ) + of_segment(shape_init, segment) |> ListUtil.split_at_nones |> ListUtil.first_and_last - |> List.map((((m1, (l1, _)): shard_data, (m2, (_, r2)): shard_data)) => - (({origin: m1.origin, last: m2.last}, (l1, r2)): shard_data) + |> List.map((((m1, (l1, _)), (m2, (_, r2)))) => + (Measured.{origin: m1.origin, last: m2.last}, (l1, r2)) ) - |> List.map(((measurement, shapes)) => - PieceDec.simple_shard_selected( - ~buffer=Selection.is_buffer(z.selection), - ~font_metrics, - ~measurement, - ~shapes, + |> List.map(((measurement, tips)) => + PieceDec.simple_shard( + {font_metrics: M.font_metrics, measurement, tips}, + classes, ) ); +}; + +module Deco = + ( + M: { + let ui_state: Model.ui_state; + let meta: Editor.Meta.t; + let highlights: option(ColorSteps.colorMap); + }, + ) => { + module Highlight = + HighlightSegment({ + let measured = M.meta.syntax.measured; + let info_map = M.meta.statics.info_map; + let font_metrics = M.ui_state.font_metrics; + }); + let font_metrics = M.ui_state.font_metrics; + + let tile = id => Id.Map.find(id, M.meta.syntax.tiles); + + let caret = (z: Zipper.t): Node.t => { + let origin = Zipper.caret_point(M.meta.syntax.measured, z); + let shape = Zipper.caret_direction(z); + let side = + switch (Indicated.piece(z)) { + | _ + when + !Selection.is_empty(z.selection) + && !Selection.is_buffer(z.selection) => + z.selection.focus + | Some((_, side, _)) => Direction.toggle(side) + | _ => Right + }; + CaretDec.view(~font_metrics, ~profile={side, origin, shape}); + }; + + let segment_selected = (z: Zipper.t) => + Highlight.go( + z.selection.content, + Some(fst(Siblings.shapes(z.relatives.siblings))), + ["selected"] @ (Selection.is_buffer(z.selection) ? ["buffer"] : []), + ); + + let term_range = (p): option((Point.t, Point.t)) => { + let id = Any.rep_id(Id.Map.find(Piece.id(p), M.meta.syntax.terms)); + switch (TermRanges.find_opt(id, M.meta.syntax.term_ranges)) { + | None => None + | Some((p_l, p_r)) => + let l = + Measured.find_p(~msg="Dec.range", p_l, M.meta.syntax.measured).origin; + let r = + Measured.find_p(~msg="Dec.range", p_r, M.meta.syntax.measured).last; + Some((l, r)); + }; + }; + + let all_tiles = (p: Piece.t): list((Uuidm.t, Mold.t, Measured.Shards.t)) => + Id.Map.find(Piece.id(p), M.meta.syntax.terms) + |> Any.ids + |> List.map(id => { + let t = tile(id); + let shards = + Measured.find_shards(~msg="all_tiles", t, M.meta.syntax.measured); + (id, t.mold, shards); + }); let indicated_piece_deco = (z: Zipper.t): list(Node.t) => { switch (Indicated.piece(z)) { | _ when z.selection.content != [] => [] | None => [] | Some((Grout(_), _, _)) => [] + | Some((Projector(p), _, _)) => + switch (Measured.find_pr_opt(p, M.meta.syntax.measured)) { + | Some(measurement) => [ + PieceDec.simple_shard_indicated( + { + font_metrics, + measurement, + tips: p |> ProjectorBase.shapes |> PieceDec.tips_of_shapes, + }, + ~sort=ProjectorBase.mold_of(p, Exp).out, + ~at_caret=true, + ), + ] + | None => [] + } | Some((p, side, _)) => // root_profile calculation assumes p is tile // TODO encode in types @@ -117,17 +269,7 @@ module Deco = | None => Nib.Shape.Convex | Some(nib) => Nib.Shape.relative(nib, side) }; - let range: option((Measured.Point.t, Measured.Point.t)) = { - // if (Piece.has_ends(p)) { - let id = Id.Map.find(Piece.id(p), M.terms) |> Term.rep_id; - switch (TermRanges.find_opt(id, M.term_ranges)) { - | None => None - | Some((p_l, p_r)) => - let l = Measured.find_p(p_l, M.map).origin; - let r = Measured.find_p(p_r, M.map).last; - Some((l, r)); - }; - }; + let range = term_range(p); let index = switch (Indicated.shard_index(z)) { | None => (-1) @@ -136,20 +278,10 @@ module Deco = switch (range) { | None => [] | Some(range) => - let tiles = - Id.Map.find(Piece.id(p), M.terms) - |> Term.ids - /* NOTE(andrew): dark_ids were originally filtered here. - * Leaving this comment in place in case issues in the - * future are traced back to here. - * |> List.filter(id => id >= 0)*/ - |> List.map(id => { - let t = tile(id); - (id, t.mold, Measured.find_shards(t, M.map)); - }); + let tiles = all_tiles(p); PieceDec.indicated( ~font_metrics, - ~rows=M.map.rows, + ~rows=M.meta.syntax.measured.rows, ~caret=(Piece.id(p), index), ~tiles, range, @@ -178,14 +310,23 @@ module Deco = switch (Siblings.neighbors((l, r))) { | (None, None) => failwith("impossible") | (_, Some(p)) => - let m = Measured.find_p(p, M.map); + let m = + Measured.find_p( + ~msg="Deco.targets", + p, + M.meta.syntax.measured, + ); Measured.{origin: m.origin, last: m.origin}; | (Some(p), _) => - let m = Measured.find_p(p, M.map); + let m = + Measured.find_p( + ~msg="Deco.targets", + p, + M.meta.syntax.measured, + ); Measured.{origin: m.last, last: m.last}; }; - let profile = - CaretPosDec.Profile.{style: `Sibling, measurement, sort: Exp}; + let profile = CaretPosDec.Profile.{style: `Sibling, measurement}; [CaretPosDec.view(~font_metrics, profile)]; }; }); @@ -208,39 +349,38 @@ module Deco = }; }; - let backpack = (z: Zipper.t): list(Node.t) => [ + let backpack = (z: Zipper.t): Node.t => BackpackView.view( ~font_metrics, - ~origin=Zipper.caret_point(M.map, z), + ~origin=Zipper.caret_point(M.meta.syntax.measured, z), z, - ), - ]; + ); - let targets' = (backpack, seg) => { - M.show_backpack_targets && Backpack.restricted(backpack) - ? targets(backpack, seg) : []; - }; + let backpack_targets = (backpack, seg) => + div_c( + "backpack-targets", + M.ui_state.show_backpack_targets && Backpack.restricted(backpack) + ? targets(backpack, seg) : [], + ); let term_decoration = - ( - ~id: Id.t, - deco: - ((Measured.Point.t, Measured.Point.t, SvgUtil.Path.t)) => Node.t, - ) => { - let (p_l, p_r) = TermRanges.find(id, M.term_ranges); - let l = Measured.find_p(p_l, M.map).origin; - let r = Measured.find_p(p_r, M.map).last; + (~id: Id.t, deco: ((Point.t, Point.t, SvgUtil.Path.t)) => Node.t) => { + let (p_l, p_r) = TermRanges.find(id, M.meta.syntax.term_ranges); + let l = + Measured.find_p(~msg="Deco.term", p_l, M.meta.syntax.measured).origin; + let r = + Measured.find_p(~msg="Deco.term", p_r, M.meta.syntax.measured).last; open SvgUtil.Path; let r_edge = ListUtil.range(~lo=l.row, r.row + 1) |> List.concat_map(i => { - let row = Measured.Rows.find(i, M.map.rows); + let row = Measured.Rows.find(i, M.meta.syntax.measured.rows); [h(~x=i == r.row ? r.col : row.max_col), v_(~dy=1)]; }); let l_edge = ListUtil.range(~lo=l.row, r.row + 1) |> List.rev_map(i => { - let row = Measured.Rows.find(i, M.map.rows); + let row = Measured.Rows.find(i, M.meta.syntax.measured.rows); [h(~x=i == l.row ? l.col : row.indent), v_(~dy=-1)]; }) |> List.concat; @@ -252,42 +392,103 @@ module Deco = (l, r, path) |> deco; }; - let term_highlight = (~clss: list(string), id: Id.t) => { - term_decoration(~id, ((origin, last, path)) => - DecUtil.code_svg_sized( - ~font_metrics, - ~measurement={origin, last}, - ~base_cls=clss, - path, + let term_highlight = (~clss: list(string), id: Id.t) => + try( + term_decoration(~id, ((origin, last, path)) => + DecUtil.code_svg_sized( + ~font_metrics, + ~measurement={origin, last}, + ~base_cls=clss, + path, + ) ) - ); - }; + ) { + | Not_found => + /* This is caused by the statics overloading for exercise mode. The overriding + * Exercise mode statics maps are calculated based on splicing together multiple + * editors, but error_ids are extracted generically from the statics map, so + * there may be error holes that don't occur in the editor being rendered. + * Additionally, when showing color highlights when the backpack is non-empty, + * the prospective completion may have different ids than the displayed code. */ + Node.div([]) + }; - let color_highlights = (colorings: list((Id.t, string))) => { - List.filter_map( - ((id, color)) => - /* HACK(andrew): Catching exceptions since when showing - term highlights when the backpack is non-empty, the - prospective completion may have different term ids - than the displayed code. */ - try(Some(term_highlight(~clss=["highlight-code-" ++ color], id))) { - | Not_found => None + let color_highlights = () => + div_c( + "color-highlights", + List.map( + ((id, color)) => + term_highlight(~clss=["highlight-code-" ++ color], id), + switch (M.highlights) { + | Some(colorMap) => ColorSteps.to_list(colorMap) + | _ => [] }, - colorings, + ), ); - }; - // faster infomap traversal - let err_holes = (_z: Zipper.t) => - List.map(term_highlight(~clss=["err-hole"]), M.error_ids); + let error_view = (id: Id.t) => + try( + switch (Id.Map.find_opt(id, M.meta.syntax.projectors)) { + | Some(p) => + /* Special case for projectors as they are not in tile map */ + let shapes = ProjectorBase.shapes(p); + let measurement = Id.Map.find(id, M.meta.syntax.measured.projectors); + div_c( + "errors-piece", + [ + PieceDec.simple_shard_error({ + font_metrics, + tips: PieceDec.tips_of_shapes(shapes), + measurement, + }), + ], + ); + | None => + let p = Piece.Tile(tile(id)); + let tiles = all_tiles(p); + let shard_decos = + tiles + |> List.map(((_, mold, shards)) => + PieceDec.simple_shards_errors(~font_metrics, mold, shards) + ) + |> List.flatten; + switch (term_range(p)) { + | Some(range) => + let rows = M.meta.syntax.measured.rows; + let decos = + shard_decos + @ PieceDec.uni_lines(~font_metrics, ~rows, range, tiles) + @ PieceDec.bi_lines(~font_metrics, ~rows, tiles); + div_c("errors-piece", decos); + | None => div_c("errors-piece", shard_decos) + }; + } + ) { + | Not_found => + /* This is caused by the statics overloading for exercise mode. The overriding + * Exercise mode statics maps are calculated based on splicing together multiple + * editors, but error_ids are extracted generically from the statics map, so + * there may be error holes that don't occur in the editor being rendered */ + Node.div([]) + }; + + let errors = () => + div_c("errors", List.map(error_view, M.meta.statics.error_ids)); - let all = (zipper, sel_seg) => - List.concat([ - caret(zipper), - indicated_piece_deco(zipper), - selected_pieces(zipper), - backpack(zipper), - targets'(zipper.backpack, sel_seg), - err_holes(zipper), - ]); + let indication = (z: Zipper.t) => + div_c("indication", indicated_piece_deco(z)); + + let selection = (z: Zipper.t) => div_c("selects", segment_selected(z)); + + let always = () => [errors()]; + + let all = z => [ + caret(z), + indication(z), + selection(z), + backpack(z), + backpack_targets(z.backpack, M.meta.syntax.segment), + errors(), + color_highlights(), + ]; }; diff --git a/src/haz3lweb/view/EditorModeView.re b/src/haz3lweb/view/EditorModeView.re index bd1c9afddf..dea884266f 100644 --- a/src/haz3lweb/view/EditorModeView.re +++ b/src/haz3lweb/view/EditorModeView.re @@ -4,19 +4,20 @@ open Widgets; let option_view = (name, n) => option( - ~attr=n == name ? Attr.create("selected", "selected") : Attr.many([]), + ~attrs=n == name ? [Attr.create("selected", "selected")] : [], [text(n)], ); let mode_menu = (~inject: Update.t => 'a, ~mode: Settings.mode) => div( - ~attr=Attr.many([Attr.class_("mode-name"), Attr.title("Toggle Mode")]), + ~attrs=[Attr.class_("mode-name"), Attr.title("Toggle Mode")], [ select( - ~attr= + ~attrs=[ Attr.on_change((_, name) => inject(Set(Mode(Settings.mode_of_string(name)))) ), + ], List.map( option_view(Settings.show_mode(mode)), ["Scratch", "Documentation", "Exercises"], @@ -36,7 +37,7 @@ let slide_select = (~inject, ~cur_slide, ~num_slides) => { }; let scratch_view = (~inject, ~cur_slide, ~slides) => - [mode_menu(~inject, ~mode=Scratch)] + [text("/"), mode_menu(~inject, ~mode=Scratch), text("/")] @ slide_select(~inject, ~cur_slide, ~num_slides=List.length(slides)); let documentation_view = (~inject, ~name, ~editors) => { @@ -52,7 +53,7 @@ let documentation_view = (~inject, ~name, ~editors) => { | [x, y, z, ..._] when name == y => (Some(x), Some(z)) | [_, ...ys] => find_prev_next(ys); let (prev, next) = find_prev_next(editor_names); - let prev = + let _prev = prev |> Option.map(s => button(Icons.back, _ => inject(Update.SwitchDocumentationSlide(s))) @@ -65,7 +66,7 @@ let documentation_view = (~inject, ~name, ~editors) => { ~disabled=true, ), ); - let next = + let _next = next |> Option.map(s => button(Icons.forward, _ => @@ -81,16 +82,17 @@ let documentation_view = (~inject, ~name, ~editors) => { ), ); [ + text("/"), mode_menu(~inject, ~mode=Documentation), - prev, + text("/"), select( - ~attr= + ~attrs=[ Attr.on_change((_, name) => inject(Update.SwitchDocumentationSlide(name)) ), + ], List.map(option_view(name), editor_names), ), - next, ]; }; @@ -104,8 +106,9 @@ let instructor_toggle = (~inject, ~instructor_mode) => : []; let exercises_view = (~inject, ~cur_slide, ~specs, ~instructor_mode) => { - [mode_menu(~inject, ~mode=Exercises)] + [text("/"), mode_menu(~inject, ~mode=Exercises), text("/")] @ instructor_toggle(~inject, ~instructor_mode) + @ [text("/")] @ slide_select(~inject, ~cur_slide, ~num_slides=List.length(specs)); }; @@ -125,5 +128,5 @@ let view = | Exercises(cur_slide, specs, _) => exercises_view(~cur_slide, ~specs, ~inject, ~instructor_mode) }; - div(~attr=Attr.id("editor-mode"), contents); + div(~attrs=[Attr.id("editor-mode")], contents); }; diff --git a/src/haz3lweb/view/ExerciseMode.re b/src/haz3lweb/view/ExerciseMode.re index 52302e7493..2b291c99f4 100644 --- a/src/haz3lweb/view/ExerciseMode.re +++ b/src/haz3lweb/view/ExerciseMode.re @@ -1,3 +1,4 @@ +open Util; open Haz3lcore; open Virtual_dom.Vdom; open Node; @@ -23,16 +24,10 @@ let view = ~ui_state: Model.ui_state, ~settings: Settings.t, ~exercise, - ~results, + ~stitched_dynamics, ~highlights, ) => { let Exercise.{eds, pos} = exercise; - let stitched_dynamics = - Exercise.stitch_dynamic( - settings.core, - exercise, - settings.core.dynamics ? Some(results) : None, - ); let { test_validation, user_impl, @@ -43,11 +38,8 @@ let view = hidden_tests: _, }: Exercise.stitched(Exercise.DynamicsItem.t) = stitched_dynamics; - let grading_report = Grading.GradingReport.mk(eds, ~stitched_dynamics); - let score_view = Grading.GradingReport.view_overall_score(grading_report); - let editor_view = ( ~editor: Editor.t, @@ -59,8 +51,7 @@ let view = ) => { Cell.editor_view( ~selected=pos == this_pos, - ~error_ids= - Statics.Map.error_ids(editor.state.meta.term_ranges, di.info_map), + ~override_statics=di.statics, ~inject, ~ui_state, ~mousedown_updates=[SwitchEditor(this_pos)], @@ -73,14 +64,12 @@ let view = editor, ); }; - let title_view = Cell.title_cell(eds.title); let prompt_view = Cell.narrative_cell( - div(~attr=Attr.class_("cell-prompt"), [eds.prompt]), + div(~attrs=[Attr.class_("cell-prompt")], [eds.prompt]), ); - let prelude_view = Always( editor_view( @@ -102,7 +91,6 @@ let view = ~di=instructor, ), ); - // determine trailing hole // TODO: module let correct_impl_ctx_view = @@ -112,10 +100,13 @@ let view = let correct_impl_trailing_hole_ctx = Haz3lcore.Editor.trailing_hole_ctx( eds.correct_impl, - instructor.info_map, + instructor.statics.info_map, ); let prelude_trailing_hole_ctx = - Haz3lcore.Editor.trailing_hole_ctx(eds.prelude, prelude.info_map); + Haz3lcore.Editor.trailing_hole_ctx( + eds.prelude, + prelude.statics.info_map, + ); switch (correct_impl_trailing_hole_ctx, prelude_trailing_hole_ctx) { | (None, _) => Node.div([text("No context available (1)")]) | (_, None) => Node.div([text("No context available (2)")]) // TODO show exercise configuration error @@ -131,7 +122,7 @@ let view = switch (specific_ctx) { | None => Node.div([text("No context available")]) // TODO show exercise configuration error | Some(specific_ctx) => - CtxInspector.ctx_view(~inject, specific_ctx) + ContextInspector.ctx_view(~inject, specific_ctx) }; }; }; @@ -146,7 +137,6 @@ let view = ]); }, ); - let your_tests_view = Always( editor_view( @@ -164,7 +154,6 @@ let view = ], ), ); - let wrong_impl_views = List.mapi( (i, (Exercise.{impl, _}, di)) => { @@ -180,7 +169,6 @@ let view = }, List.combine(eds.hidden_bugs, hidden_bugs), ); - let mutation_testing_view = Always( Grading.MutationTestingReport.view( @@ -189,7 +177,6 @@ let view = grading_report.point_distribution.mutation_testing, ), ); - let your_impl_view = { Always( editor_view( @@ -209,7 +196,6 @@ let view = ), ); }; - let syntax_grading_view = Always(Grading.SyntaxReport.view(grading_report.syntax_report)); @@ -219,7 +205,7 @@ let view = YourTestsTesting, ~caption="Implementation Validation", ~subcaption= - ": Your Tests (code synchronized with Test Validation cell above) vs. Your Implementation", + ": Your Tests (synchronized with Test Validation above) vs. Your Implementation", ~editor=eds.your_tests.tests, ~di=user_tests, ~footer=[ @@ -251,7 +237,6 @@ let view = ~max_points=grading_report.point_distribution.impl_grading, ), ); - [score_view, title_view, prompt_view] @ render_cells( settings, @@ -290,72 +275,39 @@ let reset_button = inject => ~tooltip="Reset Exercise", ); -let instructor_export = (exercise: Exercise.state) => +let instructor_export = (inject: UpdateAction.t => Ui_effect.t(unit)) => Widgets.button_named( - Icons.star, - _ => { - // .ml files because show uses OCaml syntax (dune handles seamlessly) - let module_name = exercise.eds.module_name; - let filename = exercise.eds.module_name ++ ".ml"; - let content_type = "text/plain"; - let contents = Exercise.export_module(module_name, exercise); - JsUtil.download_string_file(~filename, ~content_type, ~contents); - Virtual_dom.Vdom.Effect.Ignore; - }, + Icons.export, + _ => inject(Export(ExerciseModule)), ~tooltip="Export Exercise Module", ); -let instructor_transitionary_export = (exercise: Exercise.state) => +let instructor_transitionary_export = + (inject: UpdateAction.t => Ui_effect.t(unit)) => Widgets.button_named( - Icons.star, - _ => { - // .ml files because show uses OCaml syntax (dune handles seamlessly) - let module_name = exercise.eds.module_name; - let filename = exercise.eds.module_name ++ ".ml"; - let content_type = "text/plain"; - let contents = - Exercise.export_transitionary_module(module_name, exercise); - JsUtil.download_string_file(~filename, ~content_type, ~contents); - Virtual_dom.Vdom.Effect.Ignore; - }, + Icons.export, + _ => {inject(Export(TransitionaryExerciseModule))}, ~tooltip="Export Transitionary Exercise Module", ); -let instructor_grading_export = (exercise: Exercise.state) => +let instructor_grading_export = (inject: UpdateAction.t => Ui_effect.t(unit)) => Widgets.button_named( - Icons.star, - _ => { - // .ml files because show uses OCaml syntax (dune handles seamlessly) - let module_name = exercise.eds.module_name; - let filename = exercise.eds.module_name ++ "_grading.ml"; - let content_type = "text/plain"; - let contents = Exercise.export_grading_module(module_name, exercise); - JsUtil.download_string_file(~filename, ~content_type, ~contents); - Virtual_dom.Vdom.Effect.Ignore; - }, + Icons.export, + _ => {inject(Export(GradingExerciseModule))}, ~tooltip="Export Grading Exercise Module", ); -let download_editor_state = (~instructor_mode) => - Log.get_and(log => { - let data = Export.export_all(~instructor_mode, ~log); - JsUtil.download_json(ExerciseSettings.filename, data); - }); - -let export_submission = (~settings: Settings.t) => +let export_submission = (inject: UpdateAction.t => Ui_effect.t(unit)) => Widgets.button_named( Icons.star, - _ => { - download_editor_state(~instructor_mode=settings.instructor_mode); - Virtual_dom.Vdom.Effect.Ignore; - }, + _ => inject(Export(Submission)), ~tooltip="Export Submission", ); let import_submission = (~inject) => Widgets.file_select_button_named( "import-submission", - Icons.star, + Icons.import, file => { switch (file) { | None => Virtual_dom.Vdom.Effect.Ignore diff --git a/src/haz3lweb/view/ExplainThis.re b/src/haz3lweb/view/ExplainThis.re index de4a592f6f..7487cc7037 100644 --- a/src/haz3lweb/view/ExplainThis.re +++ b/src/haz3lweb/view/ExplainThis.re @@ -8,23 +8,21 @@ open Haz3lcore; let feedback_view = (message, up_active, up_action, down_active, down_action) => { div( - ~attr=clss(["feedback"]), + ~attrs=[clss(["feedback"])], [ - div(~attr=clss(["message"]), [text(message)]), + div(~attrs=[clss(["message"])], [text(message)]), div( - ~attr= - Attr.many([ - clss(["option"] @ (up_active ? ["active"] : [])), - Attr.on_click(up_action), - ]), + ~attrs=[ + clss(["option"] @ (up_active ? ["active"] : [])), + Attr.on_click(up_action), + ], [text("👍")], ), div( - ~attr= - Attr.many([ - clss(["option"] @ (down_active ? ["active"] : [])), - Attr.on_click(down_action), - ]), + ~attrs=[ + clss(["option"] @ (down_active ? ["active"] : [])), + Attr.on_click(down_action), + ], [text("👎")], ), ], @@ -92,17 +90,17 @@ let example_feedback_view = (~inject, group_id, form_id, example_id, model) => { ); }; -let code_node = text => Node.span(~attr=clss(["code"]), [Node.text(text)]); +let code_node = text => + Node.span(~attrs=[clss(["code"])], [Node.text(text)]); let highlight = (~inject, msg: list(Node.t), id: Id.t, mapping: ColorSteps.t) : (Node.t, ColorSteps.t) => { let (c, mapping) = ColorSteps.get_color(id, mapping); let classes = clss(["highlight-" ++ c, "clickable"]); - let attr = + let attrs = switch (inject) { - | Some(inject) => - Attr.many([ + | Some(inject) => [ classes, Attr.on_mouseenter(_ => inject(UpdateAction.Set(ExplainThis(SetHighlight(Hover(id))))) @@ -113,10 +111,10 @@ let highlight = Attr.on_click(_ => inject(UpdateAction.PerformAction(Select(Term(Id(id, Left))))) ), - ]) - | None => classes + ] + | None => [classes] }; - (Node.span(~attr, msg), mapping); + (Node.span(~attrs, msg), mapping); }; /* @@ -130,58 +128,83 @@ let highlight = let mk_translation = (~inject, text: string): (list(Node.t), ColorSteps.t) => { let omd = Omd.of_string(text); //print_markdown(omd); - let rec translate = - (doc: Omd.t, mapping: ColorSteps.t): (list(Node.t), ColorSteps.t) => + + let rec translate_inline = + (inline: Omd.inline(_), msg, mapping: ColorSteps.t, ~inject) + : (list(Node.t), ColorSteps.t) => { + switch (inline) { + | Omd.Concat(_, items) => + let (nodes, mapping) = + List.fold_left( + ((msg, mapping), item) => { + let (translated_item, mapping) = + translate_inline(item, [], mapping, ~inject); + (List.concat([msg, translated_item]), mapping); + }, + ([], mapping), + items, + ); + (List.append(msg, nodes), mapping); + | Omd.Text(_, d) => (List.append(msg, [Node.text(d)]), mapping) + | Omd.Code(_, d) => (List.append(msg, [code_node(d)]), mapping) + | Omd.Link(_, {label, destination, _}) => + let (d, mapping) = translate_inline(label, [], mapping, ~inject); + let id = + switch (Id.of_string(destination)) { + | Some(id) => id + | None => Id.invalid + }; + let (inner_msg, mapping) = highlight(~inject, d, id, mapping); + (List.append(msg, [inner_msg]), mapping); + | Omd.Emph(_, d) => + let (d, mapping) = translate_inline(d, [], mapping, ~inject); + ( + List.append( + msg, + [ + Node.span( + ~attrs=[ + Attr.style( + Css_gen.create(~field="font-style", ~value="italic"), + ), + ], + d, + ), + ], + ), + mapping, + ); + | _ => (msg, mapping) + }; + }; + + let rec translate_block = + (doc: Omd.doc, mapping: ColorSteps.t) + : (list(Node.t), ColorSteps.t) => { List.fold_left( ((msg, mapping), elem) => { switch (elem) { - | Omd.Paragraph(d) => translate(d, mapping) - | Text(t) => (List.append(msg, [Node.text(t)]), mapping) - | Ul(items) => + | Omd.Paragraph(_, d) => translate_inline(d, msg, mapping, ~inject) + | Omd.List(_, _, _, items) => let (bullets, mapping) = List.fold_left( ((nodes, mapping), d) => { - let (n, mapping) = translate(d, mapping); + let (n, mapping) = translate_block(d, mapping); (List.append(nodes, [Node.li(n)]), mapping); }, ([], mapping), items, ); (List.append(msg, [Node.ul(bullets)]), mapping); /* TODO Hannah - Should this be an ordered list instead of an unordered list? */ - | Code(_name, t) => (List.append(msg, [code_node(t)]), mapping) - | Url(id, d, _title) => - let (d, mapping) = translate(d, mapping); - let id = - switch (Id.of_string(id)) { - | Some(id) => id - | None => Id.invalid - }; - let (inner_msg, mapping) = highlight(~inject, d, id, mapping); - (List.append(msg, [inner_msg]), mapping); - | Emph(d) => - let (d, mapping) = translate(d, mapping); - ( - List.append( - msg, - [ - Node.span( - ~attr= - Attr.style( - Css_gen.create(~field="font-style", ~value="italic"), - ), - d, - ), - ], - ), - mapping, - ); | _ => (msg, mapping) } }, ([], mapping), doc, ); - translate(omd, ColorSteps.empty); + }; + + translate_block(omd, ColorSteps.empty); }; let mk_explanation = @@ -199,7 +222,7 @@ let mk_explanation = settings.explainThis.show_feedback ? [explanation_feedback_view(~inject, group_id, form_id, model)] : []; ( - div([div(~attr=clss(["explanation-contents"]), msg)] @ feedback), + div([div(~attrs=[clss(["explanation-contents"])], msg)] @ feedback), color_map, ); }; @@ -209,21 +232,22 @@ let expander_deco = ~docs: ExplainThisModel.t, ~settings: Settings.t, ~inject, - ~ui_state as {font_metrics, _}: Model.ui_state, + ~ui_state: Model.ui_state, ~options: list((ExplainThisForm.form_id, Segment.t)), ~group: ExplainThisForm.group, ~doc: ExplainThisForm.form, ) => { module Deco = Deco.Deco({ - let font_metrics = font_metrics; - let map = Measured.of_segment(doc.syntactic_form); - let show_backpack_targets = false; - let (_term, terms) = MakeTerm.go(doc.syntactic_form); - let term_ranges = TermRanges.mk(doc.syntactic_form); - let tiles = TileMap.mk(doc.syntactic_form); - let error_ids = []; + let ui_state = ui_state; + let meta = + Editor.Meta.init( + ~settings=CoreSettings.off, + Zipper.unzip(doc.syntactic_form), + ); + let highlights: option(ColorSteps.colorMap) = None; }); + let Model.{font_metrics, _} = ui_state; switch (doc.expandable_id, List.length(options)) { | (None, _) | (_, 0 | 1) => div([]) @@ -254,21 +278,14 @@ let expander_deco = let specificity_menu = Node.div( - ~attr= - Attr.many([ - clss(["specificity-options-menu", "expandable"]), - specificity_style, - ]), + ~attrs=[ + clss(["specificity-options-menu", "expandable"]), + specificity_style, + ], List.map( ((id: ExplainThisForm.form_id, segment: Segment.t)): Node.t => { - let map = Measured.of_segment(segment); let code_view = - Code.simple_view( - ~font_metrics, - ~unselected=segment, - ~map, - ~settings, - ); + Code.simple_view(~font_metrics, ~segment, ~settings); let classes = id == doc.id ? ["selected"] @ get_clss(segment) : get_clss(segment); @@ -279,11 +296,10 @@ let expander_deco = ), ); Node.div( - ~attr= - Attr.many([ - clss(classes), - Attr.on_click(update_group_selection), - ]), + ~attrs=[ + clss(classes), + Attr.on_click(update_group_selection), + ], [code_view], ); }, @@ -293,10 +309,7 @@ let expander_deco = let expand_arrow_style = Attr.create("style", specificity_pos); let expand_arrow = - Node.div( - ~attr=Attr.many([clss(["arrow"]), expand_arrow_style]), - [], - ); + Node.div(~attrs=[clss(["arrow"]), expand_arrow_style], []); let expandable_deco = DecUtil.code_svg( @@ -308,18 +321,17 @@ let expander_deco = ); Node.div( - ~attr= - Attr.many([ - clss(["expandable-target"]), - DecUtil.abs_position(~font_metrics, origin), - Attr.on_click(_ => { - inject( - UpdateAction.UpdateExplainThisModel( - ExplainThisUpdate.SpecificityOpen(!docs.specificity_open), - ), - ) - }), - ]), + ~attrs=[ + clss(["expandable-target"]), + DecUtil.abs_position(~font_metrics, origin), + Attr.on_click(_ => { + inject( + UpdateAction.UpdateExplainThisModel( + ExplainThisUpdate.SpecificityOpen(!docs.specificity_open), + ), + ) + }), + ], [expandable_deco, specificity_menu] @ (docs.specificity_open ? [] : [expand_arrow]), ); @@ -342,7 +354,7 @@ let example_view = ? [] : [ div( - ~attr=Attr.id("examples"), + ~attrs=[Attr.id("examples")], List.mapi( (idx, {term, message, sub_id, _}: ExplainThisForm.example) => { let feedback = @@ -358,7 +370,7 @@ let example_view = ] : []; div( - ~attr=clss(["example"]), + ~attrs=[clss(["example"])], [ Cell.locked( ~segment=term, @@ -368,7 +380,7 @@ let example_view = ~inject, ), div( - ~attr=clss(["explanation"]), + ~attrs=[clss(["explanation"])], [text(message)] @ feedback, ), ], @@ -380,30 +392,29 @@ let example_view = ]; }; -let rec bypass_parens_and_annot_pat = (pat: TermBase.UPat.t) => { +let rec bypass_parens_and_annot_pat = (pat: Pat.t) => { switch (pat.term) { | Parens(p) - | TypeAnn(p, _) => bypass_parens_and_annot_pat(p) - | TyAlias(_) => {...pat, term: EmptyHole} + | Cast(p, _, _) => bypass_parens_and_annot_pat(p) | _ => pat }; }; -let rec bypass_parens_pat = (pat: TermBase.UPat.t) => { +let rec bypass_parens_pat = (pat: Pat.t) => { switch (pat.term) { | Parens(p) => bypass_parens_pat(p) | _ => pat }; }; -let rec bypass_parens_exp = (exp: TermBase.UExp.t) => { +let rec bypass_parens_exp = (exp: Exp.t) => { switch (exp.term) { | Parens(e) => bypass_parens_exp(e) | _ => exp }; }; -let rec bypass_parens_typ = (typ: TermBase.UTyp.t) => { +let rec bypass_parens_typ = (typ: Typ.t) => { switch (typ.term) { | Parens(t) => bypass_parens_typ(t) | _ => typ @@ -521,8 +532,13 @@ let get_doc = let rec get_message_exp = (term) : (list(Node.t), (list(Node.t), ColorSteps.t), list(Node.t)) => - switch (term) { - | TermBase.UExp.Invalid(_) => simple("Not a valid expression") + switch ((term: Exp.term)) { + | Exp.Invalid(_) => simple("Not a valid expression") + | DynamicErrorHole(_) + | FailedCast(_) + | Closure(_) + | Cast(_) + | BuiltinFun(_) => simple("Internal expression") | EmptyHole => get_message(HoleExp.empty_hole_exps) | MultiHole(_children) => get_message(HoleExp.multi_hole_exps) | TyAlias(ty_pat, ty_def, _body) => @@ -542,7 +558,7 @@ let get_doc = ), TyAliasExp.tyalias_exps, ); - | Triv => get_message(TerminalExp.triv_exps) + | Undefined => get_message(UndefinedExp.undefined_exps) | Deferral(_) => get_message(TerminalExp.deferral_exps) | Bool(b) => get_message(TerminalExp.bool_exps(b)) | Int(i) => get_message(TerminalExp.int_exps(i)) @@ -560,7 +576,7 @@ let get_doc = ), ListExp.listlits, ) - | TypFun(tpat, body) => + | TypFun(tpat, body, _) => let basic = group_id => { let tpat_id = List.nth(tpat.ids, 0); let body_id = List.nth(body.ids, 0); @@ -584,7 +600,7 @@ let get_doc = }; /* TODO: More could be done here probably for different patterns. */ basic(TypFunctionExp.type_functions_basic); - | Fun(pat, body) => + | Fun(pat, body, _, _) => let basic = group_id => { let pat_id = List.nth(pat.ids, 0); let body_id = List.nth(body.ids, 0); @@ -773,7 +789,7 @@ let get_doc = } else { basic(FunctionExp.functions_str); } - | Triv => + | Tuple([]) => if (FunctionExp.function_triv_exp.id == get_specificity_level(FunctionExp.functions_triv)) { get_message( @@ -1015,7 +1031,7 @@ let get_doc = } else { basic(FunctionExp.functions_ap); } - | Constructor(v) => + | Constructor(v, _) => if (FunctionExp.function_ctr_exp.id == get_specificity_level(FunctionExp.functions_ctr)) { let pat_id = List.nth(pat.ids, 0); @@ -1042,7 +1058,7 @@ let get_doc = | TyAlias(_) => default // Shouldn't get hit | Invalid(_) => default // Shouldn't get hit | Parens(_) => default // Shouldn't get hit? - | TypeAnn(_) => default // Shouldn't get hit? + | Cast(_) => default // Shouldn't get hit? }; | Tuple(terms) => let basic = group_id => @@ -1297,7 +1313,7 @@ let get_doc = LetExp.lets_str, ); } - | Triv => + | Tuple([]) => if (LetExp.let_triv_exp.id == get_specificity_level(LetExp.lets_triv)) { get_message( @@ -1524,7 +1540,7 @@ let get_doc = } else { basic(LetExp.lets_ap); } - | Constructor(v) => + | Constructor(v, _) => if (LetExp.let_ctr_exp.id == get_specificity_level(LetExp.lets_ctr)) { get_message( ~colorings= @@ -1549,7 +1565,7 @@ let get_doc = | TyAlias(_) => default // Shouldn't get hit | Invalid(_) => default // Shouldn't get hit | Parens(_) => default // Shouldn't get hit? - | TypeAnn(_) => default // Shouldn't get hit? + | Cast(_) => default // Shouldn't get hit? }; | Module(pat, def, body) => message_single( @@ -1566,11 +1582,18 @@ let get_doc = ~mem_id=Term.UExp.rep_id(e_mem), ), ) - | Pipeline(arg, fn) => + | FixF(pat, body, _) => + message_single( + FixFExp.single( + ~pat_id=UPat.rep_id(pat), + ~body_id=UExp.rep_id(body), + ), + ) + | Ap(Reverse, arg, fn) => message_single( PipelineExp.single( - ~arg_id=Term.UExp.rep_id(arg), - ~fn_id=Term.UExp.rep_id(fn), + ~arg_id=UExp.rep_id(arg), + ~fn_id=UExp.rep_id(fn), ), ) | TypAp(f, typ) => @@ -1594,7 +1617,7 @@ let get_doc = TypAppExp.typfunapp_exp_coloring_ids, ); - | Ap(x, arg) => + | Ap(Forward, x, arg) => let x_id = List.nth(x.ids, 0); let arg_id = List.nth(arg.ids, 0); let basic = (group, format, coloring_ids) => { @@ -1605,7 +1628,7 @@ let get_doc = ); }; switch (x.term) { - | Constructor(v) => + | Constructor(v, _) => basic( AppExp.conaps, msg => @@ -1633,7 +1656,7 @@ let get_doc = let x_id = List.nth(x.ids, 0); let supplied_id = Id.mk(); let deferred_id = { - let deferral = List.find(Term.UExp.is_deferral, args); + let deferral = List.find(Exp.is_deferral, args); List.nth(deferral.ids, 0); }; switch (mode) { @@ -1657,11 +1680,11 @@ let get_doc = let color_fn = List.nth(ColorSteps.child_colors, 0); let color_supplied = List.nth(ColorSteps.child_colors, 1); let color_deferred = List.nth(ColorSteps.child_colors, 2); - let add = (mapping, arg: Term.UExp.t) => { + let add = (mapping, arg: Exp.t) => { let arg_id = List.nth(arg.ids, 0); Haz3lcore.Id.Map.add( arg_id, - Term.UExp.is_deferral(arg) ? color_deferred : color_supplied, + Exp.is_deferral(arg) ? color_deferred : color_supplied, mapping, ); }; @@ -1704,34 +1727,35 @@ let get_doc = ), SeqExp.seqs, ); - | Filter((Step, One), pat, body) => + | Filter(Filter({act: (Step, One), pat}), body) => message_single( FilterExp.filter_pause( - ~p_id=Term.UExp.rep_id(pat), - ~body_id=Term.UExp.rep_id(body), + ~p_id=UExp.rep_id(pat), + ~body_id=UExp.rep_id(body), ), ) - | Filter((Step, All), pat, body) => + | Filter(Filter({act: (Step, All), pat}), body) => message_single( FilterExp.filter_debug( - ~p_id=Term.UExp.rep_id(pat), - ~body_id=Term.UExp.rep_id(body), + ~p_id=UExp.rep_id(pat), + ~body_id=UExp.rep_id(body), ), ) - | Filter((Eval, All), pat, body) => + | Filter(Filter({act: (Eval, All), pat}), body) => message_single( FilterExp.filter_eval( - ~p_id=Term.UExp.rep_id(pat), - ~body_id=Term.UExp.rep_id(body), + ~p_id=UExp.rep_id(pat), + ~body_id=UExp.rep_id(body), ), ) - | Filter((Eval, One), pat, body) => + | Filter(Filter({act: (Eval, One), pat}), body) => message_single( FilterExp.filter_hide( - ~p_id=Term.UExp.rep_id(pat), - ~body_id=Term.UExp.rep_id(body), + ~p_id=UExp.rep_id(pat), + ~body_id=UExp.rep_id(body), ), ) + | Filter(_) => simple("Internal expression") | Test(body) => let body_id = List.nth(body.ids, 0); get_message( @@ -1810,7 +1834,7 @@ let get_doc = OpExp.int_un_minus, ); | Meta(Unquote) => - message_single(FilterExp.unquote(~sel_id=Term.UExp.rep_id(exp))) + message_single(FilterExp.unquote(~sel_id=UExp.rep_id(exp))) } | BinOp(op, left, right) => open OpExp; @@ -1887,7 +1911,7 @@ let get_doc = ), CaseExp.case, ); - | Constructor(v) => + | Constructor(v, _) => switch (cls) { | Exp(ModuleVar) => get_message( @@ -1968,7 +1992,7 @@ let get_doc = ), TerminalPat.strlit(s), ) - | Triv => get_message(TerminalPat.triv) + | Tuple([]) => get_message(TerminalPat.triv) | ListLit(elements) => if (List.length(elements) == 0) { get_message(ListPat.listnil); @@ -2003,7 +2027,7 @@ let get_doc = doc, ); switch (tl.term) { - | TermBase.UPat.Cons(hd2, tl2) => + | Pat.Cons(hd2, tl2) => if (ListPat.cons2_pat.id == get_specificity_level(ListPat.cons2)) { let hd2_id = List.nth(hd2.ids, 0); let tl2_id = List.nth(tl2.ids, 0); @@ -2121,7 +2145,7 @@ let get_doc = ), AppPat.ap, ); - | Constructor(con) => + | Constructor(con, _) => get_message( ~format= Some( @@ -2129,7 +2153,7 @@ let get_doc = ), TerminalPat.ctr(con), ) - | TypeAnn(pat, typ) => + | Cast(pat, typ, _) => let pat_id = List.nth(pat.ids, 0); let typ_id = List.nth(typ.ids, 0); get_message( @@ -2150,10 +2174,12 @@ let get_doc = // Shouldn't be hit? default } - | Some(InfoTyp({term, cls, _})) => + | Some(InfoTyp({term, _} as typ_info)) => switch (bypass_parens_typ(term).term) { - | EmptyHole => get_message(HoleTyp.empty_hole) - | MultiHole(_) => get_message(HoleTyp.multi_hole) + | Unknown(SynSwitch) + | Unknown(Internal) + | Unknown(Hole(EmptyHole)) => get_message(HoleTyp.empty_hole) + | Unknown(Hole(MultiHole(_))) => get_message(HoleTyp.multi_hole) | Int => get_message(TerminalTyp.int) | Float => get_message(TerminalTyp.float) | Bool => get_message(TerminalTyp.bool) @@ -2222,7 +2248,7 @@ let get_doc = doc, ); switch (result.term) { - | TermBase.UTyp.Arrow(arg2, result2) => + | Typ.Arrow(arg2, result2) => if (ArrowTyp.arrow3_typ.id == get_specificity_level(ArrowTyp.arrow3)) { let arg2_id = List.nth(arg2.ids, 0); let result2_id = List.nth(result2.ids, 0); @@ -2250,7 +2276,7 @@ let get_doc = } | _ => basic(ArrowTyp.arrow) }; - | Tuple(elements) => + | Prod(elements) => let basic = group => get_message( ~format= @@ -2323,9 +2349,7 @@ let get_doc = } | _ => basic(TupleTyp.tuple) }; - | Constructor(c) => - get_message(SumTyp.sum_typ_nullary_constructor_defs(c)) - | Var(c) when cls == Typ(Constructor) => + | Var(c) when Info.typ_is_constructor_expected(typ_info) => get_message(SumTyp.sum_typ_nullary_constructor_defs(c)) | Var(v) => get_message( @@ -2336,7 +2360,7 @@ let get_doc = TerminalTyp.var(v), ) | Sum(_) => get_message(SumTyp.labelled_sum_typs) - | Ap({term: Constructor(c), _}, _) => + | Ap({term: Var(c), _}, _) => get_message(SumTyp.sum_typ_unary_constructor_defs(c)) | Module(_) => get_message(TerminalTyp.moduletyp) | Dot(t_mod, t_mem) => @@ -2346,7 +2370,7 @@ let get_doc = ~mem_id=Term.UTyp.rep_id(t_mem), ), ) - | Invalid(_) => simple("Not a type or type operator") + | Unknown(Hole(Invalid(_))) => simple("Not a type or type operator") | Ap(_) | Parens(_) => default // Shouldn't be hit? } @@ -2377,8 +2401,8 @@ let get_doc = let section = (~section_clss: string, ~title: string, contents: list(Node.t)) => div( - ~attr=clss(["section", section_clss]), - [div(~attr=clss(["section-title"]), [text(title)])] @ contents, + ~attrs=[clss(["section", section_clss])], + [div(~attrs=[clss(["section-title"])], [text(title)])] @ contents, ); let get_color_map = @@ -2410,13 +2434,13 @@ let view = MessageContent(inject, ui_state, settings), ); div( - ~attr=Attr.id("side-bar"), + ~attrs=[Attr.id("side-bar")], [ div( - ~attr=clss(["explain-this"]), + ~attrs=[Attr.id("explain-this")], [ div( - ~attr=clss(["top-bar"]), + ~attrs=[clss(["header"])], [ Widgets.toggle( ~tooltip="Toggle highlighting", @@ -2426,14 +2450,13 @@ let view = inject(UpdateAction.Set(ExplainThis(SetHighlight(Toggle)))) ), div( - ~attr= - Attr.many([ - clss(["close"]), - Attr.on_click(_ => - inject(UpdateAction.Set(ExplainThis(ToggleShow))) - ), - ]), - [text("x")], + ~attrs=[ + clss(["close"]), + Attr.on_click(_ => + inject(UpdateAction.Set(ExplainThis(ToggleShow))) + ), + ], + [Icons.thin_x], ), ], ), @@ -2444,7 +2467,7 @@ let view = ~title= switch (info) { | None => "Whitespace or Comment" - | Some(info) => Info.cls_of(info) |> Term.Cls.show + | Some(info) => Info.cls_of(info) |> Cls.show }, syn_form @ explanation, ), diff --git a/src/haz3lweb/view/FontSpecimen.re b/src/haz3lweb/view/FontSpecimen.re index 3ee6dc8879..f5a5e6ab38 100644 --- a/src/haz3lweb/view/FontSpecimen.re +++ b/src/haz3lweb/view/FontSpecimen.re @@ -1,3 +1,4 @@ open Virtual_dom.Vdom; -let view = id => Node.span(~attr=Attr.id(id), [Node.text("X")]); +let view = id => + Node.span(~attrs=[Attr.id(id), Attr.class_("code")], [Node.text("X")]); diff --git a/src/haz3lweb/view/Icons.re b/src/haz3lweb/view/Icons.re index 1067286891..52d4e130db 100644 --- a/src/haz3lweb/view/Icons.re +++ b/src/haz3lweb/view/Icons.re @@ -7,32 +7,35 @@ let simple_icon = (~transform="", ~view: string, ds: list(string)) => and an optional (string) transform to apply to each */ Node.create_svg( "svg", - ~attr= - Attr.many( - Attr.[ - create("viewBox", view), - create("width", Printf.sprintf("%fpx", icon_size)), - create("height", Printf.sprintf("%fpx", icon_size)), - create("preserveAspectRatio", "none"), - ], - ), + ~attrs= + Attr.[ + create("viewBox", view), + create("width", Printf.sprintf("%fpx", icon_size)), + create("height", Printf.sprintf("%fpx", icon_size)), + create("preserveAspectRatio", "none"), + ], List.map( d => Node.create_svg( "path", - ~attr= - Attr.many( - [Attr.create("d", d)] - @ ( - transform == "" ? [] : [Attr.create("transform", transform)] - ), - ), + ~attrs= + [Attr.create("d", d)] + @ (transform == "" ? [] : [Attr.create("transform", transform)]), [], ), ds, ), ); +let disk = + simple_icon( + ~view="0 0 1200 1200", + [ + "m994.5 80.25-132.75 0.066406v331.88h-531v-331.88l-265.5-0.066406v1062h1062v-929.25zm-50.586 977.13h-685.96v-477.36h685.96z", + "m693.08 134.91h102.3v210.84h-102.3z", + ], + ); + let gear = simple_icon( ~view="0 0 1200 1200", @@ -122,7 +125,7 @@ let github = let back = simple_icon( - ~view="0 0 330 330", + ~view="-30 0 330 330", [ "M250.606,154.389l-150-149.996c-5.857-5.858-15.355-5.858-21.213,0.001 c-5.857,5.858-5.857,15.355,0.001,21.213l139.393,139.39L79.393,304.394c-5.857,5.858-5.857,15.355,0.001,21.213 C82.322,328.536,86.161,330,90,330s7.678-1.464,10.607-4.394l149.999-150.004c2.814-2.813,4.394-6.628,4.394-10.606 C255,161.018,253.42,157.202,250.606,154.389z", ], @@ -131,7 +134,7 @@ let back = let forward = simple_icon( - ~view="0 0 330 330", + ~view="-40 0 330 330", [ "M250.606,154.389l-150-149.996c-5.857-5.858-15.355-5.858-21.213,0.001 c-5.857,5.858-5.857,15.355,0.001,21.213l139.393,139.39L79.393,304.394c-5.857,5.858-5.857,15.355,0.001,21.213 C82.322,328.536,86.161,330,90,330s7.678-1.464,10.607-4.394l149.999-150.004c2.814-2.813,4.394-6.628,4.394-10.606 C255,161.018,253.42,157.202,250.606,154.389z", ], @@ -197,6 +200,13 @@ let x = "M3382.84 784.3 3462.43 862.829 3540.96 783.238 3601.23 842.704 3522.7 922.295 3602.29 1000.82 3542.82 1061.09 3463.23 982.566 3384.7 1062.16 3324.43 1002.69 3402.96 923.1 3323.37 844.57Z", ], ); +let thin_x = + simple_icon( + ~view="0 0 1200 1200", + [ + "m875.84 422.41c13.59-13.562 20.391-29.938 20.406-49.121-0.015626-19.188-6.8164-35.562-20.406-49.125-13.562-13.586-29.934-20.387-49.121-20.402-19.184 0.015625-35.559 6.8164-49.121 20.402l-177.59 177.59-177.59-177.59c-13.562-13.586-29.938-20.387-49.121-20.402-19.188 0.015625-35.562 6.8164-49.125 20.402-13.586 13.562-20.387 29.938-20.402 49.125 0.015625 19.184 6.8164 35.559 20.402 49.121l177.59 177.59-177.59 177.59c-13.586 13.562-20.387 29.938-20.402 49.121 0.015625 19.188 6.8164 35.559 20.402 49.121 13.562 13.59 29.938 20.391 49.125 20.406 19.184-0.015626 35.559-6.8164 49.121-20.406l177.59-177.59 177.59 177.59c13.562 13.59 29.938 20.391 49.121 20.406 19.188-0.015626 35.559-6.8164 49.121-20.406 13.59-13.562 20.391-29.934 20.406-49.121-0.015626-19.184-6.8164-35.559-20.406-49.121l-177.59-177.59z", + ], + ); let backpack = simple_icon( @@ -211,3 +221,13 @@ let backpack = "m438.25 148.18 41.09-6.3125v-34.773l7.9062-28.441s-37.945 17.387-48.996 34.766c-11.062 17.387-15.816 26.867-15.816 34.766 0 7.9062 15.816-0.003907 15.816-0.003907z", ], ); + +let command_palette_sparkle = + simple_icon( + ~view="400 400 400 400", + [ + "m505.08 561.96c-10.16 36.805-29.699 70.34-56.707 97.328-27.008 26.984-60.559 46.5-97.371 56.633 36.82 10.152 70.375 29.688 97.383 56.695 27.008 27.008 46.543 60.562 56.695 97.383 10.145-36.824 29.676-70.387 56.684-97.395 27.012-27.012 60.57-46.543 97.398-56.684-36.816-10.121-70.375-29.633-97.383-56.621-27.012-26.988-46.547-60.531-56.699-97.34z", + "m849 507.24c-46.578-13.02-82.977-49.418-96-96-13.09 46.758-49.766 83.203-96.602 96 46.812 12.844 83.469 49.273 96.602 96 13.043-46.566 49.434-82.957 96-96z", + "m554.76 426.6c6.5195-23.285 24.715-41.48 48-48-23.297-6.5-41.5-24.707-48-48-6.5 23.293-24.707 41.5-48 48 23.281 6.5195 41.477 24.715 48 48z", + ], + ); diff --git a/src/haz3lweb/view/Kind.re b/src/haz3lweb/view/Kind.re index 148336e1c2..8feb3af0b0 100644 --- a/src/haz3lweb/view/Kind.re +++ b/src/haz3lweb/view/Kind.re @@ -2,7 +2,7 @@ open Virtual_dom.Vdom; open Node; open Util.Web; -let view = (kind: Haz3lcore.TypBase.Kind.t): Node.t => +let view = (kind: Haz3lcore.Ctx.kind): Node.t => switch (kind) { | Singleton(ty) => div_c("kind-view", [Type.view(ty)]) | Abstract => div_c("kind-view", [text("Type")]) diff --git a/src/haz3lweb/view/NutMenu.re b/src/haz3lweb/view/NutMenu.re index 7b771c40fb..b67f406504 100644 --- a/src/haz3lweb/view/NutMenu.re +++ b/src/haz3lweb/view/NutMenu.re @@ -1,18 +1,104 @@ +open Util; open Virtual_dom.Vdom; open Js_of_ocaml; open Node; open Util.Web; open Widgets; +open Haz3lcore; + +let settings_group = (~inject, name: string, ts) => { + let toggle = ((_icon, tooltip, bool, setting)) => + toggle_named("", ~tooltip, bool, _ => inject(UpdateAction.Set(setting))); + div_c( + "group", + [ + div_c("name", [text(name)]), + div_c("contents", List.map(toggle, ts)), + ], + ); +}; + +let semantics_group = (~inject, ~settings: Settings.t) => { + settings_group( + ~inject, + "Semantics", + [ + ("τ", "Types", settings.core.statics, Statics), + ("⇲", "Completion", settings.core.assist, Assist), + ("𝛿", "Evaluation", settings.core.dynamics, Dynamics), + ("?", "Docs", settings.explainThis.show, ExplainThis(ToggleShow)), + // ( + // "👍", + // "Feedback", + // settings.explainThis.show_feedback, + // ExplainThis(ToggleShowFeedback), + // ), + ], + ); +}; + +let values_group = (~inject, ~settings: Settings.t) => { + let s = settings.core.evaluation; + settings_group( + ~inject, + "Value Display", + [ + ("λ", "Functions", s.show_fn_bodies, Evaluation(ShowFnBodies)), + ("|", "Cases", s.show_case_clauses, Evaluation(ShowCaseClauses)), + ("f", "Fixpoints", s.show_fixpoints, Evaluation(ShowFixpoints)), + (Unicode.castArrowSym, "Casts", s.show_casts, Evaluation(ShowCasts)), + ], + ); +}; + +let stepper_group = (~inject, ~settings: Settings.t) => { + let s = settings.core.evaluation; + settings_group( + ~inject, + "Stepper", + [ + ("🔍", "Show lookups", s.show_lookup_steps, Evaluation(ShowLookups)), + ( + "🤫", + "Show hidden", + s.show_hidden_steps, + Evaluation(ShowHiddenSteps), + ), + ("⏯️", "Filters", s.show_stepper_filters, Evaluation(ShowFilters)), + ], + ); +}; + +let dev_group = (~inject, ~settings: Settings.t) => { + settings_group( + ~inject, + "Developer", + [ + ("✓", "Benchmarks", settings.benchmark, Benchmark), + ("𝑒", "Elaboration", settings.core.elaborate, Elaborate), + ("↵", "Whitespace", settings.secondary_icons, SecondaryIcons), + ], + ); +}; + +let settings_menu = (~inject, ~settings: Settings.t) => { + [ + semantics_group(~inject, ~settings), + values_group(~inject, ~settings), + stepper_group(~inject, ~settings), + dev_group(~inject, ~settings), + ]; +}; let export_persistent_data = (~inject: Update.t => 'a) => button_named( - Icons.sprout, - _ => inject(ExportPersistentData), + Icons.export, + _ => inject(Export(ExportPersistentData)), ~tooltip="Export All Persistent Data", ); let reset_hazel = - button( + button_named( Icons.bomb, _ => { let confirmed = @@ -25,144 +111,100 @@ let reset_hazel = }; Virtual_dom.Vdom.Effect.Ignore; }, - ~tooltip="Clear Local Storage and Reload (LOSE ALL DATA)", + ~tooltip="Reset Hazel (LOSE ALL DATA)", ); let reparse = (~inject: Update.t => 'a) => - button( + button_named( Icons.backpack, - _ => inject(ReparseCurrentEditor), - ~tooltip="Reparse Current Editor", + _ => inject(PerformAction(Reparse)), + ~tooltip="Reparse Editor", ); -let settings_menu = - ( - ~inject, - ~settings as - { - core: {evaluation, _} as core, - benchmark, - secondary_icons, - explainThis, - _, - }: Settings.t, - ) => { - let toggle = (icon, tooltip, bool, setting) => - toggle_named(icon, ~tooltip, bool, _ => - inject(UpdateAction.Set(setting)) - ); - [ - toggle("τ", "Toggle Statics", core.statics, Statics), - toggle("⇲", "Toggle Completion", core.assist, Assist), - toggle("↵", "Show Whitespace", secondary_icons, SecondaryIcons), - toggle("✓", "Print Benchmarks", benchmark, Benchmark), - toggle("𝛿", "Toggle Dynamics", core.dynamics, Dynamics), - toggle("𝑒", "Show Elaboration", core.elaborate, Elaborate), - toggle( - "λ", - "Show Function Bodies", - evaluation.show_fn_bodies, - Evaluation(ShowFnBodies), - ), - toggle( - "|", - "Show Case Clauses", - evaluation.show_case_clauses, - Evaluation(ShowCaseClauses), - ), - toggle( - "f", - "Show fixpoints", - evaluation.show_fixpoints, - Evaluation(ShowFixpoints), - ), - toggle( - Unicode.castArrowSym, - "Show casts", - evaluation.show_casts, - Evaluation(ShowCasts), - ), - toggle( - "🔍", - "Show Lookup Steps", - evaluation.show_lookup_steps, - Evaluation(ShowLookups), - ), - toggle( - "⏯️", - "Show Stepper Filters", - evaluation.show_stepper_filters, - Evaluation(ShowFilters), - ), - toggle( - "🤫", - "Show Hidden Steps", - evaluation.show_hidden_steps, - Evaluation(ShowHiddenSteps), - ), - toggle( - "?", - "Show Docs Sidebar", - explainThis.show, - ExplainThis(ToggleShow), - ), - toggle( - "👍", - "Show Docs Feedback", - explainThis.show_feedback, - ExplainThis(ToggleShowFeedback), - ), - ]; +let item_group = (~inject as _, name: string, ts) => { + div_c("group", [div_c("name", [text(name)]), div_c("contents", ts)]); }; -let export_menu = (~inject, ~settings: Settings.t, editors: Editors.t) => - switch (editors) { - | Scratch(slide_idx, slides) => - let state = List.nth(slides, slide_idx); - [ScratchMode.export_button(state)]; - | Documentation(name, slides) => - let state = List.assoc(name, slides); - [ScratchMode.export_button(state)]; - | Exercises(_, _, exercise) when settings.instructor_mode => [ +let file_group_scratch = (~inject) => + item_group( + ~inject, + "File", + [ScratchMode.export_button(inject), ScratchMode.import_button(inject)], + ); + +let reset_group_scratch = (~inject) => + item_group( + ~inject, + "Reset", + [ScratchMode.reset_button(inject), reparse(~inject), reset_hazel], + ); + +let file_group_exercises = (~inject) => + item_group( + ~inject, + "File", + [ + ExerciseMode.export_submission(inject), + ExerciseMode.import_submission(~inject), + ], + ); + +let reset_group_exercises = (~inject) => + item_group( + ~inject, + "Reset", + [ExerciseMode.reset_button(inject), reparse(~inject), reset_hazel], + ); + +let dev_group_exercises = (~inject) => + item_group( + ~inject, + "Developer Export", + [ export_persistent_data(~inject), - ExerciseMode.export_submission(~settings), - ExerciseMode.instructor_export(exercise), - ExerciseMode.instructor_transitionary_export(exercise), - ExerciseMode.instructor_grading_export(exercise), - ] - | Exercises(_) => [ExerciseMode.export_submission(~settings)] - }; + ExerciseMode.instructor_export(inject), + ExerciseMode.instructor_transitionary_export(inject), + ExerciseMode.instructor_grading_export(inject), + ], + ); -let import_menu = (~inject, editors: Editors.t) => +let file_menu = (~inject, ~settings: Settings.t, editors: Editors.t) => switch (editors) { - | Scratch(_) + | Scratch(_) => [ + file_group_scratch(~inject), + reset_group_scratch(~inject), + ] | Documentation(_) => [ - ScratchMode.import_button(inject), - ScratchMode.reset_button(inject), + file_group_scratch(~inject), + reset_group_scratch(~inject), + ] + | Exercises(_) when settings.instructor_mode => [ + file_group_exercises(~inject), + reset_group_exercises(~inject), + dev_group_exercises(~inject), ] | Exercises(_) => [ - ExerciseMode.import_submission(~inject), - ExerciseMode.reset_button(inject), + file_group_exercises(~inject), + reset_group_exercises(~inject), ] }; let submenu = (~tooltip, ~icon, menu) => div( - ~attr=clss(["top-menu-item"]), + ~attrs=[clss(["top-menu-item"])], [ div( - ~attr=Attr.many([clss(["submenu-icon"]), Attr.title(tooltip)]), - [div(~attr=clss(["icon"]), [icon])], + ~attrs=[clss(["submenu-icon"]), Attr.title(tooltip)], + [div(~attrs=[clss(["icon"])], [icon])], ), - div(~attr=clss(["submenu"]), menu), + div(~attrs=[clss(["submenu"])], menu), ], ); let view = - (~inject: Update.t => 'a, ~settings: Settings.t, ~editors: Editors.t) => [ - a(~attr=clss(["nut-icon"]), [Icons.hazelnut]), + (~inject: Update.t => 'a, ~settings: Settings.t, ~editors: Editors.t) => div( - ~attr=clss(["nut-menu"]), + ~attrs=[clss(["nut-menu"])], [ submenu( ~tooltip="Settings", @@ -170,17 +212,21 @@ let view = settings_menu(~inject, ~settings), ), submenu( - ~tooltip="Export", - ~icon=Icons.export, - export_menu(~inject, ~settings, editors), + ~tooltip="File", + ~icon=Icons.disk, + file_menu(~inject, ~settings, editors), ), - submenu( - ~tooltip="Import", - ~icon=Icons.import, - import_menu(~inject, editors), + button( + Icons.command_palette_sparkle, + _ => { + NinjaKeys.open_command_palette(); + Effect.Ignore; + }, + ~tooltip= + "Command Palette (" + ++ Keyboard.meta(Os.is_mac^ ? Mac : PC) + ++ " + k)", ), - reparse(~inject), - reset_hazel, link( Icons.github, "https://github.com/hazelgrove/hazel", @@ -188,5 +234,4 @@ let view = ), link(Icons.info, "https://hazel.org", ~tooltip="Hazel Homepage"), ], - ), -]; + ); diff --git a/src/haz3lweb/view/Page.re b/src/haz3lweb/view/Page.re index fe4e1f43ba..df98ba5ee9 100644 --- a/src/haz3lweb/view/Page.re +++ b/src/haz3lweb/view/Page.re @@ -1,25 +1,36 @@ +open Util; +open Web; open Js_of_ocaml; open Haz3lcore; open Virtual_dom.Vdom; open Node; -let handlers = (~inject: UpdateAction.t => Ui_effect.t(unit), model) => { - let get_selection = (model: Model.t): string => - model.editors |> Editors.get_editor |> Printer.to_string_selection; - let key_handler = - (~inject, ~dir: Key.dir, evt: Js.t(Dom_html.keyboardEvent)) - : Effect.t(unit) => - Effect.( - switch (Keyboard.handle_key_event(Key.mk(dir, evt))) { - | None => Ignore - | Some(action) => - Many([Prevent_default, Stop_propagation, inject(action)]) - } - ); +let key_handler = + ( + ~inject: UpdateAction.t => Ui_effect.t(unit), + ~dir: Key.dir, + editor: Editor.t, + evt: Js.t(Dom_html.keyboardEvent), + ) + : Effect.t(unit) => { + open Effect; + let key = Key.mk(dir, evt); + switch (ProjectorView.key_handoff(editor, key)) { + | Some(action) => + Many([Prevent_default, inject(PerformAction(Project(action)))]) + | None => + switch (Keyboard.handle_key_event(key)) { + | None => Ignore + | Some(action) => Many([Prevent_default, inject(action)]) + } + }; +}; + +let handlers = + (~inject: UpdateAction.t => Ui_effect.t(unit), editor: Editor.t) => { [ - Attr.on_keypress(_ => Effect.Prevent_default), - Attr.on_keyup(key_handler(~inject, ~dir=KeyUp)), - Attr.on_keydown(key_handler(~inject, ~dir=KeyDown)), + Attr.on_keyup(key_handler(~inject, editor, ~dir=KeyUp)), + Attr.on_keydown(key_handler(~inject, editor, ~dir=KeyDown)), /* safety handler in case mousedown overlay doesn't catch it */ Attr.on_mouseup(_ => inject(SetMeta(Mouseup))), Attr.on_blur(_ => { @@ -31,104 +42,141 @@ let handlers = (~inject: UpdateAction.t => Ui_effect.t(unit), model) => { Effect.Ignore; }), Attr.on_copy(_ => { - JsUtil.copy(get_selection(model)); + JsUtil.copy(Printer.to_string_selection(editor)); Effect.Ignore; }), Attr.on_cut(_ => { - JsUtil.copy(get_selection(model)); + JsUtil.copy(Printer.to_string_selection(editor)); inject(UpdateAction.PerformAction(Destruct(Left))); }), Attr.on_paste(evt => { let pasted_text = Js.to_string(evt##.clipboardData##getData(Js.string("text"))) - |> Str.global_replace(Str.regexp("\n[ ]*"), "\n"); + |> Util.StringUtil.trim_leading; Dom.preventDefault(evt); - inject(UpdateAction.Paste(pasted_text)); + inject(PerformAction(Paste(pasted_text))); }), ]; }; +let top_bar = + ( + ~inject: UpdateAction.t => Ui_effect.t(unit), + ~settings: Settings.t, + ~editors, + ) => + div( + ~attrs=[Attr.id("top-bar")], + [ + div( + ~attrs=[Attr.class_("wrap")], + [a(~attrs=[clss(["nut-icon"])], [Icons.hazelnut])], + ), + NutMenu.view(~inject, ~settings, ~editors), + div( + ~attrs=[Attr.class_("wrap")], + [div(~attrs=[Attr.id("title")], [text("hazel")])], + ), + div( + ~attrs=[Attr.class_("wrap")], + [EditorModeView.view(~inject, ~settings, ~editors)], + ), + ], + ); + let main_view = ( ~inject: UpdateAction.t => Ui_effect.t(unit), - {settings, editors, explainThisModel, results, statics, ui_state, _}: Model.t, + {settings, editors, explainThisModel, results, ui_state, _}: Model.t, ) => { let editor = Editors.get_editor(editors); - let statics = Editors.lookup_statics(~settings, ~statics, editors); - let cursor_info = Indicated.ci_of(editor.state.zipper, statics.info_map); - let top_bar = - div( - ~attr=Attr.id("top-bar"), - NutMenu.view(~inject, ~settings, ~editors) - @ [div(~attr=Attr.id("title"), [text("hazel")])] - @ [EditorModeView.view(~inject, ~settings, ~editors)], - ); - let bottom_bar = CursorInspector.view(~inject, ~settings, cursor_info); - let sidebar = - settings.explainThis.show && settings.core.statics - ? ExplainThis.view( - ~inject, - ~ui_state, - ~settings, - ~explainThisModel, - cursor_info, - ) - : div([]); + let cursor_info = + Indicated.ci_of(editor.state.zipper, editor.state.meta.statics.info_map); let highlights = ExplainThis.get_color_map(~settings, ~explainThisModel, cursor_info); - let editors_view = + let (editors_view, cursor_info) = switch (editors) { | Scratch(idx, _) => let result_key = ScratchSlide.scratch_key(string_of_int(idx)); - ScratchMode.view( - ~inject, - ~ui_state, - ~settings, - ~highlights, - ~results, - ~result_key, - ~statics, - editor, - ); + let view = + ScratchMode.view( + ~inject, + ~ui_state, + ~settings, + ~highlights, + ~results, + ~result_key, + editor, + ); + (view, cursor_info); | Documentation(name, _) => let result_key = ScratchSlide.scratch_key(name); - let info = - SlideContent.get_content(editors) - |> Option.map(i => div(~attr=Attr.id("slide"), [i])) - |> Option.to_list; - info - @ ScratchMode.view( + let view = + ScratchMode.view( ~inject, ~ui_state, ~settings, ~highlights, ~results, ~result_key, - ~statics, editor, ); + let info = + SlideContent.get_content(editors) + |> Option.map(i => div(~attrs=[Attr.id("slide")], [i])) + |> Option.to_list; + (info @ view, cursor_info); | Exercises(_, _, exercise) => - ExerciseMode.view( - ~inject, - ~ui_state, - ~settings, - ~highlights, - ~results, - ~exercise, - ) + /* Note the exercises mode uses a seperate path to calculate + * statics and dynamics via stitching together multiple editors */ + let stitched_dynamics = + Exercise.stitch_dynamic( + settings.core, + exercise, + settings.core.dynamics ? Some(results) : None, + ); + let statics = + Exercise.statics_of_stiched_dynamics(exercise, stitched_dynamics); + let cursor_info = + Indicated.ci_of(editor.state.zipper, statics.info_map); + let highlights = + ExplainThis.get_color_map(~settings, ~explainThisModel, cursor_info); + let view = + ExerciseMode.view( + ~inject, + ~ui_state, + ~settings, + ~highlights, + ~stitched_dynamics, + ~exercise, + ); + (view, cursor_info); }; + + let bottom_bar = + CursorInspector.view(~inject, ~settings, editor, cursor_info); + let sidebar = + settings.explainThis.show && settings.core.statics + ? ExplainThis.view( + ~inject, + ~ui_state, + ~settings, + ~explainThisModel, + cursor_info, + ) + : div([]); [ - top_bar, + top_bar(~inject, ~settings, ~editors), div( - ~attr= - Attr.many([ - Attr.id("main"), - Attr.classes([Settings.show_mode(settings.mode)]), - ]), + ~attrs=[ + Attr.id("main"), + Attr.classes([Settings.show_mode(settings.mode)]), + ], editors_view, ), sidebar, bottom_bar, + ContextInspector.view(~inject, ~settings, cursor_info), ]; }; @@ -137,7 +185,10 @@ let get_selection = (model: Model.t): string => let view = (~inject: UpdateAction.t => Ui_effect.t(unit), model: Model.t) => div( - ~attr=Attr.many(Attr.[id("page"), ...handlers(~inject, model)]), + ~attrs=[ + Attr.id("page"), + ...handlers(~inject, Editors.get_editor(model.editors)), + ], [ FontSpecimen.view("font-specimen"), DecUtil.filters, diff --git a/src/haz3lweb/view/ProjectorView.re b/src/haz3lweb/view/ProjectorView.re new file mode 100644 index 0000000000..1669ff136d --- /dev/null +++ b/src/haz3lweb/view/ProjectorView.re @@ -0,0 +1,313 @@ +open Haz3lcore; +open Virtual_dom.Vdom; +open Node; +open ProjectorBase; +open Projector; +open Util; +open Util.OptUtil.Syntax; +open Util.Web; + +type kind = Base.kind; + +/* A friendly name for each projector. This is used + * both for identifying a projector in the CSS and for + * selecting projectors in the projector panel menu */ +let name = (p: kind): string => + switch (p) { + | Fold => "fold" + | Info => "type" + | Checkbox => "check" + | Slider => "slider" + | SliderF => "sliderf" + | TextArea => "text" + }; + +/* This must be updated and kept 1-to-1 with the above + * name function in order to be able to select the + * projector in the projector panel menu */ +let of_name = (p: string): kind => + switch (p) { + | "fold" => Fold + | "type" => Info + | "check" => Checkbox + | "slider" => Slider + | "sliderf" => SliderF + | "text" => TextArea + | _ => failwith("Unknown projector kind") + }; + +/* Projectors get a default backing decoration similar + * to token decorations. This can be made transparent + * in the CSS if no backing is wanted */ +let backing_deco = + ( + ~font_metrics: FontMetrics.t, + ~measurement: Measured.measurement, + ~shape: shape, + ) => + switch (shape) { + | Inline(_) + | Block(_) => + PieceDec.relative_shard({ + font_metrics, + measurement, + tips: (Some(Convex), Some(Convex)), + }) + }; + +/* Adds attributes to a projector UI to support + * custom styling when selected or indicated */ +let status = (indicated: option(Direction.t), selected: bool, shape: shape) => + (selected ? ["selected"] : []) + @ ( + switch (shape) { + | Inline(_) => ["inline"] + | Block(_) => ["block"] + } + ) + @ ( + switch (indicated) { + | Some(d) => ["indicated", Direction.show(d)] + | None => [] + } + ); + +/* Wraps the view function for a projector, absolutely positioning + * relative to the syntax, adding a default backing decoration, and + * adding fallthrough handlers where appropriate*/ +let view_wrapper = + ( + ~inject: UpdateAction.t => Ui_effect.t(unit), + ~font_metrics: FontMetrics.t, + ~measurement: Measured.measurement, + ~info: info, + ~indication: option(Direction.t), + ~selected: bool, + p: Base.projector, + view: Node.t, + ) => { + let shape = Projector.shape(p, info); + let focus = (id, _) => + Effect.( + Many([ + Stop_propagation, + inject(PerformAction(Project(Focus(id, None)))), + ]) + ); + div( + ~attrs=[ + Attr.classes( + ["projector", name(p.kind)] @ status(indication, selected, shape), + ), + Attr.on_mousedown(focus(info.id)), + DecUtil.abs_style(measurement, ~font_metrics), + ], + [view, backing_deco(~font_metrics, ~measurement, ~shape)], + ); +}; + +/* Dispatches projector external actions to editor-level actions */ +let handle = (id, action: external_action): Action.project => + switch (action) { + | Remove => Remove(id) + | Escape(d) => Escape(id, d) + | SetSyntax(f) => SetSyntax(id, f) + }; + +/* Extracts projector-instance-specific metadata necessary to + * render the view, instantiates appropriate action handlers, + * renders the view, and then wraps it so as to position it + * correctly with respect to the underyling editor */ +let setup_view = + ( + id: Id.t, + ~meta: Editor.Meta.t, + ~inject: UpdateAction.t => Ui_effect.t(unit), + ~font_metrics, + ~indication: option(Direction.t), + ) + : option(Node.t) => { + let* p = Id.Map.find_opt(id, meta.syntax.projectors); + let* syntax = Some(p.syntax); + let ci = Id.Map.find_opt(id, meta.statics.info_map); + let info = {id, ci, syntax}; + let+ measurement = Measured.find_pr_opt(p, meta.syntax.measured); + let (module P) = to_module(p.kind); + let parent = a => inject(PerformAction(Project(handle(id, a)))); + let local = a => + inject(PerformAction(Project(SetModel(id, P.update(p.model, a))))); + view_wrapper( + ~inject, + ~font_metrics, + ~measurement, + ~indication, + ~info, + ~selected=List.mem(id, meta.syntax.selection_ids), + p, + P.view(p.model, ~info, ~local, ~parent), + ); +}; + +let indication = (z, id) => + switch (Indicated.piece(z)) { + | Some((p, d, _)) when Piece.id(p) == id => Some(Direction.toggle(d)) + | _ => None + }; + +/* Returns a div containing all projector UIs, intended to + * be absolutely positioned atop a rendered editor UI */ +let all = (z, ~meta: Editor.Meta.t, ~inject, ~font_metrics) => + div_c( + "projectors", + List.filter_map( + ((id, _)) => { + let indication = indication(z, id); + setup_view(id, ~meta, ~inject, ~font_metrics, ~indication); + }, + Id.Map.bindings(meta.syntax.projectors) |> List.rev, + ), + ); + +/* When the caret is directly adjacent to a projector, keyboard commands + * can be overidden here. Right now, trying to move into the projector, + * that is, pressing left when it's to the right or vice-versa, without + * holding down a modifier, will give the projector focus (if its can_focus) + * flag is set. Be conservative about these kind of overloads; you need + * to consider how they interact with all the editor keyboard commands. + * For example, without the modifiers check, this would break selection + * around a projector. */ +let key_handoff = (editor: Editor.t, key: Key.t): option(Action.project) => + switch (Editor.indicated_projector(editor)) { + | None => None + | Some((id, p)) => + let* (_, d, _) = Indicated.piece(editor.state.zipper); + let (module P) = to_module(p.kind); + switch (key) { + | {key, sys: _, shift: Up, meta: Up, ctrl: Up, alt: Up} when P.can_focus => + switch (key, d) { + | (D("ArrowRight"), Right) => Some(Action.Focus(id, Some(Left))) + | (D("ArrowLeft"), Left) => Some(Focus(id, Some(Right))) + | _ => None + } + | _ => None + }; + }; + +/* The projector selection panel on the right of the bottom bar */ +module Panel = { + let option_view = (name, n) => + option( + ~attrs=n == name ? [Attr.create("selected", "selected")] : [], + [text(n)], + ); + + /* Decide which projectors are applicable based on the cursor info. + * This is slightly inside-out as elsewhere it depends on the underlying + * syntax, which is not easily available here */ + let applicable_projectors = (ci: Info.t): list(Base.kind) => + ( + switch (Info.cls_of(ci)) { + | Exp(Bool) + | Pat(Bool) => [Base.Checkbox] + | Exp(Int) + | Pat(Int) => [Slider] + | Exp(Float) + | Pat(Float) => [SliderF] + | Exp(String) + | Pat(String) => [TextArea] + | _ => [] + } + ) + @ [Base.Fold] + @ ( + switch (ci) { + | InfoExp(_) + | InfoPat(_) => [(Info: Base.kind)] + | _ => [] + } + ); + + let toggle_projector = (active, id, ci): Action.project => + active || applicable_projectors(ci) == [] + ? Remove(id) : SetIndicated(List.hd(applicable_projectors(ci))); + + let toggle_view = (~inject, ci, id, active: bool, might_project) => + div( + ~attrs=[ + clss( + ["toggle-switch"] + @ (active ? ["active"] : []) + @ (might_project ? [] : ["inactive"]), + ), + Attr.on_mousedown(_ => + might_project + ? inject(toggle_projector(active, id, ci)) : Effect.Ignore + ), + ], + [ + div( + ~attrs=[clss(["toggle-knob"])], + [ + Node.create( + "img", + ~attrs=[Attr.src("img/noun-fold-1593402.svg")], + [], + ), + ], + ), + ], + ); + + let kind = (editor: Editor.t) => { + let+ (_, p) = Editor.indicated_projector(editor); + p.kind; + }; + + let id = (editor: Editor.t) => { + switch (Editor.indicated_projector(editor)) { + | Some((id, _)) => id + | None => Id.invalid + }; + }; + + let currently_selected = editor => + option_view( + switch (kind(editor)) { + | None => "Fold" + | Some(k) => name(k) + }, + ); + + let view = (~inject, editor: Editor.t, ci: Info.t) => { + let might_project = + switch (Indicated.piece''(editor.state.zipper)) { + | Some((p, _, _)) => minimum_projection_condition(p) + | None => false + }; + let applicable_projectors = applicable_projectors(ci); + let should_show = might_project && applicable_projectors != []; + let select_view = + Node.select( + ~attrs=[ + Attr.on_change((_, name) => + inject(Action.SetIndicated(of_name(name))) + ), + ], + (might_project ? applicable_projectors : []) + |> List.map(name) + |> List.map(currently_selected(editor)), + ); + let toggle_view = + toggle_view( + ~inject, + ci, + id(editor), + kind(editor) != None, + might_project, + ); + div( + ~attrs=[Attr.id("projectors")], + (should_show ? [select_view] : []) @ [toggle_view], + ); + }; +}; diff --git a/src/haz3lweb/view/ScratchMode.re b/src/haz3lweb/view/ScratchMode.re index 2a967300d2..7fdc8eb361 100644 --- a/src/haz3lweb/view/ScratchMode.re +++ b/src/haz3lweb/view/ScratchMode.re @@ -1,3 +1,4 @@ +open Util; open Haz3lcore; type state = (Id.t, Editor.t); @@ -10,7 +11,6 @@ let view = ~highlights, ~results: ModelResults.t, ~result_key, - ~statics as {error_ids, _}: CachedStatics.statics, editor: Editor.t, ) => { let result = ModelResults.lookup(results, result_key); @@ -36,7 +36,6 @@ let view = ~ui_state, ~settings, ~target_id, - ~error_ids, ~test_results, ~footer?, ~highlights, @@ -45,20 +44,16 @@ let view = ]; }; -let export_button = state => +let export_button = (inject: Update.t => Ui_effect.t(unit)) => Widgets.button_named( - Icons.star, - _ => { - let json_data = ScratchSlide.export(state); - JsUtil.download_json("hazel-scratchpad", json_data); - Virtual_dom.Vdom.Effect.Ignore; - }, + Icons.export, + _ => inject(Export(ExportScratchSlide)), ~tooltip="Export Scratchpad", ); let import_button = inject => Widgets.file_select_button_named( "import-scratchpad", - Icons.star, + Icons.import, file => { switch (file) { | None => Virtual_dom.Vdom.Effect.Ignore @@ -82,5 +77,5 @@ let reset_button = inject => Virtual_dom.Vdom.Effect.Ignore; }; }, - ~tooltip="Reset Scratchpad", + ~tooltip="Reset Editor", ); diff --git a/src/haz3lweb/view/StepperView.re b/src/haz3lweb/view/StepperView.re index 2a31bf9f0d..b3d3884c4d 100644 --- a/src/haz3lweb/view/StepperView.re +++ b/src/haz3lweb/view/StepperView.re @@ -3,10 +3,10 @@ open Node; open Haz3lcore; let settings_modal = (~inject, settings: CoreSettings.Evaluation.t) => { - let modal = div(~attr=Attr.many([Attr.class_("settings-modal")])); + let modal = div(~attrs=[Attr.class_("settings-modal")]); let setting = (icon, name, current, action: UpdateAction.settings_action) => div( - ~attr=Attr.many([Attr.class_("settings-toggle")]), + ~attrs=[Attr.class_("settings-toggle")], [ Widgets.toggle(~tooltip=name, icon, current, _ => inject(Update.Set(action)) @@ -17,9 +17,9 @@ let settings_modal = (~inject, settings: CoreSettings.Evaluation.t) => { [ modal([ div( - ~attr=Attr.many([Attr.class_("settings-modal-top")]), + ~attrs=[Attr.class_("settings-modal-top")], [ - Widgets.button(Icons.x, _ => + Widgets.button(Icons.thin_x, _ => inject(Update.Set(Evaluation(ShowSettings))) ), ], @@ -74,13 +74,12 @@ let settings_modal = (~inject, settings: CoreSettings.Evaluation.t) => { ), ]), div( - ~attr= - Attr.many([ - Attr.class_("modal-back"), - Attr.on_mousedown(_ => - inject(Update.Set(Evaluation(ShowSettings))) - ), - ]), + ~attrs=[ + Attr.class_("modal-back"), + Attr.on_mousedown(_ => + inject(Update.Set(Evaluation(ShowSettings))) + ), + ], [], ), ]; @@ -92,24 +91,16 @@ let stepper_view = ~settings: CoreSettings.Evaluation.t, ~font_metrics, ~result_key, + ~read_only: bool, stepper: Stepper.t, ) => { - let button_back = - Widgets.button_d( - Icons.undo, - inject(UpdateAction.StepperAction(result_key, StepBackward)), - ~disabled=Stepper.undo_point(~settings, stepper.previous) == None, - ~tooltip="Step Backwards", - ); - let (hidden, previous) = - if (settings.stepper_history) { - Stepper.get_history(~settings, stepper); - } else { - ([], []); - }; - let dh_code_previous = (step_with_previous: Stepper.step_with_previous) => + let step_dh_code = + ( + ~next_steps, + {previous_step, hidden_steps, chosen_step, d}: Stepper.step_info, + ) => div( - ~attr=Attr.classes(["result"]), + ~attrs=[Attr.classes(["result"])], [ DHCode.view( ~inject, @@ -117,119 +108,114 @@ let stepper_view = ~selected_hole_instance=None, ~font_metrics, ~width=80, - ~previous_step=step_with_previous.previous, - ~chosen_step=Some(step_with_previous.step), - ~hidden_steps=step_with_previous.hidden, + ~previous_step, + ~chosen_step, + ~hidden_steps, ~result_key, - step_with_previous.step.d, + ~next_steps, + ~infomap=Id.Map.empty, + d, ), ], ); - let hide_stepper = - Widgets.toggle(~tooltip="Show Stepper", "s", true, _ => - inject(UpdateAction.ToggleStepper(result_key)) - ); - let show_history = - Widgets.toggle(~tooltip="Show History", "h", settings.stepper_history, _ => - inject(Set(Evaluation(ShowRecord))) - ); - let eval_settings = - Widgets.button(Icons.gear, _ => inject(Set(Evaluation(ShowSettings)))); - - let rec previous_step = - (~hidden=false, step: Stepper.step_with_previous): list(Node.t) => { - [ + let history = Stepper.get_history(~settings, stepper); + switch (history) { + | [] => [] + | [hd, ...tl] => + let button_back = + Widgets.button_d( + Icons.undo, + inject(UpdateAction.StepperAction(result_key, StepBackward)), + ~disabled=!Stepper.can_undo(~settings, stepper), + ~tooltip="Step Backwards", + ); + let button_hide_stepper = + Widgets.toggle(~tooltip="Show Stepper", "s", true, _ => + inject(UpdateAction.ToggleStepper(result_key)) + ); + let toggle_show_history = + Widgets.toggle(~tooltip="Show History", "h", settings.stepper_history, _ => + inject(Set(Evaluation(ShowRecord))) + ); + let eval_settings = + Widgets.button(Icons.gear, _ => + inject(Set(Evaluation(ShowSettings))) + ); + let current = div( - ~attr= - Attr.classes( - ["cell-item", "cell-result"] @ (hidden ? ["hidden"] : []), - ), - [ - div(~attr=Attr.class_("equiv"), [Node.text("≡")]), - dh_code_previous(step), - div( - ~attr=Attr.classes(["stepper-justification"]), - [ - Node.text( - Stepper.get_justification(step.step.knd) - ++ (hidden ? " (hidden)" : ""), - ), - ], - ), - ], - ), - ] - @ ( - ( + ~attrs=[Attr.classes(["cell-item", "cell-result"])], + read_only + ? [ + div(~attrs=[Attr.class_("equiv")], [Node.text("≡")]), + step_dh_code(~next_steps=[], hd), + ] + : [ + div(~attrs=[Attr.class_("equiv")], [Node.text("≡")]), + step_dh_code( + ~next_steps= + List.mapi( + (i, x: EvaluatorStep.EvalObj.t) => + (i, x.d_loc |> DHExp.rep_id), + Stepper.get_next_steps(stepper), + ), + hd, + ), + button_back, + eval_settings, + toggle_show_history, + button_hide_stepper, + ], + ); + let dh_code_previous = step_dh_code; + let rec previous_step = + (~hidden: bool, step: Stepper.step_info): list(Node.t) => { + let hidden_steps = settings.show_hidden_steps - ? List.map( - step => - {step, previous: None, hidden: []} - |> previous_step(~hidden=true), - step.hidden, - ) - : [] - ) - |> List.flatten - ); - }; - let dh_code_current = d => - div( - ~attr=Attr.classes(["result"]), + ? Stepper.hidden_steps_of_info(step) + |> List.rev_map(previous_step(~hidden=true)) + |> List.flatten + : []; [ - DHCode.view( - ~inject, - ~settings, - ~selected_hole_instance=None, - ~font_metrics, - ~width=80, - ~previous_step= - previous - |> List.nth_opt(_, 0) - |> Option.map((x: Stepper.step_with_previous) => x.step), - ~next_steps=Stepper.get_next_steps(stepper) |> List.map(snd), - ~hidden_steps=hidden, - ~result_key, - d, + div( + ~attrs=[ + Attr.classes( + ["cell-item", "cell-result"] @ (hidden ? ["hidden"] : []), + ), + ], + [ + div(~attrs=[Attr.class_("equiv")], [Node.text("≡")]), + dh_code_previous(~next_steps=[], step), + div( + ~attrs=[Attr.classes(["stepper-justification"])], + step.chosen_step + |> Option.map((chosen_step: EvaluatorStep.step) => + chosen_step.knd |> Stepper.get_justification |> Node.text + ) + |> Option.to_list, + ), + ], ), - ], - ); - - let current = + ] + @ hidden_steps; + }; ( ( - settings.show_hidden_steps - ? List.map( - step => - {step, previous: None, hidden: []} - |> previous_step(~hidden=true), - hidden, - ) + settings.stepper_history + ? List.map(previous_step(~hidden=false), tl) + |> List.flatten + |> List.rev_append( + _, + settings.show_hidden_steps + ? hd + |> Stepper.hidden_steps_of_info + |> List.map(previous_step(~hidden=true)) + |> List.flatten + : [], + ) : [] ) - |> List.flatten - |> List.rev + @ [current] ) - @ [ - switch (stepper.current) { - | StepperOK(d, _) => - div( - ~attr=Attr.classes(["cell-item", "cell-result"]), - [ - div(~attr=Attr.class_("equiv"), [Node.text("≡")]), - dh_code_current(d), - button_back, - eval_settings, - show_history, - hide_stepper, - ], - ) - // TODO[Matt]: show errors and waiting - | StepTimeout - | StepPending(_, _, _) => div([]) - }, - ]; - let nodes_previous = List.map(previous_step, previous) |> List.flatten; - List.fold_left((x, y) => List.cons(y, x), current, nodes_previous) - @ (settings.show_settings ? settings_modal(~inject, settings) : []); + @ (settings.show_settings ? settings_modal(~inject, settings) : []); + }; }; diff --git a/src/haz3lweb/view/TestView.re b/src/haz3lweb/view/TestView.re index 81cc608411..1b01158c56 100644 --- a/src/haz3lweb/view/TestView.re +++ b/src/haz3lweb/view/TestView.re @@ -8,10 +8,15 @@ module TestResults = Haz3lcore.TestResults; module Interface = Haz3lcore.Interface; let test_instance_view = - (~settings, ~inject, ~font_metrics, (d, status): TestMap.instance_report) => + ( + ~settings, + ~inject, + ~font_metrics, + ~infomap, + (d, status): TestMap.instance_report, + ) => div( - ~attr= - Attr.many([clss(["test-instance", TestStatus.to_string(status)])]), + ~attrs=[clss(["test-instance", TestStatus.to_string(status)])], [ DHCode.view( ~inject, @@ -20,6 +25,7 @@ let test_instance_view = ~font_metrics, ~width=40, ~result_key="", + ~infomap, d, ), ], @@ -37,27 +43,27 @@ let test_report_view = ~inject, ~font_metrics, ~description: option(string)=None, + ~infomap, i: int, (id, instance_reports): TestMap.report, ) => { let status = instance_reports |> TestMap.joint_status |> TestStatus.to_string; div( - ~attr= - Attr.many([ - Attr.class_("test-report"), - Attr.on_click(jump_to_test(~inject, YourTestsTesting, id)), - ]), + ~attrs=[ + Attr.class_("test-report"), + Attr.on_click(jump_to_test(~inject, YourTestsTesting, id)), + ], [ div( - ~attr=clss(["test-id", "Test" ++ status]), + ~attrs=[clss(["test-id", "Test" ++ status])], // note: prints lexical index, not id [text(string_of_int(i + 1))], ), div( - ~attr=Attr.class_("test-instances"), + ~attrs=[Attr.class_("test-instances")], List.map( - test_instance_view(~settings, ~inject, ~font_metrics), + test_instance_view(~infomap, ~settings, ~inject, ~font_metrics), instance_reports, ), ), @@ -65,16 +71,22 @@ let test_report_view = @ ( switch (description) { | None => [] - | Some(d) => [div(~attr=clss(["test-description"]), [text(d)])] + | Some(d) => [div(~attrs=[clss(["test-description"])], [text(d)])] } ), ); }; let test_reports_view = - (~settings, ~inject, ~font_metrics, ~test_results: option(TestResults.t)) => + ( + ~settings, + ~inject, + ~font_metrics, + ~infomap, + ~test_results: option(TestResults.t), + ) => div( - ~attr=clss(["panel-body", "test-reports"]), + ~attrs=[clss(["panel-body", "test-reports"])], switch (test_results) { | None => [Node.text("No test report available.")] | Some(test_results) => @@ -84,6 +96,7 @@ let test_reports_view = ~settings, ~inject, ~font_metrics, + ~infomap, ~description=List.nth_opt(test_results.descriptions, i), i, r, @@ -96,18 +109,17 @@ let test_reports_view = let test_bar_segment = (~inject, pos, (id, reports)) => { let status = reports |> TestMap.joint_status |> TestStatus.to_string; div( - ~attr= - Attr.many([ - clss(["segment", status]), - Attr.on_click(jump_to_test(~inject, pos, id)), - ]), + ~attrs=[ + clss(["segment", status]), + Attr.on_click(jump_to_test(~inject, pos, id)), + ], [], ); }; let test_bar = (~inject, ~test_results: TestResults.t, pos) => div( - ~attr=Attr.class_("test-bar"), + ~attrs=[Attr.class_("test-bar")], List.map(test_bar_segment(~inject, pos), test_results.test_map), ); @@ -117,7 +129,7 @@ let percent_view = (n: int, p: int): Node.t => { let percentage = n == 0 ? 100. : 100. *. float_of_int(p) /. float_of_int(n); div( - ~attr=clss(["test-percent", n == p ? "all-pass" : "some-fail"]), + ~attrs=[clss(["test-percent", n == p ? "all-pass" : "some-fail"])], [text(Printf.sprintf("%.0f%%", percentage))], ); }; @@ -127,7 +139,7 @@ let test_percentage = (test_results: TestResults.t): Node.t => let test_text = (test_results: TestResults.t): Node.t => div( - ~attr=Attr.class_("test-text"), + ~attrs=[Attr.class_("test-text")], [ test_percentage(test_results), div([text(":")]), @@ -137,7 +149,7 @@ let test_text = (test_results: TestResults.t): Node.t => let test_summary = (~inject, ~test_results: option(TestResults.t)) => { div( - ~attr=clss(["test-summary"]), + ~attrs=[clss(["test-summary"])], { switch (test_results) { | None => [Node.text("No test results available.")] @@ -152,7 +164,7 @@ let test_summary = (~inject, ~test_results: option(TestResults.t)) => { let view_of_main_title_bar = (title_text: string) => div( - ~attr=Attr.many([clss(["title-bar", "panel-title-bar"])]), + ~attrs=[clss(["title-bar", "panel-title-bar"])], [Node.text(title_text)], ); @@ -162,6 +174,7 @@ let inspector_view = ~inject, ~font_metrics, ~test_map: TestMap.t, + ~infomap, id: Haz3lcore.Id.t, ) : option(t) => { @@ -169,12 +182,12 @@ let inspector_view = | Some(instances) when TestMap.joint_status(instances) != Indet => Some( div( - ~attr=Attr.class_("test-inspector"), + ~attrs=[Attr.class_("test-inspector")], [ div( - ~attr=Attr.class_("test-instances"), + ~attrs=[Attr.class_("test-instances")], List.map( - test_instance_view(~settings, ~inject, ~font_metrics), + test_instance_view(~settings, ~inject, ~font_metrics, ~infomap), instances, ), ), diff --git a/src/haz3lweb/view/Type.re b/src/haz3lweb/view/Type.re index bcc190ced5..2b399a033f 100644 --- a/src/haz3lweb/view/Type.re +++ b/src/haz3lweb/view/Type.re @@ -3,31 +3,29 @@ open Node; open Util.Web; open Haz3lcore; +let tpat_view = (tpat: Haz3lcore.TPat.t): string => + switch (tpat.term) { + | Var(x) => x + | _ => "?" + }; + let ty_view = (cls: string, s: string): Node.t => - div(~attr=clss(["typ-view", cls]), [text(s)]); + div(~attrs=[clss(["typ-view", cls])], [text(s)]); let alias_view = (s: string): Node.t => - div(~attr=clss(["typ-alias-view"]), [text(s)]); - -let prov_view: Typ.type_provenance => Node.t = - fun - | Internal => div([]) - | Free(name) => - div(~attr=clss(["typ-mod", "free-type-var"]), [text(name)]) - | TypeHole => div(~attr=clss(["typ-mod", "type-hole"]), [text("𝜏")]) - | SynSwitch => div(~attr=clss(["typ-mod", "syn-switch"]), [text("⇒")]); + div(~attrs=[clss(["typ-alias-view"])], [text(s)]); let rec view_ty = (~strip_outer_parens=false, ty: Haz3lcore.Typ.t): Node.t => - switch (ty) { + switch (Typ.term_of(ty)) { | Unknown(prov) => div( - ~attr= - Attr.many([ - clss(["typ-view", "atom", "unknown"]), - Attr.title(Typ.show_type_provenance(prov)), - ]), + ~attrs=[ + clss(["typ-view", "atom", "unknown"]), + Attr.title(Typ.show_type_provenance(prov)), + ], [text("?") /*, prov_view(prov)*/], ) + | Parens(ty) => view_ty(ty) | Int => ty_view("Int", "Int") | Float => ty_view("Float", "Float") | String => ty_view("String", "String") @@ -35,30 +33,30 @@ let rec view_ty = (~strip_outer_parens=false, ty: Haz3lcore.Typ.t): Node.t => | Var(name) => ty_view("Var", name) | Rec(name, t) => div( - ~attr=clss(["typ-view", "Rec"]), - [text("rec " ++ name ++ " -> "), view_ty(t)], + ~attrs=[clss(["typ-view", "Rec"])], + [text("Rec " ++ tpat_view(name) ++ ". "), view_ty(t)], ) | Forall(name, t) => div( - ~attr=clss(["typ-view", "Forall"]), - [text("forall " ++ name ++ " -> "), view_ty(t)], + ~attrs=[clss(["typ-view", "Forall"])], + [text("forall " ++ tpat_view(name) ++ " -> "), view_ty(t)], ) | List(t) => div( - ~attr=clss(["typ-view", "atom", "List"]), + ~attrs=[clss(["typ-view", "atom", "List"])], [text("["), view_ty(t), text("]")], ) | Arrow(t1, t2) => div( - ~attr=clss(["typ-view", "Arrow"]), + ~attrs=[clss(["typ-view", "Arrow"])], paren_view(t1) @ [text(" -> "), view_ty(t2)], ) - | Prod([]) => div(~attr=clss(["typ-view", "Prod"]), [text("()")]) + | Prod([]) => div(~attrs=[clss(["typ-view", "Prod"])], [text("()")]) | Prod([_]) => - div(~attr=clss(["typ-view", "Prod"]), [text("Singleton Product")]) + div(~attrs=[clss(["typ-view", "Prod"])], [text("Singleton Product")]) | Prod([t0, ...ts]) => div( - ~attr=clss(["typ-view", "atom", "Prod"]), + ~attrs=[clss(["typ-view", "atom", "Prod"])], ( if (!strip_outer_parens) { [text("(")]; @@ -68,7 +66,7 @@ let rec view_ty = (~strip_outer_parens=false, ty: Haz3lcore.Typ.t): Node.t => ) @ [ div( - ~attr=clss(["typ-view", "Prod"]), + ~attrs=[clss(["typ-view", "Prod"])], paren_view(t0) @ ( List.map(t => [text(", "), ...paren_view(t)], ts) @@ -130,7 +128,7 @@ let rec view_ty = (~strip_outer_parens=false, ty: Haz3lcore.Typ.t): Node.t => ); | Sum(ts) => div( - ~attr=clss(["typ-view", "Sum"]), + ~attrs=[clss(["typ-view", "Sum"])], switch (ts) { | [] => [text("Nullary Sum")] | [t0] => [text("+")] @ ctr_view(t0) @@ -141,16 +139,25 @@ let rec view_ty = (~strip_outer_parens=false, ty: Haz3lcore.Typ.t): Node.t => }, ) | Member(name, _) => ty_view("Member", name) + | Ap(_) => + div( + ~attrs=[ + clss(["typ-view", "atom", "unknown"]), + Attr.title(Typ.show_type_provenance(Internal)), + ], + [text("?") /*, prov_view(prov)*/], + ) } -and ctr_view = ((ctr, typ)) => - switch (typ) { - | None => [text(ctr)] - | Some(typ) => [ +and ctr_view = + fun + | Variant(ctr, _, None) => [text(ctr)] + | Variant(ctr, _, Some(typ)) => [ text(ctr ++ "("), - view_ty(~strip_outer_parens=true, typ), + view_ty(typ), text(")"), ] - } + | BadEntry(typ) => [view_ty(typ)] + and paren_view = typ => if (Typ.needs_parens(typ)) { [text("("), view_ty(~strip_outer_parens=true, typ), text(")")]; @@ -159,4 +166,4 @@ and paren_view = typ => }; let view = (ty: Haz3lcore.Typ.t): Node.t => - div_c("typ-wrapper", [view_ty(ty)]); + div(~attrs=[clss(["type", "code"])], [view_ty(ty)]); diff --git a/src/haz3lweb/view/Widgets.re b/src/haz3lweb/view/Widgets.re index 72522f6e82..f9e590f235 100644 --- a/src/haz3lweb/view/Widgets.re +++ b/src/haz3lweb/view/Widgets.re @@ -4,41 +4,36 @@ open Util.Web; let button = (~tooltip="", icon, action) => div( - ~attr= - Attr.many([ - clss(["icon"]), - Attr.on_mousedown(action), - Attr.title(tooltip), - ]), + ~attrs=[ + clss(["icon"]), + Attr.on_mousedown(action), + Attr.title(tooltip), + ], [icon], ); let button_named = (~tooltip="", icon, action) => div( - ~attr=Attr.many([clss(["named-menu-item"]), Attr.on_click(action)]), + ~attrs=[clss(["named-menu-item"]), Attr.on_click(action)], [button(icon, _ => Effect.Ignore), div([text(tooltip)])], ); let button_d = (~tooltip="", icon, action, ~disabled: bool) => div( - ~attr= - Attr.many([ - clss(["icon"] @ (disabled ? ["disabled"] : [])), - Attr.title(tooltip), - Attr.on_mousedown(_ => unless(disabled, action)), - ]), + ~attrs=[ + clss(["icon"] @ (disabled ? ["disabled"] : [])), + Attr.title(tooltip), + Attr.on_mousedown(_ => unless(disabled, action)), + ], [icon], ); let link = (~tooltip="", icon, url) => div( - ~attr=clss(["icon"]), + ~attrs=[clss(["icon"])], [ a( - ~attr= - Attr.many( - Attr.[href(url), title(tooltip), create("target", "_blank")], - ), + ~attrs=Attr.[href(url), title(tooltip), create("target", "_blank")], [icon], ), ], @@ -46,29 +41,27 @@ let link = (~tooltip="", icon, url) => let toggle = (~tooltip="", label, active, action) => div( - ~attr= - Attr.many([ - clss(["toggle-switch"] @ (active ? ["active"] : [])), - Attr.on_click(action), - Attr.title(tooltip), - ]), - [div(~attr=clss(["toggle-knob"]), [text(label)])], + ~attrs=[ + clss(["toggle-switch"] @ (active ? ["active"] : [])), + Attr.on_click(action), + Attr.title(tooltip), + ], + [div(~attrs=[clss(["toggle-knob"])], [text(label)])], ); let toggle_named = (~tooltip="", icon, active, action) => div( - ~attr= - Attr.many([ - clss(["named-menu-item"] @ (active ? ["active"] : [])), - Attr.on_click(action), - ]), + ~attrs=[ + clss(["named-menu-item"] @ (active ? ["active"] : [])), + Attr.on_click(action), + ], [toggle(icon, active, _ => Effect.Ignore), div([text(tooltip)])], ); let file_select_button = (~tooltip="", id, icon, on_input) => { /* https://stackoverflow.com/questions/572768/styling-an-input-type-file-button */ label( - ~attr=Attr.for_(id), + ~attrs=[Attr.for_(id)], [ Vdom_input_widgets.File_select.single( ~extra_attrs=[Attr.class_("file-select-button"), Attr.id(id)], @@ -76,13 +69,13 @@ let file_select_button = (~tooltip="", id, icon, on_input) => { ~on_input, (), ), - div(~attr=Attr.many([clss(["icon"]), Attr.title(tooltip)]), [icon]), + div(~attrs=[clss(["icon"]), Attr.title(tooltip)], [icon]), ], ); }; let file_select_button_named = (~tooltip="", id, icon, on_input) => div( - ~attr=Attr.many([clss(["named-menu-item"])]), + ~attrs=[clss(["named-menu-item"])], [file_select_button(id, icon, on_input), div([text(tooltip)])], ); diff --git a/src/haz3lweb/view/assistant/UpdateAssistant.re b/src/haz3lweb/view/assistant/UpdateAssistant.re deleted file mode 100644 index 3370ab03f6..0000000000 --- a/src/haz3lweb/view/assistant/UpdateAssistant.re +++ /dev/null @@ -1,97 +0,0 @@ -open Haz3lcore; -include UpdateAction; - -/* NOTE: this is duplicated from Update */ -let perform_action = (model: Model.t, a: Action.t): Result.t(Model.t) => { - let ed_init = Editors.get_editor(model.editors); - switch (Haz3lcore.Perform.go(~settings=model.settings.core, a, ed_init)) { - | Error(err) => Error(FailedToPerform(err)) - | Ok(ed) => Ok({...model, editors: Editors.put_editor(ed, model.editors)}) - }; -}; - -let reset_buffer = (model: Model.t) => { - let ed = model.editors |> Editors.get_editor; - let z = ed.state.zipper; - switch (z.selection.mode) { - | Buffer(_) => - switch (Perform.go_z(~settings=model.settings.core, Destruct(Left), z)) { - | Error(_) => model - | Ok(z) => - let ed = Editor.new_state(Destruct(Left), z, ed); - //TODO(andrew): fix double action - {...model, editors: Editors.put_editor(ed, model.editors)}; - } - | _ => model - }; -}; - -let apply = - ( - {settings, _} as model: Model.t, - update: agent_action, - ~schedule_action, - ~state, - ~main, - ) - : Result.t(Model.t) => { - let editor = model.editors |> Editors.get_editor; - let z = editor.state.zipper; - switch (update) { - | Prompt(TyDi) => - let ctx_init = Editors.get_ctx_init(~settings, model.editors); - switch (TyDi.set_buffer(~settings=settings.core, ~ctx=ctx_init, z)) { - | None => Ok(model) - | Some(z) => - let ed = Editor.new_state(Pick_up, z, editor); - //TODO: add correct action to history (Pick_up is wrong) - let editors = Editors.put_editor(ed, model.editors); - Ok({...model, editors}); - }; - | AcceptSuggestion => - print_endline("accepting suggestion"); - let trim = AssistantExpander.trim; - switch (z.selection.mode) { - | Normal => Ok(model) - | Buffer(Parsed) => perform_action(model, Unselect(Some(Right))) - | Buffer(Unparsed) => - switch (TyDi.get_buffer(z)) { - | None => Ok(model) - /* This case shouldn't happen if we assume that we prevalidate - * everything we put in the unparsed buffer*/ - | Some(completion) when String.contains(completion, ' ') => - /* Slightly hacky. We assume that if a completion string has - * spaces in it, that means it will have a hole in it. This - * is a non-essential invariant currently maintained in TyDi. - * In such a case, we insert the completion as normal by - * pasting, then return to the beginning and advance to the - * first hole. This should be revisited if completions are - * refactored to use a more structured buffer format */ - module M = (val Editor.Meta.module_of_t(editor.state.meta)); - let start = Zipper.caret_point(M.measured, z); - let rec do_actions = (model, actions: list(UpdateAction.t)) => - switch (actions) { - | [] => Ok(model) - | [hd, ...tl] => - switch (main(model, hd, state, ~schedule_action)) { - | Error(err) => Error(err) - | Ok(model) => do_actions(model, tl) - } - }; - /* TODO(andrew): use zipper-level actions here to avoid - * measured recomputation at editor-level */ - do_actions( - model, - [ - Paste(trim(completion)), - PerformAction(Move(Goal(Point(start)))), - PerformAction(MoveToNextHole(Right)), - PerformAction(Move(Local(Left(ByToken)))), - ], - ); - | Some(completion) => - main(model, Paste(trim(completion)), state, ~schedule_action) - } - }; - }; -}; diff --git a/src/haz3lweb/view/dec/CaretDec.re b/src/haz3lweb/view/dec/CaretDec.re index 04fd7b8002..2e7e1f5a1d 100644 --- a/src/haz3lweb/view/dec/CaretDec.re +++ b/src/haz3lweb/view/dec/CaretDec.re @@ -1,56 +1,26 @@ open Util; -open SvgUtil; - -let caret_width_straight = 0.1; -let caret_width_bent = 0.1; -let caret_bend = DecUtil.tip_width; module Profile = { type t = { side: Direction.t, - origin: Haz3lcore.Measured.Point.t, + origin: Point.t, shape: option(Direction.t), }; }; -let caret_path = (shape: option(Direction.t)) => { - let caret_bend_param = - switch (shape) { - | Some(Right) => -. caret_bend - | Some(Left) => caret_bend - | None => 0.0 - }; - let caret_width_param = - switch (shape) { - | Some(Right) => -. caret_width_bent - | Some(Left) => caret_width_bent - | None => caret_width_straight - }; - Path.[ - m(~x=0, ~y=0), - H({x: caret_width_param}), - L_({dx: -. caret_bend_param, dy: 0.5}), - L_({dx: +. caret_bend_param, dy: 0.5}), - H({x: -. caret_width_param}), - L_({dx: -. caret_bend_param, dy: (-0.5)}), - L_({dx: +. caret_bend_param, dy: (-0.5)}), - ]; -}; - let view = ( ~font_metrics: FontMetrics.t, ~profile as {shape, side, origin}: Profile.t, ) => { - let l_adj = DecUtil.caret_adjust(side, shape); DecUtil.code_svg( ~font_metrics, ~origin, ~id="caret", ~base_cls=["blink"], ~path_cls=["caret-path"], - ~height_fudge=DecUtil.shadow_adj *. font_metrics.row_height, - ~left_fudge=l_adj *. font_metrics.col_width, - caret_path(shape), + /* Make caret as tall as shard + shard's shadow */ + ~height_fudge=DecUtil.shadow_dy *. font_metrics.row_height, + DecUtil.caret_base_path(side, shape), ); }; diff --git a/src/haz3lweb/view/dec/CaretPosDec.re b/src/haz3lweb/view/dec/CaretPosDec.re index 60f0a6420c..d270f27f4c 100644 --- a/src/haz3lweb/view/dec/CaretPosDec.re +++ b/src/haz3lweb/view/dec/CaretPosDec.re @@ -1,11 +1,10 @@ open Virtual_dom.Vdom; module Profile = { - type style = [ | `Bare | `Sibling | `Anchor | `Caret]; + type style = [ | `Sibling]; type t = { style, measurement: Haz3lcore.Measured.measurement, - sort: Haz3lcore.Sort.t, }; }; @@ -13,46 +12,32 @@ let caret_position_radii = (~font_metrics: FontMetrics.t, ~style: Profile.style) => { let r = switch (style) { - | `Caret => 3.75 - | `Anchor | `Sibling => 2.75 - | `Bare => 2.0 }; (r /. font_metrics.col_width, r /. font_metrics.row_height); }; -let view = (~font_metrics, {style, sort, measurement}: Profile.t) => { +let view = (~font_metrics, {style, measurement}: Profile.t) => { let (r_x, r_y) = caret_position_radii(~font_metrics, ~style); - let c_cls = Haz3lcore.Sort.to_string(sort); - let cls = - switch (style) { - | `Bare => "outer-cousin" - | `Caret => "current-caret-pos" - | `Anchor => "anchor" - | `Sibling => "sibling" - }; Node.create_svg( "svg", - ~attr= - Attr.many([ - Attr.class_(cls), - DecUtil.abs_position(~font_metrics, measurement.origin), - Attr.create("viewBox", Printf.sprintf("0 0 1 1")), - Attr.create("preserveAspectRatio", "none"), - ]), + ~attrs=[ + Attr.class_("backpack-target"), + DecUtil.abs_position(~font_metrics, measurement.origin), + Attr.create("viewBox", Printf.sprintf("0 0 1 1")), + Attr.create("preserveAspectRatio", "none"), + ], [ Node.create_svg( "rect", - ~attr= - Attr.many( - Attr.[ - create("x", Printf.sprintf("%fpx", -. r_x)), - create("y", Printf.sprintf("%fpx", 0.1 -. r_y)), - create("width", Printf.sprintf("%fpx", 1. *. r_x)), - create("height", Printf.sprintf("%fpx", 1. *. r_y)), - Attr.classes(["caret-position-path", cls, c_cls]), - ], - ), + ~attrs= + Attr.[ + create("x", Printf.sprintf("%fpx", -. r_x)), + create("y", Printf.sprintf("%fpx", 0.1 -. r_y)), + create("width", Printf.sprintf("%fpx", 1. *. r_x)), + create("height", Printf.sprintf("%fpx", 1. *. r_y)), + Attr.classes(["caret-position-path"]), + ], [], ), ], diff --git a/src/haz3lweb/view/dec/DecUtil.re b/src/haz3lweb/view/dec/DecUtil.re index c34c727aef..d4d3492946 100644 --- a/src/haz3lweb/view/dec/DecUtil.re +++ b/src/haz3lweb/view/dec/DecUtil.re @@ -2,38 +2,87 @@ open Virtual_dom.Vdom; open Node; open Util; -let tip_width = 0.32; -let concave_adj = 0.25; -let convex_adj = (-0.13); -let shadow_adj = 0.015; - -let caret_adjust = (side: Direction.t, shape: option(Direction.t)) => - switch (side, shape) { - | (_, None) => 0. - | (Left, Some(Left)) => concave_adj - | (Right, Some(Right)) => -. concave_adj - | (Left, Some(Right)) => convex_adj - | (Right, Some(Left)) => -. convex_adj - }; +let caret_width = 0.2; -let child_border_thickness = 0.05; +let tip_width = 0.32; +let concave_offset = 0.8 *. 0.32; /* Tuned parameter */ +let convex_offset = 0.6 *. 0.32; /* Tuned parameter */ +let shadow_dy = 0.037; +let shadow_dx = 0.08; +let child_border_thickness = 0.; //0.05; +let shadow_adj = shadow_dy /. 2.; let t = child_border_thickness /. 0.5; +let short_tip_width = (1. -. t) *. tip_width; let short_tip_height = (1. -. t) *. 0.5; -let stretch_dx = 0.15; +let shape_adjust = (d1: Direction.t, d2: Direction.t): float => + switch (d1, d2) { + | (Left, Left) => -. convex_offset + | (Right, Right) => convex_offset + | (Left, Right) => concave_offset + | (Right, Left) => -. concave_offset + }; + +let shape_adjust = (side: Direction.t, shape: option(Direction.t)) => + switch (shape) { + | None => 0. + | Some(d2) => shape_adjust(side, d2) + }; + +let caret_run = (shape: option(Direction.t)) => + switch (shape) { + | None => 0. + | Some(Left) => +. tip_width + | Some(Right) => -. tip_width + }; -let raised_shadow_dx = "0.1"; -let raised_shadow_dy = "0.037"; -let shadow_dx = raised_shadow_dx; -let shadow_dy = raised_shadow_dy; +let chevronf = (run: float, rise: float): list(SvgUtil.Path.cmd) => + SvgUtil.Path.[L_({dx: -. run, dy: rise}), L_({dx: +. run, dy: rise})]; + +let chevron = (direction: option(Direction.t), drawing_from: Direction.t) => + chevronf(caret_run(direction), drawing_from == Left ? (-0.5) : 0.5); + +let chonky_shard_path_base = + ((l, r), x_offset, length: float, height: float): list(SvgUtil.Path.cmd) => { + List.flatten( + SvgUtil.Path.[ + [M({x: -. x_offset, y: 0.}), H_({dx: length}), V({y: height})], + chevron(r, Right), + [H_({dx: -. length}), v(~y=1)], + chevron(l, Left), + ], + ); +}; + +let caret_base_path = (side, shape): list(SvgUtil.Path.cmd) => + chonky_shard_path_base( + (shape, shape), + shape_adjust(side, shape) +. 0.5 *. caret_width, + caret_width, + float_of_int(0), + ); + +let shard_length = (length, d_l, d_r) => + float_of_int(length) + +. shape_adjust(Left, d_l) + -. shape_adjust(Right, d_r); + +let shard_offset = d_l => shape_adjust(Left, d_l); + +let shard_path = + ((d_l, d_r), length: int, height: int): list(SvgUtil.Path.cmd) => + chonky_shard_path_base( + (d_l, d_r), + shard_offset(d_l), + shard_length(length, d_l, d_r), + float_of_int(height), + ); let extra_tail = 0.; let jagged_edge_h = child_border_thickness /. 3.; let jagged_edge_w = child_border_thickness /. 1.; -let short_tip_width = (1. -. t) *. tip_width; - type dims = { width: int, height: int, @@ -59,30 +108,39 @@ let pos_str = (~d: dims, ~fudge: fdims=fzero, font_metrics: FontMetrics.t) => Float.of_int(d.height) *. (font_metrics.row_height +. fudge.height), ); +let abs_dims = ({origin, last}: Haz3lcore.Measured.measurement): dims => { + left: origin.col, + top: origin.row, + width: abs(last.col - origin.col), + height: abs(last.row - origin.row + 1), +}; + +let abs_style = (~font_metrics, ~fudge: fdims=fzero, measurement): Attr.t => + Attr.create( + "style", + pos_str(~d=abs_dims(measurement), ~fudge, font_metrics), + ); + let code_svg_sized = ( ~font_metrics: FontMetrics.t, - ~measurement as {origin, last}: Haz3lcore.Measured.measurement, + ~absolute=true, + ~measurement: Haz3lcore.Measured.measurement, ~base_cls=[], ~path_cls=[], ~fudge: fdims=fzero, paths: list(SvgUtil.Path.cmd), ) => { - let (left, top) = (origin.col, origin.row); - let (width, height) = ( - abs(last.col - origin.col), - abs(last.row - origin.row + 1), - ); - let style = pos_str(~d={left, top, width, height}, ~fudge, font_metrics); + let d = abs_dims(measurement); + let d = absolute ? d : {left: 0, top: 0, width: d.width, height: d.height}; create_svg( "svg", - ~attr= - Attr.many([ - Attr.classes(base_cls), - Attr.create("style", style), - Attr.create("viewBox", Printf.sprintf("0 0 %d %d", width, height)), - Attr.create("preserveAspectRatio", "none"), - ]), + ~attrs=[ + Attr.classes(base_cls), + Attr.create("style", pos_str(~d, ~fudge, font_metrics)), + Attr.create("viewBox", Printf.sprintf("0 0 %d %d", d.width, d.height)), + Attr.create("preserveAspectRatio", "none"), + ], [SvgUtil.Path.view(~attrs=[Attr.classes(path_cls)], paths)], ); }; @@ -96,7 +154,7 @@ let position = ~height_fudge=0.0, ~scale=1., ~font_metrics: FontMetrics.t, - origin: Haz3lcore.Measured.Point.t, + origin: Point.t, ) => Attr.create( "style", @@ -119,7 +177,7 @@ let abs_position = ~height_fudge=0.0, ~scale=1., ~font_metrics: FontMetrics.t, - origin: Haz3lcore.Measured.Point.t, + origin: Point.t, ) => { position( ~style="position: absolute", @@ -136,7 +194,7 @@ let abs_position = let code_svg = ( ~font_metrics: FontMetrics.t, - ~origin: Haz3lcore.Measured.Point.t, + ~origin: Point.t, ~base_cls=[], ~path_cls=[], ~left_fudge=0.0, @@ -152,87 +210,64 @@ let code_svg = // (https://bugs.chromium.org/p/chromium/issues/detail?id=424288) that // causes miaslignment between piece decorations and text. // Using a different viewBox size seems to fix this. - let scale = 2.; + let scale = 0.5; create_svg( "svg", - ~attr= - Attr.many( - (id == "" ? [] : [Attr.id(id)]) - @ [ - Attr.classes(base_cls), - abs_pos - ? abs_position( - ~font_metrics, - ~left_fudge, - ~top_fudge, - ~width_fudge, - ~height_fudge, - ~scale, - origin, - ) - : position( - ~font_metrics, - ~left_fudge, - ~top_fudge, - ~width_fudge, - ~height_fudge, - ~scale, - origin, - ), - Attr.create("viewBox", Printf.sprintf("0 0 %f %f", scale, scale)), - Attr.create("preserveAspectRatio", "none"), - ] - @ attrs, - ), + ~attrs= + (id == "" ? [] : [Attr.id(id)]) + @ [ + Attr.classes(base_cls), + abs_pos + ? abs_position( + ~font_metrics, + ~left_fudge, + ~top_fudge, + ~width_fudge, + ~height_fudge, + ~scale, + origin, + ) + : position( + ~font_metrics, + ~left_fudge, + ~top_fudge, + ~width_fudge, + ~height_fudge, + ~scale, + origin, + ), + Attr.create("viewBox", Printf.sprintf("0 0 %f %f", scale, scale)), + Attr.create("preserveAspectRatio", "none"), + ] + @ attrs, [SvgUtil.Path.view(~attrs=[Attr.classes(path_cls)], paths)], ); }; -let raised_shadow_filter = (sort: Haz3lcore.Sort.t) => { +let drop_shadow_filter = (sort: Haz3lcore.Sort.t) => { let s = Haz3lcore.Sort.to_string(sort); create_svg( "filter", - ~attr=Attr.id("raised-drop-shadow-" ++ s), + ~attrs=[Attr.id("drop-shadow-" ++ s)], [ create_svg( "feDropShadow", - ~attr= - Attr.many([ - Attr.classes(["tile-drop-shadow"]), - Attr.create("dx", raised_shadow_dx), - Attr.create("dy", raised_shadow_dy), - Attr.create("stdDeviation", "0"), - ]), + ~attrs=[ + Attr.classes(["tile-drop-shadow"]), + Attr.create("dx", Printf.sprintf("%.3f", shadow_dx)), + Attr.create("dy", Printf.sprintf("%.3f", shadow_dy)), + Attr.create("stdDeviation", "0"), + ], [], ), ], ); }; -let shadow_filter = (sort: Haz3lcore.Sort.t) => { - let s = Haz3lcore.Sort.to_string(sort); - create_svg( - "filter", - ~attr=Attr.id("drop-shadow-" ++ s), - [ - create_svg( - "feDropShadow", - ~attr= - Attr.many([ - Attr.classes(["tile-drop-shadow"]), - Attr.create("dx", shadow_dx), - Attr.create("dy", shadow_dy), - Attr.create("stdDeviation", "0"), - ]), - [], - ), - ], - ); -}; +let svg = (attrs, children) => Node.create_svg("svg", ~attrs, children); let filters = - NodeUtil.svg( + svg( Attr.[id("filters")], - List.map(raised_shadow_filter, Haz3lcore.Sort.all) - @ List.map(shadow_filter, Haz3lcore.Sort.all), + List.map(drop_shadow_filter, Haz3lcore.Sort.all), ); diff --git a/src/haz3lweb/view/dec/Diag.re b/src/haz3lweb/view/dec/Diag.re index 6c52ab23de..a145c9d0e9 100644 --- a/src/haz3lweb/view/dec/Diag.re +++ b/src/haz3lweb/view/dec/Diag.re @@ -1,6 +1,6 @@ open DecUtil; open SvgUtil.Path; -open Sexplib.Std; +open Util; //TODO(?): deprecate this module @@ -18,24 +18,22 @@ let tr_bl = (), ) => SvgUtil.Path.( - { - let (diag, junction) = - with_child_border - ? ( - L_({dx: Float.neg(short_tip_width), dy: short_tip_height}), - H_({dx: Float.neg(0.5 -. short_tip_width)}), - ) - : ( - L_({dx: Float.neg(tip_width), dy: 0.5 +. stretch_y}), - H_({dx: Float.neg(stretch_x)}), - ); - let path = - switch (hemi) { - | `North => [junction, diag] - | `South => [diag, junction] - }; - scale(s, path); - } + let (diag, junction) = + with_child_border + ? ( + L_({dx: Float.neg(short_tip_width), dy: short_tip_height}), + H_({dx: Float.neg(0.5 -. short_tip_width)}), + ) + : ( + L_({dx: Float.neg(tip_width), dy: 0.5 +. stretch_y}), + H_({dx: Float.neg(stretch_x)}), + ); + let path = + switch (hemi) { + | `North => [junction, diag] + | `South => [diag, junction] + }; + scale(s, path) ); // bottom left to top right let bl_tr = @@ -60,18 +58,16 @@ let tl_br = (), ) => SvgUtil.Path.( - { - let (diag, junction) = - with_child_border - ? ( - L_({dx: short_tip_width, dy: short_tip_height}), - H_({dx: 0.5 -. short_tip_width}), - ) - : (L_({dx: tip_width, dy: 0.5 +. stretch_y}), H_({dx: stretch_x})); - switch (hemi) { - | `North => [junction, diag] - | `South => [diag, junction] - }; + let (diag, junction) = + with_child_border + ? ( + L_({dx: short_tip_width, dy: short_tip_height}), + H_({dx: 0.5 -. short_tip_width}), + ) + : (L_({dx: tip_width, dy: 0.5 +. stretch_y}), H_({dx: stretch_x})); + switch (hemi) { + | `North => [junction, diag] + | `South => [diag, junction] } ); // bottom right to top left diff --git a/src/haz3lweb/view/dec/PieceDec.re b/src/haz3lweb/view/dec/PieceDec.re index 92d0ac54fc..4dc9465520 100644 --- a/src/haz3lweb/view/dec/PieceDec.re +++ b/src/haz3lweb/view/dec/PieceDec.re @@ -4,109 +4,99 @@ open Virtual_dom.Vdom; open Node; open SvgUtil; -let run: Nib.Shape.t => float = - fun - | Convex => +. DecUtil.short_tip_width - | Concave(_) => -. DecUtil.short_tip_width; +type tip = option(Nib.Shape.t); -let adj: Nib.Shape.t => float = - fun - | Convex => DecUtil.convex_adj - | Concave(_) => DecUtil.concave_adj; - -let l_hook = (l: Nib.Shape.t): list(Path.cmd) => [ - H_({dx: -. adj(l)}), - L_({dx: -. run(l), dy: (-0.5)}), - L_({dx: +. run(l), dy: (-0.5)}), - H_({dx: +. adj(l)}), -]; - -let r_hook = (r: Nib.Shape.t): list(Path.cmd) => [ - H_({dx: +. adj(r)}), - L_({dx: +. run(r), dy: 0.5}), - L_({dx: -. run(r), dy: 0.5}), - H_({dx: -. adj(r)}), -]; - -let simple_shard_path = ((l, r): Nibs.shapes, length: int): list(Path.cmd) => - List.flatten( - Path.[ - [m(~x=0, ~y=0), h(~x=length)], - r_hook(r), - [h(~x=0)], - l_hook(l), - ], - ); +type shard_dims = { + font_metrics: FontMetrics.t, + measurement: Measured.measurement, + tips: (option(Nib.Shape.t), option(Nib.Shape.t)), +}; let simple_shard = ( - ~font_metrics, - ~shapes, - ~path_cls, - ~base_cls, - ~fudge=DecUtil.fzero, - measurement: Measured.measurement, + {font_metrics, tips: (l, r), measurement}: shard_dims, + ~absolute=true, + classes, ) : t => DecUtil.code_svg_sized( ~font_metrics, ~measurement, - ~base_cls, - ~path_cls, - ~fudge, - simple_shard_path(shapes, measurement.last.col - measurement.origin.col), + ~base_cls=["shard"] @ classes, + ~path_cls=[], + ~absolute, + DecUtil.shard_path( + ( + Option.map(Nib.Shape.direction_of(Left), l), + Option.map(Nib.Shape.direction_of(Right), r), + ), + measurement.last.col - measurement.origin.col, + measurement.last.row - measurement.origin.row, + ), ); -let simple_shard_selected = - (~font_metrics, ~shapes, ~measurement: Measured.measurement, ~buffer): t => { - let path_cls = [ - "tile-path", - "raised", - buffer ? "selected-buffer" : "selected", - ]; - let base_cls = ["tile-selected"]; +let relative_shard = (shard_dims: shard_dims) => + simple_shard(~absolute=false, shard_dims, []); + +let tips_of_shapes = ((l, r): (Nib.Shape.t, Nib.Shape.t)): (tip, tip) => ( + Some(l), + Some(r), +); + +let simple_shard_indicated = (shard_dims, ~sort: Sort.t, ~at_caret: bool): t => simple_shard( - /* Increase height slightly to avoid leaving spaces between selected lines */ - ~fudge={height: 0.3, top: 0., width: 0., left: 0.}, - ~font_metrics, - ~shapes, - ~path_cls, - ~base_cls, - measurement, + shard_dims, + ["indicated", Sort.to_string(sort)] @ (at_caret ? ["caret"] : []), ); -}; - -let simple_shard_indicated = - ( - ~font_metrics, - ~has_caret, - ~shapes, - ~sort, - ~measurement: Measured.measurement, - ) - : t => { - let path_cls = - ["tile-path", "raised", Sort.to_string(sort)] - @ (has_caret ? ["indicated-caret"] : ["indicated"]); - let base_cls = ["tile-indicated"]; - simple_shard(~font_metrics, ~shapes, ~path_cls, ~base_cls, measurement); -}; let simple_shards_indicated = - (~font_metrics: FontMetrics.t, ~caret: (Id.t, int), (id, mold, shards)) + (~font_metrics: FontMetrics.t, (id, mold, shards), ~caret: (Id.t, int)) : list(t) => List.map( ((index, measurement)) => simple_shard_indicated( - ~font_metrics, - ~has_caret=caret == (id, index), - ~shapes=Mold.nib_shapes(~index, mold), + { + font_metrics, + measurement, + tips: tips_of_shapes(Mold.nib_shapes(~index, mold)), + }, ~sort=mold.out, - ~measurement, + ~at_caret=caret == (id, index), + ), + shards, + ); + +let simple_shard_selected = (shard_dims, buffer): t => + simple_shard(shard_dims, ["selected"] @ (buffer ? ["buffer"] : [])); + +let simple_shards_selected = + (~font_metrics: FontMetrics.t, mold, buffer, shards) => + List.map( + ((index, measurement)) => + simple_shard_selected( + { + font_metrics, + measurement, + tips: tips_of_shapes(Mold.nib_shapes(~index, mold)), + }, + buffer, ), shards, ); +let simple_shard_error = simple_shard(_, ["error"]); + +let simple_shards_errors = (~font_metrics: FontMetrics.t, mold, shards) => + List.map( + ((index, measurement)) => + simple_shard_error({ + font_metrics, + measurement, + tips: tips_of_shapes(Mold.nib_shapes(~index, mold)), + }), + shards, + ); + let shadowfudge = Path.cmdfudge(~y=DecUtil.shadow_adj); let shards_of_tiles = tiles => @@ -117,6 +107,17 @@ let shards_of_tiles = tiles => Measured.Point.compare(m1.origin, m2.origin) ); +let rep_tips = (tiles: list((Id.t, Mold.t, Measured.Shards.t))) => { + assert(tiles != []); + let (_, rep_mold, _) = List.hd(tiles); + let (l, r) = rep_mold.nibs; + let (l, r) = tips_of_shapes((l.shape, r.shape)); + ( + Option.map(Nib.Shape.direction_of(Left), l), + Option.map(Nib.Shape.direction_of(Right), r), + ); +}; + let bi_lines = ( ~font_metrics: FontMetrics.t, @@ -124,37 +125,48 @@ let bi_lines = tiles: list((Id.t, Mold.t, Measured.Shards.t)), ) : list(t) => { + let (dl, dr) = rep_tips(tiles); let shards = shards_of_tiles(tiles); let shard_rows = Measured.Shards.split_by_row(shards); let intra_lines = shard_rows |> List.map(ListUtil.neighbors) |> List.concat_map( - List.map( - (((_, l: Measured.measurement), (_, r: Measured.measurement))) => + List.mapi( + ( + i, + ((_, l: Measured.measurement), (_, r: Measured.measurement)), + ) => { + let offset = i == 0 ? -. DecUtil.shard_offset(dl) : 0.; + let length = + i == 0 + ? DecUtil.shard_length(r.origin.col - l.origin.col, dl, dr) + +. 0.2 + : float_of_int(r.origin.col - l.origin.col) +. 0.2; ( l.origin, SvgUtil.Path.[ - shadowfudge(m(~x=0, ~y=1)), - h(~x=r.last.col - l.origin.col), + shadowfudge(M({x: offset, y: 1.0})), + H({x: length}), ], - ) - ), + ); + }), ); let inter_lines = ListUtil.neighbors(shard_rows) - |> List.map( - ((row_shards: Measured.Shards.t, row_shards': Measured.Shards.t)) => { + |> List.mapi( + (i, (row_shards: Measured.Shards.t, row_shards': Measured.Shards.t)) => { assert(row_shards != []); assert(row_shards' != []); let origin = snd(List.hd(row_shards)).origin; let origin' = snd(List.hd(row_shards')).origin; let indent = Measured.Rows.find(origin.row, rows).indent; let v_delta = origin'.col == indent ? (-1) : 0; + let offset = i == 0 ? -. DecUtil.shard_offset(dl) : 0.; ( origin, SvgUtil.Path.[ - shadowfudge(m(~x=0, ~y=1)), + shadowfudge(M({x: offset, y: 1.0})), h_(~dx=indent - origin.col), shadowfudge(v_(~dy=origin'.row - origin.row + v_delta)), h_(~dx=origin'.col - indent), @@ -184,6 +196,10 @@ let uni_lines = ) => { open SvgUtil.Path; let shards = shards_of_tiles(tiles); + let (dl, _) = rep_tips(tiles); + let offset = -. DecUtil.shard_offset(dl); + let hook_dx = DecUtil.short_tip_width /. 2.; + let hook_dy = DecUtil.short_tip_height /. 4.; let l_line = { let (_, m_first) = List.hd(shards); let (_, m_last_of_first) = { @@ -206,16 +222,9 @@ let uni_lines = ? ( m_first.origin, [ - shadowfudge(m(~x=0, ~y=1)), + shadowfudge(M({x: 0., y: 1.0})), h(~x=l.col - m_first.origin.col), - L_({ - dx: -. DecUtil.short_tip_width, - dy: -. DecUtil.short_tip_height /. 2. //hack - }), - //L_({ - // dx: DecUtil.short_tip_width, - // dy: -. DecUtil.short_tip_height, - //}), + L_({dx: -. hook_dx, dy: -. hook_dy}), ], ) : ( @@ -229,7 +238,7 @@ let uni_lines = shadowfudge(v(~y=l.row - m_last_of_first.origin.row)), ] : [ - shadowfudge(m(~x=0, ~y=1)), + shadowfudge(M({x: offset, y: 1.0})), h(~x=indent - m_first.origin.col), shadowfudge(v(~y=l.row + 1 - m_first.origin.row)), h(~x=max_col - m_first.origin.col), @@ -238,11 +247,7 @@ let uni_lines = ) @ [ h(~x=l.col - m_first.origin.col), - L_({ - dx: -. DecUtil.short_tip_width, - dy: DecUtil.short_tip_height /. 2. //hack - }), - //L_({dx: DecUtil.short_tip_width, dy: DecUtil.short_tip_height}), + L_({dx: -. hook_dx, dy: hook_dy}), ], ), ]; @@ -252,13 +257,7 @@ let uni_lines = }; let r_line = { let (_, m_last) = ListUtil.last(shards); - let hook = [ - L_({ - dx: DecUtil.short_tip_width, - dy: -. DecUtil.short_tip_height /. 2. //hack - }), - //L_({dx: -. DecUtil.short_tip_width, dy: -. DecUtil.short_tip_height}), - ]; + let hook = [L_({dx: hook_dx, dy: -. hook_dy})]; if (r.row == m_last.last.row && r.col > m_last.last.col) { [ ( @@ -282,7 +281,6 @@ let uni_lines = rows, ) |> min(m_last.last.col); - // let r_indent = Measured.Rows.find(r.row, rows).indent; let (_, m_flast) = { let shard_rows = Measured.Shards.split_by_row(shards); assert(shard_rows != []); @@ -290,13 +288,15 @@ let uni_lines = assert(row != []); List.hd(row); }; - // let flast_indent = Measured.Rows.find(m_flast.origin.row, rows).indent; [ ( m_flast.origin, [ shadowfudge( - m(~x=0, ~y=m_flast.last.row - m_flast.origin.row + 1), + M({ + x: offset, + y: float_of_int(m_flast.last.row - m_flast.origin.row + 1), + }), ), h(~x=min_col - m_flast.origin.col), shadowfudge(v(~y=r.row - m_flast.origin.row + 1)), diff --git a/src/haz3lweb/view/dhcode/DHCode.re b/src/haz3lweb/view/dhcode/DHCode.re index 8b777976e4..b28f9e18bf 100644 --- a/src/haz3lweb/view/dhcode/DHCode.re +++ b/src/haz3lweb/view/dhcode/DHCode.re @@ -4,7 +4,7 @@ open Util; open Pretty; open Haz3lcore; -let with_cls = cls => Node.span(~attr=Attr.classes([cls])); +let with_cls = cls => Node.span(~attrs=[Attr.classes([cls])]); let view_of_layout = (~inject, ~font_metrics: FontMetrics.t, ~result_key, l: DHLayout.t) @@ -17,7 +17,7 @@ let view_of_layout = ~text=(_, s) => ([Node.text(s)], []), ~align= (_, (txt, ds)) => - ([Node.div(~attr=Attr.classes(["Align"]), txt)], ds), + ([Node.div(~attrs=[Attr.classes(["Align"])], txt)], ds), ~cat=(_, (txt1, ds1), (txt2, ds2)) => (txt1 @ txt2, ds1 @ ds2), ~annot= (~go, ~indent, ~start, annot: DHAnnot.t, m) => { @@ -26,36 +26,28 @@ let view_of_layout = | Steppable(obj) => ( [ Node.span( - ~attr= - Attr.many([ - Attr.class_("steppable"), - Attr.on_click(_ => - inject( - UpdateAction.StepperAction( - result_key, - StepForward(obj), - ), - ) - ), - ]), + ~attrs=[ + Attr.class_("steppable"), + Attr.on_click(_ => + inject( + UpdateAction.StepperAction( + result_key, + StepForward(obj), + ), + ) + ), + ], txt, ), ], ds, ) | Stepped => ( - [ - Node.span(~attr=Attr.many([Attr.class_("stepped")]), txt), - ], + [Node.span(~attrs=[Attr.class_("stepped")], txt)], ds, ) | Substituted => ( - [ - Node.span( - ~attr=Attr.many([Attr.class_("substituted")]), - txt, - ), - ], + [Node.span(~attrs=[Attr.class_("substituted")], txt)], ds, ) | Step(_) @@ -66,19 +58,18 @@ let view_of_layout = | EmptyHole(selected, _inst) => ( [ Node.span( - ~attr= - Attr.many([ - Attr.classes([ - "EmptyHole", - ...selected ? ["selected"] : [], - ]), - Attr.on_click(_ => - Vdom.Effect.Many([ - Vdom.Effect.Stop_propagation, - //inject(ModelAction.SelectHoleInstance(inst)), - ]) - ), + ~attrs=[ + Attr.classes([ + "EmptyHole", + ...selected ? ["selected"] : [], ]), + Attr.on_click(_ => + Vdom.Effect.Many([ + Vdom.Effect.Stop_propagation, + //inject(ModelAction.SelectHoleInstance(inst)), + ]) + ), + ], txt, ), ], @@ -105,12 +96,9 @@ let view_of_layout = ds, ) | VarHole(_) => ([with_cls("InVarHole", txt)], ds) - | Invalid((_, (-666))) => - /* Evaluation and Elaboration exceptions */ - ([with_cls("exception", txt)], ds) - | NonEmptyHole(_) + | NonEmptyHole | InconsistentBranches(_) - | Invalid(_) => + | Invalid => let offset = start.col - indent; let decoration = Decoration_common.container( @@ -127,7 +115,7 @@ let view_of_layout = }, ); Node.div( - ~attr=Attr.classes(["DHCode"]), + ~attrs=[Attr.classes(["DHCode"])], [with_cls("code", text), ...decorations], ); }; @@ -137,15 +125,16 @@ let view = ~locked as _=false, // NOTE: When we add mouse events to this, ignore them if locked ~inject, ~settings: CoreSettings.Evaluation.t, - ~selected_hole_instance: option(HoleInstance.t), + ~selected_hole_instance: option(Id.t), ~font_metrics: FontMetrics.t, ~width: int, ~pos=0, - ~previous_step: option(EvaluatorStep.step)=None, // The step that will be displayed above this one - ~hidden_steps: list(EvaluatorStep.step)=[], // The hidden steps between the above and the current one + ~previous_step: option((EvaluatorStep.step, Id.t))=None, // The step that will be displayed above this one + ~hidden_steps: list((EvaluatorStep.step, Id.t))=[], // The hidden steps between the above and the current one ~chosen_step: option(EvaluatorStep.step)=None, // The step that will be taken next - ~next_steps: list(EvaluatorStep.EvalObj.t)=[], + ~next_steps: list((int, Id.t))=[], ~result_key: string, + ~infomap, d: DHExp.t, ) : Node.t => { @@ -158,6 +147,7 @@ let view = ~settings, ~enforce_inline=false, ~selected_hole_instance, + ~infomap, d, ) |> LayoutOfDoc.layout_of_doc(~width, ~pos) diff --git a/src/haz3lweb/view/dhcode/Decoration_common.re b/src/haz3lweb/view/dhcode/Decoration_common.re index b56135d99d..2be3d88be8 100644 --- a/src/haz3lweb/view/dhcode/Decoration_common.re +++ b/src/haz3lweb/view/dhcode/Decoration_common.re @@ -39,59 +39,53 @@ let container = switch (container_type) { | Div => Node.div( - ~attr= - Attr.many([ - Attr.classes([ - "decoration-container", - Printf.sprintf("%s-container", cls), - ]), - Attr.create( - "style", - Printf.sprintf( - "width: %fpx; height: %fpx;", - buffered_width_px, - buffered_height_px, - ), - ), + ~attrs=[ + Attr.classes([ + "decoration-container", + Printf.sprintf("%s-container", cls), ]), + Attr.create( + "style", + Printf.sprintf( + "width: %fpx; height: %fpx;", + buffered_width_px, + buffered_height_px, + ), + ), + ], contents, ) | Svg => Node.create_svg( "svg", - ~attr= - Attr.many([ - Attr.classes([cls]), - Attr.create( - "viewBox", - Printf.sprintf("0 0 %d %d", buffered_width, buffered_height), - ), - Attr.create("width", Printf.sprintf("%fpx", buffered_width_px)), - Attr.create( - "height", - Printf.sprintf("%fpx", buffered_height_px), - ), - Attr.create("preserveAspectRatio", "none"), - ]), + ~attrs=[ + Attr.classes([cls]), + Attr.create( + "viewBox", + Printf.sprintf("0 0 %d %d", buffered_width, buffered_height), + ), + Attr.create("width", Printf.sprintf("%fpx", buffered_width_px)), + Attr.create("height", Printf.sprintf("%fpx", buffered_height_px)), + Attr.create("preserveAspectRatio", "none"), + ], contents, ) }; Node.div( - ~attr= - Attr.many([ - Attr.classes([ - "decoration-container", - Printf.sprintf("%s-container", cls), - ]), - Attr.create( - "style", - Printf.sprintf( - "top: calc(%fpx); left: %fpx;", - container_origin_x, - container_origin_y, - ), - ), + ~attrs=[ + Attr.classes([ + "decoration-container", + Printf.sprintf("%s-container", cls), ]), + Attr.create( + "style", + Printf.sprintf( + "top: calc(%fpx); left: %fpx;", + container_origin_x, + container_origin_y, + ), + ), + ], [inner], ); }; diff --git a/src/haz3lweb/view/dhcode/layout/DHAnnot.re b/src/haz3lweb/view/dhcode/layout/DHAnnot.re index d754529f87..2b351315d3 100644 --- a/src/haz3lweb/view/dhcode/layout/DHAnnot.re +++ b/src/haz3lweb/view/dhcode/layout/DHAnnot.re @@ -1,4 +1,4 @@ -open Sexplib.Std; +open Util; open Haz3lcore; [@deriving sexp] @@ -8,11 +8,11 @@ type t = | Term | HoleLabel | Delim - | EmptyHole(bool, HoleInstance.t) - | NonEmptyHole(ErrStatus.HoleReason.t, HoleInstance.t) - | VarHole(VarErrStatus.HoleReason.t, HoleInstance.t) - | InconsistentBranches(HoleInstance.t) - | Invalid(HoleInstance.t) + | EmptyHole(bool, ClosureEnvironment.t) + | NonEmptyHole + | VarHole(VarErrStatus.HoleReason.t, Id.t) + | InconsistentBranches(Id.t) + | Invalid | FailedCastDelim | FailedCastDecoration | CastDecoration diff --git a/src/haz3lweb/view/dhcode/layout/DHDoc_Exp.re b/src/haz3lweb/view/dhcode/layout/DHDoc_Exp.re index cc119ebdf0..d0ddb64685 100644 --- a/src/haz3lweb/view/dhcode/layout/DHDoc_Exp.re +++ b/src/haz3lweb/view/dhcode/layout/DHDoc_Exp.re @@ -3,13 +3,13 @@ open EvaluatorStep; open Transition; module Doc = Pretty.Doc; -let precedence_bin_bool_op = (op: TermBase.UExp.op_bin_bool) => +let precedence_bin_bool_op = (op: Operators.op_bin_bool) => switch (op) { | And => DHDoc_common.precedence_And | Or => DHDoc_common.precedence_Or }; -let precedence_bin_int_op = (bio: TermBase.UExp.op_bin_int) => +let precedence_bin_int_op = (bio: Operators.op_bin_int) => switch (bio) { | Times => DHDoc_common.precedence_Times | Power => DHDoc_common.precedence_Power @@ -23,7 +23,7 @@ let precedence_bin_int_op = (bio: TermBase.UExp.op_bin_int) => | GreaterThan => DHDoc_common.precedence_GreaterThan | GreaterThanOrEqual => DHDoc_common.precedence_GreaterThan }; -let precedence_bin_float_op = (bfo: TermBase.UExp.op_bin_float) => +let precedence_bin_float_op = (bfo: Operators.op_bin_float) => switch (bfo) { | Times => DHDoc_common.precedence_Times | Power => DHDoc_common.precedence_Power @@ -37,124 +37,135 @@ let precedence_bin_float_op = (bfo: TermBase.UExp.op_bin_float) => | GreaterThan => DHDoc_common.precedence_GreaterThan | GreaterThanOrEqual => DHDoc_common.precedence_GreaterThan }; -let precedence_bin_string_op = (bso: TermBase.UExp.op_bin_string) => +let precedence_bin_string_op = (bso: Operators.op_bin_string) => switch (bso) { | Concat => DHDoc_common.precedence_Plus | Equals => DHDoc_common.precedence_Equals }; -let rec precedence = (~show_casts: bool, d: DHExp.t) => { - let precedence' = precedence(~show_casts); - switch (d) { - | BoundVar(_) - | FreeVar(_) - | InvalidText(_) - | BoolLit(_) - | IntLit(_) - | Sequence(_) +let rec precedence = (~show_function_bodies, ~show_casts: bool, d: DHExp.t) => { + let precedence' = precedence(~show_function_bodies, ~show_casts); + switch (DHExp.term_of(d)) { + | Var(_) + | Invalid(_) + | Bool(_) + | Int(_) + | Seq(_) | Test(_) - | FloatLit(_) - | StringLit(_) + | Float(_) + | String(_) | ListLit(_) - | Prj(_) - | EmptyHole(_) + | EmptyHole | Constructor(_) | FailedCast(_) - | InvalidOperation(_) - | IfThenElse(_) | ModuleVal(_) + | DynamicErrorHole(_) + | If(_) + | Closure(_) | BuiltinFun(_) - | Filter(_) - | Closure(_) => DHDoc_common.precedence_const + | Deferral(_) + | Undefined + | Filter(_) => DHDoc_common.precedence_const | Cast(d1, _, _) => - show_casts ? DHDoc_common.precedence_const : precedence'(d1) + show_casts ? DHDoc_common.precedence_Ap : precedence'(d1) + | DeferredAp(_) | Ap(_) | TypAp(_) => DHDoc_common.precedence_Ap - | ApBuiltin(_) => DHDoc_common.precedence_Ap | Dot(_) => DHDoc_common.precedence_Ap | Cons(_) => DHDoc_common.precedence_Cons | ListConcat(_) => DHDoc_common.precedence_Plus | Tuple(_) => DHDoc_common.precedence_Comma | TypFun(_) + | Fun(_) when !show_function_bodies => DHDoc_common.precedence_const + | TypFun(_) | Fun(_) => DHDoc_common.precedence_max | Let(_) | Module(_) + | TyAlias(_) | FixF(_) - | ConsistentCase(_) - | InconsistentBranches(_) => DHDoc_common.precedence_max - - | BinBoolOp(op, _, _) => precedence_bin_bool_op(op) - | BinIntOp(op, _, _) => precedence_bin_int_op(op) - | BinFloatOp(op, _, _) => precedence_bin_float_op(op) - | BinStringOp(op, _, _) => precedence_bin_string_op(op) - - | NonEmptyHole(_, _, _, d) => precedence'(d) + | Match(_) => DHDoc_common.precedence_max + | UnOp(Meta(Unquote), _) => DHDoc_common.precedence_Ap + | UnOp(Bool(Not), _) => DHDoc_common.precedence_Not + | UnOp(Int(Minus), _) => DHDoc_common.precedence_Minus + | BinOp(Bool(op), _, _) => precedence_bin_bool_op(op) + | BinOp(Int(op), _, _) => precedence_bin_int_op(op) + | BinOp(Float(op), _, _) => precedence_bin_float_op(op) + | BinOp(String(op), _, _) => precedence_bin_string_op(op) + | MultiHole(_) => DHDoc_common.precedence_max + | Parens(d) => precedence'(d) }; }; -let mk_bin_bool_op = (op: TermBase.UExp.op_bin_bool): DHDoc.t => - Doc.text(TermBase.UExp.bool_op_to_string(op)); +let mk_bin_bool_op = (op: Operators.op_bin_bool): DHDoc.t => + Doc.text(Operators.bool_op_to_string(op)); -let mk_bin_int_op = (op: TermBase.UExp.op_bin_int): DHDoc.t => - Doc.text(TermBase.UExp.int_op_to_string(op)); +let mk_bin_int_op = (op: Operators.op_bin_int): DHDoc.t => + Doc.text(Operators.int_op_to_string(op)); -let mk_bin_float_op = (op: TermBase.UExp.op_bin_float): DHDoc.t => - Doc.text(TermBase.UExp.float_op_to_string(op)); +let mk_bin_float_op = (op: Operators.op_bin_float): DHDoc.t => + Doc.text(Operators.float_op_to_string(op)); -let mk_bin_string_op = (op: TermBase.UExp.op_bin_string): DHDoc.t => - Doc.text(TermBase.UExp.string_op_to_string(op)); +let mk_bin_string_op = (op: Operators.op_bin_string): DHDoc.t => + Doc.text(Operators.string_op_to_string(op)); let mk = ( ~settings: CoreSettings.Evaluation.t, ~enforce_inline: bool, - ~selected_hole_instance: option(HoleInstance.t), + ~selected_hole_instance: option(Id.t), // The next four are used when drawing the stepper to track where we can annotate changes - ~previous_step: option(step), // The step that will be displayed above this one - ~hidden_steps: list(step), // The hidden steps between the above and the current one + ~previous_step: option((step, Id.t)), // The step that will be displayed above this one (an Id in included because it may have changed since the step was taken) + ~hidden_steps: list((step, Id.t)), // The hidden steps between the above and the current one (an Id in included because it may have changed since the step was taken) ~chosen_step: option(step), // The step that will be taken next - ~next_steps: list(EvalObj.t), // The options for the next step, if it hasn't been chosen yet + ~next_steps: list((int, Id.t)), // The options for the next step, if it hasn't been chosen yet ~env: ClosureEnvironment.t, + ~infomap: Statics.Map.t, d: DHExp.t, ) : DHDoc.t => { - let precedence = precedence(~show_casts=settings.show_casts); + let precedence = + precedence( + ~show_casts=settings.show_casts, + ~show_function_bodies=settings.show_fn_bodies, + ); let rec go = ( d: DHExp.t, env: ClosureEnvironment.t, enforce_inline: bool, - previous_step: option(step), - hidden_steps: list(step), - chosen_step: option(step), - next_steps: list((EvalCtx.t, int)), recent_subst: list(Var.t), ) : DHDoc.t => { open Doc; let recent_subst = switch (previous_step) { - | Some(ps) when ps.ctx == Mark => - switch (ps.knd, ps.d_loc) { - | (FunAp, Ap(Fun(p, _, _, _), _)) => DHPat.bound_vars(p) + | Some((ps, id)) when id == DHExp.rep_id(d) => + switch (ps.knd, DHExp.term_of(ps.d_loc)) { + | (FunAp, Ap(_, d2, _)) => + switch (DHExp.term_of(d2)) { + | Fun(p, _, _, _) => DHPat.bound_vars(p) + | _ => [] + } | (FunAp, _) => [] | (LetBind, Let(p, _, _)) => DHPat.bound_vars(p) | (LetBind, _) => [] | (ModuleBind, Module(p, _, _)) => DHPat.bound_vars(p) | (ModuleBind, _) => [] - | (FixUnwrap, FixF(f, _, _)) => [f] + | (FixUnwrap, FixF(p, _, _)) => DHPat.bound_vars(p) | (FixUnwrap, _) => [] | (TypFunAp, _) // TODO: Could also do something here for type variable substitution like in FunAp? | (InvalidStep, _) | (VarLookup, _) | (ModuleLookup, _) | (DotAccess, _) - | (Sequence, _) + | (Seq, _) | (FunClosure, _) | (FixClosure, _) + | (DeferredAp, _) | (UpdateTest, _) | (CastTypAp, _) | (CastAp, _) | (BuiltinWrap, _) + | (UnOp(_), _) | (BuiltinAp(_), _) | (BinBoolOp(_), _) | (BinIntOp(_), _) @@ -164,57 +175,23 @@ let mk = | (ListCons, _) | (ListConcat, _) | (CaseApply, _) - | (CaseNext, _) | (CompleteClosure, _) | (CompleteFilter, _) | (Cast, _) | (Conditional(_), _) - | (Skip, _) => [] + | (RemoveParens, _) + | (RemoveTypeAlias, _) => [] // Maybe this last one could count as a substitution? } | _ => recent_subst }; - let substitution = - hidden_steps - |> List.find_opt(step => - step.knd == VarLookup - // HACK[Matt]: to prevent substitutions hiding inside casts - && EvalCtx.fuzzy_mark(step.ctx) - ); - let next_recent_subst = - switch (substitution) { - | Some({d_loc: BoundVar(v), _}) => - List.filter(u => u != v, recent_subst) - | _ => recent_subst - }; let go' = ( ~env=env, ~enforce_inline=enforce_inline, - ~recent_subst=next_recent_subst, + ~recent_subst=recent_subst, d, - ctx, ) => { - go( - d, - env, - enforce_inline, - Option.join( - Option.map(EvaluatorStep.unwrap(_, ctx), previous_step), - ), - hidden_steps - |> List.filter(s => !EvalCtx.fuzzy_mark(s.ctx)) - |> List.filter_map(EvaluatorStep.unwrap(_, ctx)), - Option.join(Option.map(EvaluatorStep.unwrap(_, ctx), chosen_step)), - List.filter_map( - ((x, y)) => - switch (EvalCtx.unwrap(x, ctx)) { - | None => None - | Some(x') => Some((x', y)) - }, - next_steps, - ), - recent_subst, - ); + go(d, env, enforce_inline, recent_subst); }; let parenthesize = (b, doc) => if (b) { @@ -226,29 +203,21 @@ let mk = } else { doc(~enforce_inline); }; - let go_case_rule = - (consistent: bool, rule_idx: int, Rule(dp, dclause): DHExp.rule) - : DHDoc.t => { - let kind: EvalCtx.cls = - if (consistent) { - ConsistentCaseRule(rule_idx); - } else { - InconsistentBranchesRule(rule_idx); - }; + let go_case_rule = ((dp, dclause)): DHDoc.t => { let hidden_clause = annot(DHAnnot.Collapsed, text(Unicode.ellipsis)); let clause_doc = settings.show_case_clauses ? choices([ - hcats([space(), go'(~enforce_inline=true, dclause, kind)]), + hcats([space(), go'(~enforce_inline=true, dclause)]), hcats([ linebreak(), - indent_and_align(go'(~enforce_inline=false, dclause, kind)), + indent_and_align(go'(~enforce_inline=false, dclause)), ]), ]) : hcat(space(), hidden_clause); hcats([ DHDoc_common.Delim.bar_Rule, - DHDoc_Pat.mk(dp) + DHDoc_Pat.mk(~infomap, ~show_casts=settings.show_casts, dp) |> DHDoc_common.pad_child( ~inline_padding=(space(), space()), ~enforce_inline=false, @@ -257,46 +226,45 @@ let mk = clause_doc, ]); }; - let go_case = (dscrut, drs, consistent) => + let go_case = (dscrut, drs) => if (enforce_inline) { fail(); } else { - let kind: EvalCtx.cls = - if (consistent) {ConsistentCase} else {InconsistentBranches}; let scrut_doc = choices([ - hcats([space(), go'(~enforce_inline=true, dscrut, kind)]), + hcats([space(), go'(~enforce_inline=true, dscrut)]), hcats([ linebreak(), - indent_and_align(go'(~enforce_inline=false, dscrut, kind)), + indent_and_align(go'(~enforce_inline=false, dscrut)), ]), ]); vseps( List.concat([ [hcat(DHDoc_common.Delim.open_Case, scrut_doc)], - drs |> List.mapi(go_case_rule(consistent)), + drs |> List.map(go_case_rule), [DHDoc_common.Delim.close_Case], ]), ); }; let go_formattable = (~enforce_inline) => go'(~enforce_inline); - let mk_left_associative_operands = (precedence_op, (d1, l), (d2, r)) => ( - go_formattable(d1, l) |> parenthesize(precedence(d1) > precedence_op), - go_formattable(d2, r) |> parenthesize(precedence(d2) >= precedence_op), + let mk_left_associative_operands = (precedence_op, d1, d2) => ( + go_formattable(d1) |> parenthesize(precedence(d1) > precedence_op), + go_formattable(d2) |> parenthesize(precedence(d2) >= precedence_op), ); - let mk_right_associative_operands = (precedence_op, (d1, l), (d2, r)) => ( - go_formattable(d1, l) |> parenthesize(precedence(d1) >= precedence_op), - go_formattable(d2, r) |> parenthesize(precedence(d2) > precedence_op), + let mk_right_associative_operands = (precedence_op, d1, d2) => ( + go_formattable(d1) |> parenthesize(precedence(d1) >= precedence_op), + go_formattable(d2) |> parenthesize(precedence(d2) > precedence_op), ); let doc = { - switch (d) { - | Closure(env', d') => go'(d', Closure, ~env=env') + switch (DHExp.term_of(d)) { + | Parens(d') => go'(d') + | Closure(env', d') => go'(d', ~env=env') | Filter(flt, d') => if (settings.show_stepper_filters) { switch (flt) { | Filter({pat, act}) => let keyword = FilterAction.string_of_t(act); - let flt_doc = go_formattable(pat, FilterPattern); + let flt_doc = go_formattable(pat); vseps([ hcats([ DHDoc_common.Delim.mk(keyword), @@ -307,75 +275,52 @@ let mk = ), DHDoc_common.Delim.mk("in"), ]), - go'(d', Filter), + go'(d'), ]); | Residue(_, act) => let keyword = FilterAction.string_of_t(act); - vseps([DHDoc_common.Delim.mk(keyword), go'(d', Filter)]); + vseps([DHDoc_common.Delim.mk(keyword), go'(d')]); }; } else { switch (flt) { - | Residue(_) => go'(d', Filter) - | Filter(_) => go'(d', Filter) + | Residue(_) => go'(d') + | Filter(_) => go'(d') }; } /* Hole expressions must appear within a closure in the postprocessed result */ - | EmptyHole(u, i) => - let selected = - switch (selected_hole_instance) { - | None => false - | Some((u', i')) => u == u' && i == i' - }; - DHDoc_common.mk_EmptyHole(~selected, (u, i)); - | NonEmptyHole(reason, u, i, d') => - go'(d', NonEmptyHole) - |> annot(DHAnnot.NonEmptyHole(reason, (u, i))) - | FreeVar(u, i, x) => - text(x) |> annot(DHAnnot.VarHole(Free, (u, i))) - | InvalidText(u, i, t) => DHDoc_common.mk_InvalidText(t, (u, i)) - | InconsistentBranches(u, i, Case(dscrut, drs, _)) => - go_case(dscrut, drs, false) - |> annot(DHAnnot.InconsistentBranches((u, i))) - | BoundVar(x) when settings.show_lookup_steps => text(x) - | BoundVar(x) => + | EmptyHole => + DHDoc_common.mk_EmptyHole( + ~selected=Some(DHExp.rep_id(d)) == selected_hole_instance, + env, + ) + | MultiHole(_ds) => + DHDoc_common.mk_EmptyHole( + ~selected=Some(DHExp.rep_id(d)) == selected_hole_instance, + env, + ) + | Invalid(t) => DHDoc_common.mk_InvalidText(t) + | Var(x) when settings.show_lookup_steps => text(x) + | Var(x) => switch (ClosureEnvironment.lookup(env, x)) { | None => text(x) | Some(d') => if (List.mem(x, recent_subst)) { hcats([ - go'(~env=ClosureEnvironment.empty, BoundVar(x), BoundVar) + go'(~env=ClosureEnvironment.empty, d) |> annot(DHAnnot.Substituted), go'( ~env=ClosureEnvironment.empty, - ~recent_subst=List.filter(u => u != x, next_recent_subst), + ~recent_subst=List.filter(u => u != x, recent_subst), d', - BoundVar, ), ]); } else { - go'(~env=ClosureEnvironment.empty, d', BoundVar); + go'(~env=ClosureEnvironment.empty, d'); } } | BuiltinFun(f) => text(f) - | Constructor(name) => - switch (ClosureEnvironment.lookup(env, name)) { - | None => DHDoc_common.mk_ConstructorLit(name) - | Some(d') => - if (List.mem(name, recent_subst)) { - hcats([ - go'(~env=ClosureEnvironment.empty, BoundVar(name), BoundVar) - |> annot(DHAnnot.Substituted), - go'(~env=ClosureEnvironment.empty, d', BoundVar), - ]); - } else { - go'(~env=ClosureEnvironment.empty, d', BoundVar); - } - } - | BoolLit(b) => DHDoc_common.mk_BoolLit(b) - | IntLit(n) => DHDoc_common.mk_IntLit(n) - | FloatLit(f) => DHDoc_common.mk_FloatLit(f) | ModuleVal(e, names) => if (enforce_inline) { fail(); @@ -403,20 +348,32 @@ let mk = }; DHDoc_common.mk_ModuleVal(List.rev(envlist)); } - | StringLit(s) => DHDoc_common.mk_StringLit(s) - | Test(_, d) => DHDoc_common.mk_Test(go'(d, Test)) - | Sequence(d1, d2) => - let (doc1, doc2) = (go'(d1, Sequence1), go'(d2, Sequence2)); + | Constructor(name, _) => DHDoc_common.mk_ConstructorLit(name) + | Bool(b) => DHDoc_common.mk_BoolLit(b) + | Int(n) => DHDoc_common.mk_IntLit(n) + | Float(f) => DHDoc_common.mk_FloatLit(f) + | String(s) => DHDoc_common.mk_StringLit(s) + | Undefined => DHDoc_common.mk_Undefined() + | Test(d) => DHDoc_common.mk_Test(go'(d)) + | Deferral(_) => text("_") + | Seq(d1, d2) => + let (doc1, doc2) = (go'(d1), go'(d2)); DHDoc_common.mk_Sequence(doc1, doc2); - | ListLit(_, _, _, d_list) => - let ol = d_list |> List.mapi((i, d) => go'(d, ListLit(i))); + | ListLit(d_list) => + let ol = d_list |> List.map(d => go'(d)); DHDoc_common.mk_ListLit(ol); - - | Ap(d1, d2) => + | Ap(Forward, d1, d2) => let (doc1, doc2) = ( - go_formattable(d1, Ap1) + go_formattable(d1) |> parenthesize(precedence(d1) > DHDoc_common.precedence_Ap), - go'(d2, Ap2), + go'(d2), + ); + DHDoc_common.mk_Ap(doc1, doc2); + | DeferredAp(d1, d2) => + let (doc1, doc2) = ( + go_formattable(d1) + |> parenthesize(precedence(d1) > DHDoc_common.precedence_Ap), + go'(Tuple(d2) |> DHExp.fresh), ); DHDoc_common.mk_Ap(doc1, doc2); | Dot(d1, d2) => @@ -424,96 +381,98 @@ let mk = let doc2 = go'(d2, Dot2); DHDoc_common.mk_Dot(doc1, doc2); | TypAp(d1, ty) => - let doc1 = go'(d1, TypAp); + let doc1 = go'(d1); let doc2 = DHDoc_Typ.mk(~enforce_inline=true, ty); DHDoc_common.mk_TypAp(doc1, doc2); - | ApBuiltin(ident, d) => + | Ap(Reverse, d1, d2) => + let (doc1, doc2) = ( + go_formattable(d1) + |> parenthesize(precedence(d1) > DHDoc_common.precedence_Ap), + go'(d2), + ); + DHDoc_common.mk_rev_Ap(doc2, doc1); + | UnOp(Meta(Unquote), d) => DHDoc_common.mk_Ap( - text(ident), - go_formattable(d, ApBuiltin) + text("$"), + go_formattable(d) |> parenthesize(precedence(d) > DHDoc_common.precedence_Ap), ) - | BinIntOp(op, d1, d2) => + | UnOp(Bool(Not), d) => + DHDoc_common.mk_Ap( + text("!"), + go_formattable(d) + |> parenthesize(precedence(d) > DHDoc_common.precedence_Not), + ) + | UnOp(Int(Minus), d) => + DHDoc_common.mk_Ap( + text("-"), + go_formattable(d) + |> parenthesize(precedence(d) > DHDoc_common.precedence_Minus), + ) + | BinOp(Int(op), d1, d2) => // TODO assumes all bin int ops are left associative let (doc1, doc2) = - mk_left_associative_operands( - precedence_bin_int_op(op), - (d1, BinIntOp1), - (d2, BinIntOp2), - ); + mk_left_associative_operands(precedence_bin_int_op(op), d1, d2); hseps([doc1, mk_bin_int_op(op), doc2]); - | BinFloatOp(op, d1, d2) => + | BinOp(Float(op), d1, d2) => // TODO assumes all bin float ops are left associative let (doc1, doc2) = - mk_left_associative_operands( - precedence_bin_float_op(op), - (d1, BinFloatOp1), - (d2, BinFloatOp2), - ); + mk_left_associative_operands(precedence_bin_float_op(op), d1, d2); hseps([doc1, mk_bin_float_op(op), doc2]); - | BinStringOp(op, d1, d2) => + | BinOp(String(op), d1, d2) => // TODO assumes all bin string ops are left associative let (doc1, doc2) = - mk_left_associative_operands( - precedence_bin_string_op(op), - (d1, BinStringOp1), - (d2, BinStringOp2), - ); + mk_left_associative_operands(precedence_bin_string_op(op), d1, d2); hseps([doc1, mk_bin_string_op(op), doc2]); | Cons(d1, d2) => let (doc1, doc2) = - mk_right_associative_operands( - DHDoc_common.precedence_Cons, - (d1, Cons1), - (d2, Cons2), - ); + mk_right_associative_operands(DHDoc_common.precedence_Cons, d1, d2); DHDoc_common.mk_Cons(doc1, doc2); | ListConcat(d1, d2) => let (doc1, doc2) = - mk_right_associative_operands( - DHDoc_common.precedence_Plus, - (d1, ListConcat1), - (d2, ListConcat2), - ); + mk_right_associative_operands(DHDoc_common.precedence_Plus, d1, d2); DHDoc_common.mk_ListConcat(doc1, doc2); - | BinBoolOp(op, d1, d2) => + | BinOp(Bool(op), d1, d2) => let (doc1, doc2) = - mk_right_associative_operands( - precedence_bin_bool_op(op), - (d1, BinBoolOp1), - (d2, BinBoolOp2), - ); + mk_right_associative_operands(precedence_bin_bool_op(op), d1, d2); hseps([doc1, mk_bin_bool_op(op), doc2]); | Tuple([]) => DHDoc_common.Delim.triv - | Tuple(ds) => - DHDoc_common.mk_Tuple(ds |> List.mapi((i, d) => go'(d, Tuple(i)))) - | Prj(d, n) => DHDoc_common.mk_Prj(go'(d, Prj), n) - | ConsistentCase(Case(dscrut, drs, _)) => go_case(dscrut, drs, true) - | Cast(d, _, ty) when settings.show_casts => + | Tuple(ds) => DHDoc_common.mk_Tuple(ds |> List.map(d => go'(d))) + | Match(dscrut, drs) => go_case(dscrut, drs) + | TyAlias(_, _, d) => go'(d) + | Cast(d, t1, t2) when settings.show_casts => // TODO[Matt]: Roll multiple casts into one cast - let doc = go'(d, Cast); + let doc = + go_formattable(d) + |> parenthesize(precedence(d) > DHDoc_common.precedence_Ap); Doc.( hcat( doc, annot( DHAnnot.CastDecoration, - DHDoc_Typ.mk(~enforce_inline=true, ty), + hcats([ + DHDoc_common.Delim.open_Cast, + DHDoc_Typ.mk(~enforce_inline=true, t1), + DHDoc_common.Delim.arrow_Cast, + DHDoc_Typ.mk(~enforce_inline=true, t2), + DHDoc_common.Delim.close_Cast, + ]), ), ) ); | Cast(d, _, _) => - let doc = go'(d, Cast); + let doc = go'(d); doc; | Let(dp, ddef, dbody) => if (enforce_inline) { fail(); } else { let bindings = DHPat.bound_vars(dp); - let def_doc = go_formattable(ddef, Let1); + let def_doc = go_formattable(ddef); vseps([ hcats([ DHDoc_common.Delim.mk("let"), - DHDoc_Pat.mk(dp) + DHDoc_Pat.mk(~infomap, ~show_casts=settings.show_casts, dp) |> DHDoc_common.pad_child( ~inline_padding=(space(), space()), ~enforce_inline, @@ -530,9 +489,8 @@ let mk = ~enforce_inline=false, ~env=ClosureEnvironment.without_keys(bindings, env), ~recent_subst= - List.filter(x => !List.mem(x, bindings), next_recent_subst), + List.filter(x => !List.mem(x, bindings), recent_subst), dbody, - Let2, ), ]); } @@ -570,6 +528,9 @@ let mk = } | FailedCast(Cast(d, ty1, ty2), ty2', ty3) when Typ.eq(ty2, ty2') => let d_doc = go'(d, FailedCastCast); + (); + | FailedCast(d1, ty1, ty3) => + let d_doc = go'(d1); let cast_decoration = hcats([ DHDoc_common.Delim.open_FailedCast, @@ -582,19 +543,16 @@ let mk = ]) |> annot(DHAnnot.FailedCastDecoration); hcats([d_doc, cast_decoration]); - | FailedCast(_d, _ty1, _ty2) => - failwith("unexpected FailedCast without inner cast") - | InvalidOperation(d, err) => - let d_doc = go'(d, InvalidOperation); + | DynamicErrorHole(d, err) => + let d_doc = go'(d); let decoration = Doc.text(InvalidOperationError.err_msg(err)) |> annot(DHAnnot.OperationError(err)); hcats([d_doc, decoration]); - - | IfThenElse(_, c, d1, d2) => - let c_doc = go_formattable(c, IfThenElse1); - let d1_doc = go_formattable(d1, IfThenElse2); - let d2_doc = go_formattable(d2, IfThenElse3); + | If(c, d1, d2) => + let c_doc = go_formattable(c); + let d1_doc = go_formattable(d1); + let d2_doc = go_formattable(d2); hcats([ DHDoc_common.Delim.mk("("), DHDoc_common.Delim.mk("if"), @@ -617,68 +575,86 @@ let mk = ), DHDoc_common.Delim.mk(")"), ]); - | Fun(dp, ty, dbody, s) when settings.show_fn_bodies => - let bindings = DHPat.bound_vars(dp); - let body_doc = - switch (dbody) { - | Closure(env', dbody) => + | Fun(dp, d, Some(env'), s) => + if (settings.show_fn_bodies) { + let bindings = DHPat.bound_vars(dp); + let body_doc = go_formattable( - Closure(env', dbody), + Closure( + ClosureEnvironment.without_keys(Option.to_list(s), env'), + d, + ) + |> DHExp.fresh, ~env= ClosureEnvironment.without_keys( DHPat.bound_vars(dp) @ Option.to_list(s), env, ), ~recent_subst= - List.filter(x => !List.mem(x, bindings), next_recent_subst), - Fun, - ) - | _ => + List.filter(x => !List.mem(x, bindings), recent_subst), + ); + hcats( + [ + DHDoc_common.Delim.sym_Fun, + DHDoc_Pat.mk(~infomap, ~show_casts=settings.show_casts, dp) + |> DHDoc_common.pad_child( + ~inline_padding=(space(), space()), + ~enforce_inline, + ), + ] + @ [ + DHDoc_common.Delim.arrow_Fun, + space(), + body_doc |> DHDoc_common.pad_child(~enforce_inline=false), + ], + ); + } else { + annot( + DHAnnot.Collapsed, + text( + switch (s) { + | None => "" + | Some(name) + when + !settings.show_fixpoints + && String.ends_with(~suffix="+", name) => + "<" ++ String.sub(name, 0, String.length(name) - 1) ++ ">" + | Some(name) => "<" ++ name ++ ">" + }, + ), + ); + } + | Fun(dp, dbody, None, s) => + if (settings.show_fn_bodies) { + let bindings = DHPat.bound_vars(dp); + let body_doc = go_formattable( dbody, ~env=ClosureEnvironment.without_keys(bindings, env), ~recent_subst= - List.filter(x => !List.mem(x, bindings), next_recent_subst), - Fun, - ) - }; - hcats( - [ - DHDoc_common.Delim.sym_Fun, - DHDoc_Pat.mk(dp) - |> DHDoc_common.pad_child( - ~inline_padding=(space(), space()), - ~enforce_inline, - ), - ] - @ ( - settings.show_casts - ? [ - DHDoc_common.Delim.colon_Fun, - space(), - DHDoc_Typ.mk(~enforce_inline=true, ty), - space(), - ] - : [] - ) - @ [ - DHDoc_common.Delim.arrow_Fun, - space(), - body_doc |> DHDoc_common.pad_child(~enforce_inline=false), - ], - ); - | Fun(_, _, _, s) => - let name = + List.filter(x => !List.mem(x, bindings), recent_subst), + ); + hcats( + [ + DHDoc_common.Delim.sym_Fun, + DHDoc_Pat.mk(~infomap, ~show_casts=settings.show_casts, dp) + |> DHDoc_common.pad_child( + ~inline_padding=(space(), space()), + ~enforce_inline, + ), + ] + @ [ + DHDoc_common.Delim.arrow_Fun, + space(), + body_doc |> DHDoc_common.pad_child(~enforce_inline), + ], + ); + } else { switch (s) { - | None => "anon fn" - | Some(name) - when - !settings.show_fixpoints - && String.ends_with(~suffix="+", name) => - String.sub(name, 0, String.length(name) - 1) - | Some(name) => name + | None => annot(DHAnnot.Collapsed, text("")) + | Some(name) => annot(DHAnnot.Collapsed, text("<" ++ name ++ ">")) }; - annot(DHAnnot.Collapsed, text("<" ++ name ++ ">")); + } | TypFun(_tpat, _dbody, s) => /* same display as with Fun but with anon typfn in the nameless case. */ let name = @@ -692,25 +668,24 @@ let mk = | Some(name) => name }; annot(DHAnnot.Collapsed, text("<" ++ name ++ ">")); - | FixF(x, ty, dbody) + | FixF(dp, dbody, _) when settings.show_fn_bodies && settings.show_fixpoints => let doc_body = go_formattable( dbody, - ~env=ClosureEnvironment.without_keys([x], env), - FixF, + ~env=ClosureEnvironment.without_keys(DHPat.bound_vars(dp), env), ); hcats( - [DHDoc_common.Delim.fix_FixF, space(), text(x)] - @ ( - settings.show_casts - ? [ - DHDoc_common.Delim.colon_Fun, - space(), - DHDoc_Typ.mk(~enforce_inline=true, ty), - ] - : [] - ) + [ + DHDoc_common.Delim.fix_FixF, + space(), + DHDoc_Pat.mk( + ~infomap, + dp, + ~show_casts=settings.show_casts, + ~enforce_inline=true, + ), + ] @ [ space(), DHDoc_common.Delim.arrow_FixF, @@ -718,20 +693,39 @@ let mk = doc_body |> DHDoc_common.pad_child(~enforce_inline), ], ); - | FixF(x, _, _) => annot(DHAnnot.Collapsed, text("<" ++ x ++ ">")) + | FixF(_, {term: Fun(_, _, _, Some(x)), _}, _) => + if (String.ends_with(~suffix="+", x)) { + annot( + DHAnnot.Collapsed, + text("<" ++ String.sub(x, 0, String.length(x) - 1) ++ ">"), + ); + } else { + annot(DHAnnot.Collapsed, text("<" ++ x ++ ">")); + } + | FixF(_, _, _) => annot(DHAnnot.Collapsed, text("")) }; }; let steppable = - next_steps |> List.find_opt(((ctx, _)) => ctx == EvalCtx.Mark); + next_steps |> List.find_opt(((_, id)) => id == DHExp.rep_id(d)); let stepped = chosen_step - |> Option.map(x => x.ctx == Mark) + |> Option.map(x => DHExp.rep_id(x.d_loc) == DHExp.rep_id(d)) |> Option.value(~default=false); + let substitution = + hidden_steps + |> List.find_opt(((step, id)) => + step.knd == VarLookup + // HACK[Matt]: to prevent substitutions hiding inside casts + && id == DHExp.rep_id(d) + ); let doc = switch (substitution) { - | Some({d_loc: BoundVar(v), _}) when List.mem(v, recent_subst) => - hcats([text(v) |> annot(DHAnnot.Substituted), doc]) - | Some(_) + | Some((step, _)) => + switch (DHExp.term_of(step.d_loc)) { + | Var(v) when List.mem(v, recent_subst) => + hcats([text(v) |> annot(DHAnnot.Substituted), doc]) + | _ => doc + } | None => doc }; let doc = @@ -739,20 +733,11 @@ let mk = annot(DHAnnot.Stepped, doc); } else { switch (steppable) { - | Some((_, full)) => annot(DHAnnot.Steppable(full), doc) + | Some((i, _)) => annot(DHAnnot.Steppable(i), doc) | None => doc }; }; doc; }; - go( - d, - env, - enforce_inline, - previous_step, - hidden_steps, - chosen_step, - List.mapi((idx, x: EvalObj.t) => (x.ctx, idx), next_steps), - [], - ); + go(d, env, enforce_inline, []); }; diff --git a/src/haz3lweb/view/dhcode/layout/DHDoc_Pat.re b/src/haz3lweb/view/dhcode/layout/DHDoc_Pat.re index 0e2bd8e004..8996bd4b03 100644 --- a/src/haz3lweb/view/dhcode/layout/DHDoc_Pat.re +++ b/src/haz3lweb/view/dhcode/layout/DHDoc_Pat.re @@ -1,28 +1,36 @@ open Pretty; open Haz3lcore; -let precedence = (dp: DHPat.t) => - switch (dp) { - | EmptyHole(_) - | NonEmptyHole(_) +let precedence = (dp: Pat.t) => + switch (DHPat.term_of(dp)) { + | EmptyHole + | MultiHole(_) | Wild - | InvalidText(_) - | BadConstructor(_) + | Invalid(_) | Var(_) - | IntLit(_) - | FloatLit(_) - | BoolLit(_) - | StringLit(_) + | Int(_) + | Float(_) + | Bool(_) + | String(_) | ListLit(_) | Constructor(_) => DHDoc_common.precedence_const | Tuple(_) => DHDoc_common.precedence_Comma | Cons(_) => DHDoc_common.precedence_Cons | Ap(_) => DHDoc_common.precedence_Ap + | Parens(_) => DHDoc_common.precedence_const + | Cast(_) => DHDoc_common.precedence_Ap }; let rec mk = - (~parenthesize=false, ~enforce_inline: bool, dp: DHPat.t): DHDoc.t => { - let mk' = mk(~enforce_inline); + ( + ~infomap: Statics.Map.t, + ~parenthesize=false, + ~show_casts, + ~enforce_inline: bool, + dp: Pat.t, + ) + : DHDoc.t => { + let mk' = mk(~enforce_inline, ~infomap, ~show_casts); let mk_left_associative_operands = (precedence_op, dp1, dp2) => ( mk'(~parenthesize=precedence(dp1) > precedence_op, dp1), mk'(~parenthesize=precedence(dp2) >= precedence_op, dp2), @@ -32,20 +40,18 @@ let rec mk = mk'(~parenthesize=precedence(dp2) > precedence_op, dp2), ); let doc = - switch (dp) { - | EmptyHole(u, i) => DHDoc_common.mk_EmptyHole((u, i)) - | NonEmptyHole(reason, u, i, dp) => - mk'(dp) |> Doc.annot(DHAnnot.NonEmptyHole(reason, (u, i))) - | InvalidText(u, i, t) => DHDoc_common.mk_InvalidText(t, (u, i)) - | BadConstructor(u, i, t) => DHDoc_common.mk_InvalidText(t, (u, i)) + switch (DHPat.term_of(dp)) { + | MultiHole(_) + | EmptyHole => DHDoc_common.mk_EmptyHole(ClosureEnvironment.empty) + | Invalid(t) => DHDoc_common.mk_InvalidText(t) | Var(x) => Doc.text(x) | Wild => DHDoc_common.Delim.wild - | Constructor(name) => DHDoc_common.mk_ConstructorLit(name) - | IntLit(n) => DHDoc_common.mk_IntLit(n) - | FloatLit(f) => DHDoc_common.mk_FloatLit(f) - | BoolLit(b) => DHDoc_common.mk_BoolLit(b) - | StringLit(s) => DHDoc_common.mk_StringLit(s) - | ListLit(_, d_list) => + | Constructor(name, _) => DHDoc_common.mk_ConstructorLit(name) + | Int(n) => DHDoc_common.mk_IntLit(n) + | Float(f) => DHDoc_common.mk_FloatLit(f) + | Bool(b) => DHDoc_common.mk_BoolLit(b) + | String(s) => DHDoc_common.mk_StringLit(s) + | ListLit(d_list) => let ol = List.map(mk', d_list); DHDoc_common.mk_ListLit(ol); | Cons(dp1, dp2) => @@ -54,11 +60,34 @@ let rec mk = DHDoc_common.mk_Cons(doc1, doc2); | Tuple([]) => DHDoc_common.Delim.triv | Tuple(ds) => DHDoc_common.mk_Tuple(List.map(mk', ds)) + // TODO: Print type annotations + | Cast(dp, t1, t2) when show_casts => + Doc.hcats([ + mk'(dp), + Doc.annot( + DHAnnot.CastDecoration, + Doc.hcats([ + DHDoc_common.Delim.open_Cast, + DHDoc_Typ.mk(~enforce_inline=true, t1), + DHDoc_common.Delim.back_arrow_Cast, + DHDoc_Typ.mk(~enforce_inline=true, t2), + DHDoc_common.Delim.close_Cast, + ]), + ), + ]) + | Cast(dp, _, _) => mk'(~parenthesize, dp) + | Parens(dp) => + mk(~enforce_inline, ~parenthesize=true, ~infomap, ~show_casts, dp) | Ap(dp1, dp2) => let (doc1, doc2) = mk_left_associative_operands(DHDoc_common.precedence_Ap, dp1, dp2); DHDoc_common.mk_Ap(doc1, doc2); }; + let doc = + switch (Statics.get_pat_error_at(infomap, DHPat.rep_id(dp))) { + | Some(_) => Doc.annot(DHAnnot.NonEmptyHole, doc) + | None => doc + }; parenthesize ? Doc.hcats([ DHDoc_common.Delim.open_Parenthesized, diff --git a/src/haz3lweb/view/dhcode/layout/DHDoc_Pat.rei b/src/haz3lweb/view/dhcode/layout/DHDoc_Pat.rei deleted file mode 100644 index 33c37b6092..0000000000 --- a/src/haz3lweb/view/dhcode/layout/DHDoc_Pat.rei +++ /dev/null @@ -1,5 +0,0 @@ -open Haz3lcore; - -let precedence: DHPat.t => int; - -let mk: (~parenthesize: bool=?, ~enforce_inline: bool, DHPat.t) => DHDoc.t; diff --git a/src/haz3lweb/view/dhcode/layout/DHDoc_Typ.rei b/src/haz3lweb/view/dhcode/layout/DHDoc_Typ.rei deleted file mode 100644 index 5ea2583ae4..0000000000 --- a/src/haz3lweb/view/dhcode/layout/DHDoc_Typ.rei +++ /dev/null @@ -1,3 +0,0 @@ -open Haz3lcore; - -let mk: (~enforce_inline: bool, Typ.t) => DHDoc.t; diff --git a/src/haz3lweb/view/dhcode/layout/DHDoc_Util.re b/src/haz3lweb/view/dhcode/layout/DHDoc_Util.re index f127804400..9e9578d217 100644 --- a/src/haz3lweb/view/dhcode/layout/DHDoc_Util.re +++ b/src/haz3lweb/view/dhcode/layout/DHDoc_Util.re @@ -1,4 +1,3 @@ -open Util; open Haz3lcore; module Doc = Pretty.Doc; @@ -46,8 +45,8 @@ module Delim = { let mk = (delim_text: string): t => Doc.text(delim_text) |> Doc.annot(DHAnnot.Delim); - let empty_hole = ((u, i): HoleInstance.t): t => { - let lbl = StringUtil.cat([Id.to_string(u), ":", string_of_int(i + 1)]); + let empty_hole = (_env: ClosureEnvironment.t): t => { + let lbl = "-"; Doc.text(lbl) |> Doc.annot(DHAnnot.HoleLabel) |> Doc.annot(DHAnnot.Delim); @@ -85,9 +84,8 @@ module Delim = { let close_FailedCast = close_Cast |> Doc.annot(DHAnnot.FailedCastDelim); }; -let mk_EmptyHole = (~selected=false, (u, i)) => - Delim.empty_hole((u, i)) - |> Doc.annot(DHAnnot.EmptyHole(selected, (u, i))); +let mk_EmptyHole = (~selected=false, env) => + Delim.empty_hole(env) |> Doc.annot(DHAnnot.EmptyHole(selected, env)); let mk_IntLit = n => Doc.text(string_of_int(n)); diff --git a/src/haz3lweb/view/dhcode/layout/DHDoc_common.re b/src/haz3lweb/view/dhcode/layout/DHDoc_common.re index 68abee9f93..3627d26bf2 100644 --- a/src/haz3lweb/view/dhcode/layout/DHDoc_common.re +++ b/src/haz3lweb/view/dhcode/layout/DHDoc_common.re @@ -8,7 +8,7 @@ module P = Precedence; let precedence_const = P.max; let precedence_Ap = P.ap; let precedence_Power = P.power; - +let precedence_Not = P.not_; let precedence_Times = P.mult; let precedence_Divide = P.mult; let precedence_Plus = P.plus; @@ -19,7 +19,7 @@ let precedence_LessThan = P.eqs; let precedence_GreaterThan = P.eqs; let precedence_And = P.and_; let precedence_Or = P.or_; -let precedence_Comma = P.prod; +let precedence_Comma = P.comma; let precedence_max = P.min; let pad_child = @@ -45,7 +45,7 @@ module Delim = { let mk = (delim_text: string): t => Doc.text(delim_text) |> Doc.annot(DHAnnot.Delim); - let empty_hole = ((_u, _i): HoleInstance.t): t => { + let empty_hole = (_env: ClosureEnvironment.t): t => { let lbl = //StringUtil.cat([string_of_int(u + 1), ":", string_of_int(i + 1)]); "?"; @@ -70,8 +70,6 @@ module Delim = { let arrow_FixF = mk("->"); let colon_FixF = mk(":"); - let projection_dot = mk("."); - let open_Case = mk("case"); let close_Case = mk("end"); @@ -80,6 +78,7 @@ module Delim = { let open_Cast = mk("<"); let arrow_Cast = mk(Unicode.castArrowSym); + let back_arrow_Cast = mk(Unicode.castBackArrowSym); let close_Cast = mk(">"); let open_FailedCast = open_Cast |> Doc.annot(DHAnnot.FailedCastDelim); @@ -88,11 +87,10 @@ module Delim = { let close_FailedCast = close_Cast |> Doc.annot(DHAnnot.FailedCastDelim); }; -let mk_EmptyHole = (~selected=false, hc: HoleInstance.t) => - Delim.empty_hole(hc) |> Doc.annot(DHAnnot.EmptyHole(selected, hc)); +let mk_EmptyHole = (~selected=false, env: ClosureEnvironment.t) => + Delim.empty_hole(env) |> Doc.annot(DHAnnot.EmptyHole(selected, env)); -let mk_InvalidText = (t, hc) => - Doc.text(t) |> Doc.annot(DHAnnot.Invalid(hc)); +let mk_InvalidText = t => Doc.text(t) |> Doc.annot(DHAnnot.Invalid); let mk_Sequence = (doc1, doc2) => Doc.(hcats([doc1, linebreak(), doc2])); @@ -155,5 +153,6 @@ let mk_TypAp = (doc1, doc2) => let mk_Ap = (doc1, doc2) => Doc.(hcats([doc1, text("("), doc2, text(")")])); -let mk_Prj = (targ, n) => - Doc.hcats([targ, Delim.projection_dot, Doc.text(string_of_int(n))]); +let mk_rev_Ap = (doc1, doc2) => Doc.(hcats([doc1, text(" |> "), doc2])); + +let mk_Undefined = () => Doc.text("undefined"); diff --git a/src/haz3lweb/view/dhcode/layout/DHDoc_common.rei b/src/haz3lweb/view/dhcode/layout/DHDoc_common.rei index 1d0a2d65d2..553d6ce8ec 100644 --- a/src/haz3lweb/view/dhcode/layout/DHDoc_common.rei +++ b/src/haz3lweb/view/dhcode/layout/DHDoc_common.rei @@ -9,6 +9,7 @@ let precedence_Power: int; let precedence_Divide: int; let precedence_Plus: int; let precedence_Minus: int; +let precedence_Not: int; let precedence_Cons: int; let precedence_Equals: int; let precedence_LessThan: int; @@ -29,7 +30,7 @@ let pad_child: module Delim: { let mk: string => DHDoc.t; - let empty_hole: HoleInstance.t => DHDoc.t; + let empty_hole: ClosureEnvironment.t => DHDoc.t; let list_nil: DHDoc.t; let triv: DHDoc.t; @@ -54,6 +55,7 @@ module Delim: { let open_Cast: DHDoc.t; let arrow_Cast: DHDoc.t; + let back_arrow_Cast: DHDoc.t; let close_Cast: DHDoc.t; let open_FailedCast: Pretty.Doc.t(DHAnnot.t); @@ -62,9 +64,9 @@ module Delim: { }; let mk_EmptyHole: - (~selected: bool=?, HoleInstance.t) => Pretty.Doc.t(DHAnnot.t); + (~selected: bool=?, ClosureEnvironment.t) => Pretty.Doc.t(DHAnnot.t); -let mk_InvalidText: (string, HoleInstance.t) => Pretty.Doc.t(DHAnnot.t); +let mk_InvalidText: string => Pretty.Doc.t(DHAnnot.t); let mk_Sequence: (Pretty.Doc.t('a), Pretty.Doc.t('a)) => Pretty.Doc.t('a); @@ -96,4 +98,6 @@ let mk_TypAp: (Pretty.Doc.t('a), Pretty.Doc.t('a)) => Pretty.Doc.t('a); let mk_Ap: (Pretty.Doc.t('a), Pretty.Doc.t('a)) => Pretty.Doc.t('a); -let mk_Prj: (Pretty.Doc.t(DHAnnot.t), int) => Pretty.Doc.t(DHAnnot.t); +let mk_rev_Ap: (Pretty.Doc.t('a), Pretty.Doc.t('a)) => Pretty.Doc.t('a); + +let mk_Undefined: unit => Pretty.Doc.t('a); diff --git a/src/haz3lweb/view/dhcode/layout/HTypDoc.re b/src/haz3lweb/view/dhcode/layout/HTypDoc.re index ab1cd80cb1..72c4cb9d60 100644 --- a/src/haz3lweb/view/dhcode/layout/HTypDoc.re +++ b/src/haz3lweb/view/dhcode/layout/HTypDoc.re @@ -6,6 +6,30 @@ type t = Doc.t(HTypAnnot.t); type formattable_child = (~enforce_inline: bool) => t; +let precedence_Prod = 1; +let precedence_Arrow = 2; +let precedence_Sum = 3; +let precedence_Ap = 4; +let precedence_Const = 5; + +let precedence = (ty: Typ.t): int => + switch (Typ.term_of(ty)) { + | Int + | Float + | Bool + | String + | Unknown(_) + | Var(_) + | Forall(_) + | Rec(_) + | Sum(_) => precedence_Sum + | List(_) => precedence_Const + | Prod(_) => precedence_Prod + | Arrow(_, _) => precedence_Arrow + | Parens(_) => precedence_Const + | Ap(_) => precedence_Ap + }; + let pad_child = ( ~inline_padding as (l, r)=(Doc.empty(), Doc.empty()), @@ -18,7 +42,7 @@ let pad_child = Doc.( hcats([ linebreak(), - indent_and_align(child(~enforce_inline=false)), + indent_and_align(child(~enforce_inline)), linebreak(), ]) ); @@ -33,15 +57,16 @@ let rec mk = (~parenthesize=false, ~enforce_inline: bool, ty: Typ.t): t => { let mk_right_associative_operands = (precedence_op, ty1, ty2) => ( annot( HTypAnnot.Step(0), - mk'(~parenthesize=Typ.precedence(ty1) <= precedence_op, ty1), + mk'(~parenthesize=precedence(ty1) <= precedence_op, ty1), ), annot( HTypAnnot.Step(1), - mk'(~parenthesize=Typ.precedence(ty2) < precedence_op, ty2), + mk'(~parenthesize=precedence(ty2) < precedence_op, ty2), ), ); let (doc, parenthesize) = - switch (ty) { + switch (Typ.term_of(ty)) { + | Parens(ty) => (mk(~parenthesize=true, ~enforce_inline, ty), false) | Unknown(_) => ( annot(HTypAnnot.Delim, annot(HTypAnnot.HoleLabel, text("?"))), parenthesize, @@ -65,7 +90,7 @@ let rec mk = (~parenthesize=false, ~enforce_inline: bool, ty: Typ.t): t => { ) | Arrow(ty1, ty2) => let (d1, d2) = - mk_right_associative_operands(TypBase.precedence_Arrow, ty1, ty2); + mk_right_associative_operands(precedence_Arrow, ty1, ty2); ( hcats([ d1, @@ -83,20 +108,13 @@ let rec mk = (~parenthesize=false, ~enforce_inline: bool, ty: Typ.t): t => { [ annot( HTypAnnot.Step(0), - mk'( - ~parenthesize=Typ.precedence(head) <= TypBase.precedence_Prod, - head, - ), + mk'(~parenthesize=precedence(head) <= precedence_Prod, head), ), ...List.mapi( (i, ty) => annot( HTypAnnot.Step(i + 1), - mk'( - ~parenthesize= - Typ.precedence(ty) <= TypBase.precedence_Prod, - ty, - ), + mk'(~parenthesize=precedence(ty) <= precedence_Prod, ty), ), tail, ), @@ -108,7 +126,7 @@ let rec mk = (~parenthesize=false, ~enforce_inline: bool, ty: Typ.t): t => { (center, true); | Rec(name, ty) => ( hcats([ - text("rec " ++ name ++ "->{"), + text("rec " ++ Type.tpat_view(name) ++ "->{"), ( (~enforce_inline) => annot(HTypAnnot.Step(0), mk(~enforce_inline, ty)) @@ -120,7 +138,7 @@ let rec mk = (~parenthesize=false, ~enforce_inline: bool, ty: Typ.t): t => { ) | Forall(name, ty) => ( hcats([ - text("forall " ++ name ++ "->{"), + text("forall " ++ Type.tpat_view(name) ++ "->{"), ( (~enforce_inline) => annot(HTypAnnot.Step(0), mk(~enforce_inline, ty)) @@ -179,15 +197,21 @@ let rec mk = (~parenthesize=false, ~enforce_inline: bool, ty: Typ.t): t => { | Sum(sum_map) => let center = List.mapi( - (i, (ctr, ty)) => - switch (ty) { - | None => annot(HTypAnnot.Step(i + 1), text(ctr)) - | Some(ty) => - annot( - HTypAnnot.Step(i + 1), - hcats([text(ctr ++ "("), mk'(ty), text(")")]), - ) - }, + (i, vr) => { + ConstructorMap.( + switch (vr) { + | Variant(ctr, _, None) => + annot(HTypAnnot.Step(i + 1), text(ctr)) + | Variant(ctr, _, Some(ty)) => + annot( + HTypAnnot.Step(i + 1), + hcats([text(ctr ++ "("), mk'(ty), text(")")]), + ) + | BadEntry(ty) => + annot(HTypAnnot.Step(i + 1), hcats([mk'(ty)])) + } + ) + }, sum_map, ) |> ListUtil.join( @@ -195,6 +219,10 @@ let rec mk = (~parenthesize=false, ~enforce_inline: bool, ty: Typ.t): t => { ) |> hcats; (center, true); + | Ap(t1, t2) => ( + hcats([mk'(t1), text("("), mk'(t2), text(")")]), + parenthesize, + ) }; let doc = annot(HTypAnnot.Term, doc); parenthesize ? 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--git a/src/haz3lweb/www/img/noun-fold-1593409.svg b/src/haz3lweb/www/img/noun-fold-1593409.svg new file mode 100644 index 0000000000..db6149dfff --- /dev/null +++ b/src/haz3lweb/www/img/noun-fold-1593409.svg @@ -0,0 +1,15 @@ + + + + + + + + + + + + + + + diff --git a/src/haz3lweb/www/img/noun-map-24173.svg b/src/haz3lweb/www/img/noun-map-24173.svg new file mode 100644 index 0000000000..bcfaa12eea --- /dev/null +++ b/src/haz3lweb/www/img/noun-map-24173.svg @@ -0,0 +1,4 @@ + + + + diff --git a/src/haz3lweb/www/img/noun-map-6188938.svg b/src/haz3lweb/www/img/noun-map-6188938.svg new file mode 100644 index 0000000000..cc83ede9c4 --- /dev/null +++ b/src/haz3lweb/www/img/noun-map-6188938.svg @@ -0,0 +1,4 @@ + + + + diff --git a/src/haz3lweb/www/img/noun-pa-5383544.svg b/src/haz3lweb/www/img/noun-pa-5383544.svg new file mode 100644 index 0000000000..7333419486 --- /dev/null +++ b/src/haz3lweb/www/img/noun-pa-5383544.svg @@ -0,0 +1,8 @@ + + + + + + + + diff --git a/src/haz3lweb/www/index.html b/src/haz3lweb/www/index.html index cd9cc8aa2a..47cbc90039 100644 --- a/src/haz3lweb/www/index.html +++ b/src/haz3lweb/www/index.html @@ -9,6 +9,22 @@ hazel + + + + + + + @@ -22,6 +38,7 @@ + diff --git a/src/haz3lweb/www/ninja_module.js b/src/haz3lweb/www/ninja_module.js new file mode 100644 index 0000000000..05698342a5 --- /dev/null +++ b/src/haz3lweb/www/ninja_module.js @@ -0,0 +1,25 @@ +import {NinjaKeys} from 'https://unpkg.com/ninja-keys?module'; +import hotkeys from "https://unpkg.com/hotkeys-js@3.8.7?module" + + +// This is the default behavior for the hotkeys module but I'm overriding it for the clipboard-shim +hotkeys.filter = event => { + const target = event.target || event.srcElement; + const { tagName, id } = target; + + // Override happening here + if(id == "clipboard-shim") { + return true; + } + + let flag = true; + const isInput = tagName === 'INPUT' && !['checkbox', 'radio', 'range', 'button', 'file', 'reset', 'submit', 'color'].includes(target.type); + // ignore: isContentEditable === 'true', and