Programming exercises: Improve preliminary AI feedback

[dmytropolityka]

You can test this PR only on ts1

Checklist

General

• I tested all changes and their related features with all corresponding user types on a test server.
• This is a small issue that I tested locally and was confirmed by another developer on a test server.
• Language: I followed the guidelines for inclusive, diversity-sensitive, and appreciative language.
• I chose a title conforming to the naming conventions for pull requests.

Server

• Important: I implemented the changes with a very good performance and prevented too many (unnecessary) and too complex database calls.
• I strictly followed the principle of data economy for all database calls.
• I strictly followed the server coding and design guidelines.
• I added multiple integration tests (Spring) related to the features (with a high test coverage).
• I added pre-authorization annotations according to the guidelines and checked the course groups for all new REST Calls (security).
• I documented the Java code using JavaDoc style.

Client

• Important: I implemented the changes with a very good performance, prevented too many (unnecessary) REST calls and made sure the UI is responsive, even with large data (e.g. using paging).
• I strictly followed the principle of data economy for all client-server REST calls.
• I strictly followed the client coding and design guidelines.
• Following the theming guidelines, I specified colors only in the theming variable files and checked that the changes look consistent in both the light and the dark theme.
• I added multiple integration tests (Jest) related to the features (with a high test coverage), while following the test guidelines.
• I added authorities to all new routes and checked the course groups for displaying navigation elements (links, buttons).
• I documented the TypeScript code using JSDoc style.
• I added multiple screenshots/screencasts of my UI changes.
• I translated all newly inserted strings into English and German.

Motivation and Context

We previously used individual due dates and repository locks to control when requests were sent to Athena, allowing better management of the feedback process. This has now been simplified by removing individual due dates and locks, which are no longer needed. Additionally, animations have been aligned with the default Artemis indicator for consistency. Generated feedback results are now rated by default, with a tooltip explaining that the grade is an AI assessment, subject to change. I also added sorting to the generated feedback to improve clarity.

Description

Removed the individual due date and lock mechanism for feedback requests to Athena.
Updated animations to be consistent with Artemis’ default loading indicators.
Added automatic rating of AI-generated results with a tooltip explaining that it's a preliminary grade.
Implemented sorting for generated feedback to ensure a clearer presentation of results.

Steps for Testing

Prerequisites:
1 Instructor
1 Students
1 Programming Exercise

Log in to Artemis.
Navigate to Course Administration.
Create a programming exercise, set the due date, enable manual assessment, enable grading suggestions, and select an Athena module for feedback as the instructor.
As a student, solve the programming exercise and request feedback.
Ensure the animations function as expected and that the feedback status is clearly displayed.
Verify that the feedback results can be viewed, including from the code editor.
As the instructor, set the due date to the past and assess the submission.
Ensure that the AI-generated result is no longer visible in the assessment view.
Submit the assessment, and as a student, verify that the final grade is visible.

Exam Mode Testing

Prerequisites:

1 Instructor
2 Students
1 Exam with a Programming Exercise
Log in to Artemis.
As a student, participate in the exam, solve the programming exercise, and submit.
As the instructor, assess the submission.
Ensure that the student can access the assessment without any change in functionality compared to the standard mode.

Testserver States

Note

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Green = Currently available, Red = Currently locked
Click on the badges to get to the test servers.

Review Progress

Performance Review

• I (as a reviewer) confirm that the client changes (in particular related to REST calls and UI responsiveness) are implemented with a very good performance even for very large courses with more than 2000 students.
• I (as a reviewer) confirm that the server changes (in particular related to database calls) are implemented with a very good performance even for very large courses with more than 2000 students.

Code Review

• Code Review 1
• Code Review 2

Manual Tests

• Test 1
• Test 2

Exam Mode Test

• Test 1
• Test 2

Performance Tests

• Test 1
• Test 2

Test Coverage

Info: ✅ ❌ in Confirmation (assert/expect) have to be adjusted manually, also delete trivial files!

Client

Class/File	Line Coverage	Confirmation (assert/expect)
code-editor-actions.component.ts	81.3%	✅ ❌
programming-exercise.utils.ts	94.82%	✅ ❌
participation.utils.ts	76.19%	✅ ❌
result.service.ts	91.52%	✅ ❌
result.utils.ts	90.65%	✅ ❌
updating-result.component.ts	97.05%	✅ ❌
course-exercise-details.component.ts	89.2%	✅ ❌
exercise-details-student-actions.component.ts	86.03%	✅ ❌
request-feedback-button.component.ts	89.65%	✅ ❌

Server

Class/File	Line Coverage	Confirmation (assert/expect)
Exercise.java	92%	✅ ❌
ParticipationResource.java	87%	✅ ❌
ProgrammingExerciseCodeReviewFeedbackService.java	74%	✅ ❌

Screenshots

Results timeline:

Feedback window:

Summary by CodeRabbit

Summary by CodeRabbit

Release Notes

• New Features

  • Introduced a new requestFeedback method to streamline feedback requests, improving user interaction.
  • Added a RequestFeedbackButtonComponent to enhance the user experience in the code editor.

• Bug Fixes

  • Improved error handling and messaging for feedback requests, ensuring users receive clear notifications based on their actions and submission states.

• Improvements

  • Refined logic for filtering results based on assessment types, particularly for AI assessments.
  • Enhanced participation management functionality by improving error handling and refining logic for participation-related operations.
  • Streamlined initialization processes in the user interface for better usability and clarity.
  • Updated localization for clarity, including changes to key names and messages.
  • Improved clarity and functionality of feedback request tests, ensuring they accurately reflect intended behavior under different conditions.

[github-actions]

⚠️ Unable to deploy to test servers ⚠️

The docker build needs to run through before deploying.

[github-actions]

There hasn't been any activity on this pull request recently. Therefore, this pull request has been automatically marked as stale and will be closed if no further activity occurs within seven days. Thank you for your contributions.