diff --git a/01-big-shiny.Rmd b/01-big-shiny.Rmd
index 7cec4be8..12d86096 100644
--- a/01-big-shiny.Rmd
+++ b/01-big-shiny.Rmd
@@ -8,7 +8,6 @@
 
 If you are reading this page, chances are you already know what a `{shiny}` application (sometimes shortened as "`{shiny}` app") is—**a web application that communicates with R, built in R, and working with R**.
 The beauty of `{shiny}` [@R-shiny] is that it makes it easy for someone already familiar with R to create a small app in a matter of hours.
-With small and minimal `{shiny}` apps, no knowledge of HTML (HyperText Markup Language), CSS(Cascading Style Sheets) or JavaScript is required, and you do not have to think about technical elements that usually come with web applications—for example, you do not have to think about the port the application is served on: `{shiny}` picks one for you.[^big-shiny-1]
 Same goes for serving external dependencies: the application comes with its set of CSS and JavaScript dependencies that a common `{shiny}` developer does not need to worry about.
 And that is probably one of the main reasons why this package has become so successful over the years—**with very little training, you can rapidly create a proof-of-concept (PoC) for a data product, showcase an algorithm, or present your results in an elegant and accessible user interfaces**.
 
@@ -304,7 +303,7 @@ hexmake_cloc
 
 
 One thing that this package also allows is counting the number of lines of commented code: it's usually a good sign to see that a package has comments in its code-base, as it will allow to work more safely in the future, provided that this metric doesn't reveal that large portions of the application are "commented code" (as opposed to "code comments").
-For example, here we can see that `{hemake}` has `r dplyr::filter(hexmake_cloc, language == "R") %>% dplyr::pull(loc)` lines of R code, which come with `r dplyr::filter(hexmake_cloc, language == "R") %>% dplyr::pull(comment_lines)` lines of code comments.
+For example, here we can see that `{hexmake}` has `r dplyr::filter(hexmake_cloc, language == "R") %>% dplyr::pull(loc)` lines of R code, which come with `r dplyr::filter(hexmake_cloc, language == "R") %>% dplyr::pull(comment_lines)` lines of code comments.
 
 #### B. Cyclomatic complexity {.unnumbered}