Advanced R Programming: Reusable Functions, Debugging and Clean Code

Writing Reusable Functions

If you copy the same code more than twice, turn it into a function. Give each input a clear name. With double curly brackets ({{ }}), a function can accept a column name when using tidy evaluation.

This approach can help you create a function that summarises marks for any grouping column. Small functions are also easier to test, because you can try them on a few values.

Error Handling and Debugging

Programs can fail, for example, when the data has the wrong type. The tryCatch() function lets your code handle a problem calmly instead of stopping unexpectedly.

To find bugs:

• Print values as you go.
• Use traceback() after an error.
• Use breakpoints in RStudio.
• Test your code with small examples first.

Clear error messages help the next person understand what went wrong and how to fix it.

Improving Code Readability and Reusability

Other people, and your future self, must be able to read your code. Use clear names in snake_case, write comments that explain why you did something, and keep each function focused on one job.

Place shared functions in a file such as helpers.R. Load it with source().

Clean code is easier to fix and easier to trust. Reading your code aloud as a sentence is a good test of whether the names are clear.