PIPING HOT DATA: Debugging

Shannon Pileggi

Figure organize by functions, options, and the RStudio IDE, with icons to indicate traceback, interactive debugger, your code, their code.

Figure 1: Overview of debugging tools in R.

Overview

A 3-hour zoom workshop on debugging for the NHS-R conference.

Under the Creative Commons Share Alike 4.0 International license, workshop materials have been adapted from the 2022 RStudio What They Forgot To Teach You About R Workshop.

Pre-requisites

Knowledge of how to write a function in R.

Learning objectives:

Review code troubleshooting tips.
Discuss debugging functions (traceback(), browser(), debug(), trace(), and recover()) and the additional benefits of employing some of these strategies within RStudio.
Distinguish between strategies for debugging your own code versus someone else’s code.

Citation

For attribution, please cite this work as

Pileggi (2022, Nov. 10). PIPING HOT DATA: Debugging. Retrieved from https://www.pipinghotdata.com/talks/2022-11-11-debugging/

BibTeX citation

@misc{pileggi2022debugging,
  author = {Pileggi, Shannon},
  title = {PIPING HOT DATA: Debugging},
  url = {https://www.pipinghotdata.com/talks/2022-11-11-debugging/},
  year = {2022}
}