Writing Good Software

Last updated on 2026-01-14 | Edit this page

Estimated time: 15 minutes

Overview

Questions

  • How can I write software that other people can use?

Objectives

  • Describe best practices for writing R and explain the justification for each.

Structure your project folder

Keep your project folder structured, organized and tidy, by creating subfolders for your code files, manuals, data, binaries, output plots, etc. It can be done completely manually, or with the help of RStudio’s New Project functionality, or a designated package, such as ProjectTemplate.

An example layout for the project folder:

|– README |– task | |– project_task.js | |– stim |– data | |– project_data.csv |– analysis | |– project_analysis.Rmd | |– project_analysis.html |– manuscript | |– project_manuscript.docx

Make code readable

The most important part of writing code is making it readable and understandable. You want someone else to be able to pick up your code and be able to understand what it does: more often than not this someone will be you 6 months down the line, who will otherwise be cursing past-self.

  • Use intuitive variable names that identify the object.
  • Use a consistent style and spacing for your code.
  • Use comments to explain your code (especially uncommon steps).

Documentation: tell us what and why, not how

When you first start out, your comments will often describe what a command does, since you’re still learning yourself and it can help to clarify concepts and remind you later. However, these comments aren’t particularly useful later on when you don’t remember what problem your code is trying to solve. Try to also include comments that tell you why you’re solving a problem, and what problem that is. The how can come after that: it’s an implementation detail you ideally shouldn’t have to worry about.

Keep your code modular

Our recommendation is that you should separate your functions from your analysis scripts, and store them in a separate file that you source when you open the R session in your project. This approach is nice because it leaves you with an uncluttered analysis script, and a repository of useful functions that can be loaded into any analysis script in your project. It also lets you group related functions together easily.

Break down problem into bite size pieces

When you first start out, problem solving and function writing can be daunting tasks, and hard to separate from code inexperience. Try to break down your problem into digestible chunks and worry about the implementation details later: keep breaking down the problem into smaller and smaller functions until you reach a point where you can code a solution, and build back up from there.

Know that your code is doing the right thing

Make sure to test your functions and your code!

Don’t repeat yourself

Functions enable easy reuse within a project. If you see blocks of similar lines of code through your project, those are usually candidates for being moved into functions.

If your calculations are performed through a series of functions, then the project becomes more modular and easier to change. This is especially the case for which a particular input always gives a particular output.

Key Points
  • Keep your project folder structured, organized and tidy.
  • Document what and why, not how.
  • Break programs into short single-purpose functions.
  • Write re-runnable tests.
  • Don’t repeat yourself.
  • Be consistent in naming, indentation, and other aspects of style.