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Writing Good Tests In R

Brian Rowe discusses testing strategy in R:

It’s not uncommon for tests to be written at the get-go and then forgotten about. Remember that as code changes or incorrect behavior is found, new tests need to be written or existing tests need to be modified. Possibly worse than having no tests is having a bunch of tests spitting out false positives. This is because humans are prone to habituation and desensitization. It’s easy to become habituated to false positives to the point where we no longer pay attention to them.

Temporarily disabling tests may be acceptable in the short term. A more strategic solution is to optimize your test writing. The easier it is to create and modify tests, the more likely they will be correct and continue to provide value. For my testing, I generally write code to automate a lot of wiring to verify results programmatically.

I started this article with almost no idea how to test R code.  I still don’t…but this article does help.  I recommend reading it if you want to write production-quality R code.