How do you review code that accompanies a research project or paper? Help rOpenSci plan a Community Call

codereview
commcalls
Tags: #<Tag:0x00007f6571153640> #<Tag:0x00007f6571153488>

#43

Resources on this topic, in no particular order (add yours!)


#44

I would love to help you do whatever it would take to make this thing!


#45

Very similar boat at my workplace. Additionally, all the coders we have are essentially at the same level - doesn’t mean we can’t help each other, but does mean we may have a bit of a plateau effect when it comes to improving code through review…


#46

Thanks for the great community call today! As promised, a quick post about code review as part of the peer review process of journal articles. Code Ocean is piloting code review with Nature currently, you can find some details here: https://www.nature.com/articles/s41592-018-0137-5; and the perspective of our developer advocate, Seth Green, on the code review process here: https://codeocean.com/blog/post/nature-journals-pilot-with-code-ocean-a-developer-advocates-perspective

Generally speaking, the code review process is as follows:

  1. Authors upload a working copy of their code to Code Ocean.
  2. Code Ocean verifies that the code runs and delivers results.
  3. Code Ocean provides Nature editors with a private link (blinded or unblinded) to the code capsule for peer review of the code.
  4. Once the code and article are approved by reviewers, Code Ocean will mint a DOI and include a link to the article in the metadata.
  5. Nature includes a link or embed the Code Ocean widget in the the article.
  6. Nature readers will be able to run code and reproduce the results associated with an article by simply clicking a button, as well as edit the code or test it with new data and parameters.

#47

Not everyone reading about this stuff knows what “refactoring” or “linters” are. In the summary blog post about this Community Call, we’d like to link those words to definitions. Anyone have favourite? Otherwise I’ll go with wikipedia


#48

good call! For linting, it might be more helpful to most of our audience to link directly to https://github.com/jimhester/lintr.

for code refactoring, the wikipedia entry looks like a good choice to me.


#49

Thanks Carl! Do you have recommendations for links for unit testing, continuous integration, and container as well?


#50

recommendations for links for unit testing, continuous integration, and container


#51

We’ve published a summary of the Community Call on this topic, written by the speakers, Hao Ye, Melanie Frazier, Julia Stewart-Lowndes, Carl Boettiger, and rOpenSci software peer review editor Noam Ross!