Good enough practices in scientific computing

One thing they mentioned in the 'left out' section is code review. I'm a researcher in a computation-heavy field and I think that anything I write that is intended to be used in our research group or used by other people should be code reviewed. In my experience, so many codes written by former group members or by senior group members become blackboxes that no one can read or maintain in five years.

Code review for anything more complicated than a script has helped the quality of what I write. It also ensures that there are other people who have at least seen the code that I wrote. Even if they don't fully understand it, they are at least empowered enough to wade through it if need be.

Oh, those citations:

> ... you have to explain the difference between plain text and word processing. And text editors. And Markdown/LaTeX compilers. And BiBTeX. And Git. ... the barrier to collaborating on papers in this framework is simply too high to overcome. Good intentions aside, it always comes down to, "just give me a Word document with tracked changes"

> ... Google Docs excels at easy sharing, collaboration, simultaneous editing, commenting, and reply-to-commenting.

Using google docs is not "good enough" practice for scientific computing. How will you embed parts of your csv files in the report, how will you at the same time have it included in the version control system? Using plain text file toolchains on the other hand could solve all that. Now they mentioned Markdown and Pandoc, but no mention of the ReStructuredText, Orgmode files or Asciidocs, so it makes me wonder why would they recommend version control and google docs?

related: https://www.practicereproducibleresearch.org/