What metrics would help you identify packages? (Either from a "trust"; perspective or a "usefulness" perspective?)
R users and admins face a discoverability crisis. With more than 12K packages, how can you decide which packages to use and trust? In RStudio Package Manager we're hoping to help new users discover packages by tracking which packages are used:
However, we'd also like to provide metrics for packages that aren't in the organization yet. There has been some interesting work in this space (here, here, and here). We've also got some ideas of our own, adding badges based on a package’s download frequency, the presence of vignettes and tests, and code coverage.
Those are good questions. The last one especially is something I look for when comparing two packages that do the same thing. If I use an abandoned package and happen to find a problem for my use case, any changes I make (via forking, fixing, and making a pull request) are unlikely to get into the package.
I think you are going to struggle to do this in an automated way. Just glancing at the packagemetrics page in the link, for example, it determines whether continuous integration is being used by looking whether the travis or appveyor badge icons are present! This gives the wrong answer, even in the example it advertises (and I've seen the other type of error -- the presence of a badge but no continuous integration actually used -- too).
If I don’t know the developer, I’ll look at downloads, and issues. If a package seems popular, and the outstanding issues won’t harm what I’m doing, I go for it. Though often I go off recommendations from podcasts, or @mara’s twitter feed.
Eeep! For the record, I do no security profiling whatsoever. Not that any security investigation I did would be worth much, but wanted to put that out there, FWIW.
Most of the important qualities can't be automatically measured:
How easy is it to use?
Does it work well with other packages?
Does it have good documentation (official and unofficial)?
Can I extend it?
A collection of user reviews would be nice. To help people winnow down to likely winners, let people rate packages in different categories. They can decide what's important, get a short list, and read the reviews.