Published: July 10, 2025
Code quality is what typically comes to mind when talking about "good packages". Does that package pass standard checks? What is the Unit test coverage? How many dependencies does the package have? This post discusses how we use code quality when determining the package litmus score.
Published: July 3, 2025
Not all R packages are clearly “good” or “risky”, most fall somewhere in between. This post introduces our scoring framework around package documentation. We investigate the different measures, then look at a few well known packages.
Published: June 26, 2025
The popularity of an R package can be measured using package downloads and reverse dependencies. While these measures clearly have issues, they do provide a good indication of the package health. This post looks at these measures in more detail.
Published: June 19, 2025
Not all R packages are clearly “good” or “risky”, most fall somewhere in between. This post introduces a scoring framework to help users assess package quality, based on documentation, code, maintenance, and popularity. We also share key principles to ensure the scores are useful, fair, and adaptable to different contexts.
