A Computational Analysis of the Dynamics of R Style Based on 108 Million Lines of Code from All CRAN Packages in the Past 21 Years

Abstract

The flexibility of R and the diversity of the R community leads to a large number of programming styles applied in R packages. We have analyzed 108 million lines of R code from CRAN and quantified the evolution in popularity of 12 style-elements from 1998 to 2019. We attribute 3 main factors that drive changes in programming style: the effect of style-guides, the effect of introducing new features, and the effect of editors. We observe in the data that a consensus in programming style is forming, such as using lower snake case for function names (e.g. softplus_func) and \<- rather than = for assignment.