On the Impact of Programming Languages on Code Quality
This is an incremental reproduction study that challenges prior claims about programming language impact on software defects for researchers and practitioners.
This paper reproduces and reanalyzes a previous study that claimed programming languages affect code quality, finding that only four languages show statistically significant associations with defects and the effect sizes are very small, undermining the original conclusions.
This paper is a reproduction of work by Ray et al. which claimed to have uncovered a statistically significant association between eleven programming languages and software defects in projects hosted on GitHub. First we conduct an experimental repetition, repetition is only partially successful, but it does validate one of the key claims of the original work about the association of ten programming languages with defects. Next, we conduct a complete, independent reanalysis of the data and statistical modeling steps of the original study. We uncover a number of flaws that undermine the conclusions of the original study as only four languages are found to have a statistically significant association with defects, and even for those the effect size is exceedingly small. We conclude with some additional sources of bias that should be investigated in follow up work and a few best practice recommendations for similar efforts.