First Come First Served: The Impact of File Position on Code Review

TL;DR

This study investigates how the position of files in code review tools influences review activity and defect detection, revealing that earlier presented files tend to receive more comments and higher defect detection rates.

Contribution

It provides empirical evidence that file position affects review outcomes and highlights implications for improving code review tool design.

Findings

Earlier files receive more review comments.

File position impacts defect detection odds.

Participants are 64% less likely to find defects in last-position files.

Abstract

The most popular code review tools (e.g., Gerrit and GitHub) present the files to review sorted in alphabetical order. Could this choice or, more generally, the relative position in which a file is presented bias the outcome of code reviews? We investigate this hypothesis by triangulating complementary evidence in a two-step study. First, we observe developers' code review activity. We analyze the review comments pertaining to 219,476 Pull Requests (PRs) from 138 popular Java projects on GitHub. We found files shown earlier in a PR to receive more comments than files shown later, also when controlling for possible confounding factors: e.g., the presence of discussion threads or the lines added in a file. Second, we measure the impact of file position on defect finding in code review. Recruiting 106 participants, we conduct an online controlled experiment in which we measure participants' performance in detecting two unrelated defects seeded into two different files. Participants are assigned to one of two treatments in which the position of the defective files is switched. For one type of defect, participants are not affected by its file's position; for the other, they have 64% lower odds to identify it when its file is last as opposed to first. Overall, our findings provide evidence that the relative position in which files are presented has an impact on code reviews' outcome; we discuss these results and implications for tool design and code review. Data and materials: https://doi.org/10.5281/zenodo.6901285