A Network Perspective on the Influence of Code Review Bots on the Structure of Developer Collaborations (2304.14787v2)

Abstract: Background: Despite a growing body of literature on the impact of software bots on open source software development teams, their effects on team communication, coordination, and collaboration practices are not well understood. Bots can have negative consequences, such as producing information overload or reducing interactions between developers. Objective: The objective of this study is to investigate the effect of specific GitHub Actions on the collaboration networks of Open Source Software teams, using a network-analytic approach. The study will focus on Code Review bots, one of the most frequently implemented types of bots. Method: Fine-grained, time-stamped data of co-editing networks, developer-file contribution networks, as well as workflow runs and git commit logs will be obtained from a large sample of GitHub repositories. This will allow us to study how bots affect the collaboration networks of developers over time. By using a more representative sample of GitHub repositories than previous studies, which includes projects whose sizes span the whole range of Open Source communities, this study will provide generalizable results and updated findings on the general usage and distribution of GitHub Actions. With this study, we aim to contribute to advancing our knowledge of human-bot interaction and the effects of support tools on software engineering teams.