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.

翻译：背景：尽管关于软件机器人对开源软件开发团队影响的文献日益增多，但其对团队沟通、协调及协作实践的影响机制尚不明确。机器人可能带来信息过载或开发者间互动减少等负面后果。目标：本研究旨在通过网络分析方法，探究特定GitHub Actions对开源软件团队协作网络的影响。研究聚焦于最常被实施的机器人类型——代码审查机器人。方法：将从大规模GitHub代码库样本中获取细粒度时间戳数据，包括协同编辑网络、开发者-文件贡献网络、工作流执行记录及Git提交日志。通过这些数据可研究机器人如何随时间影响开发者协作网络。相较于以往研究，本实验采用更具代表性的GitHub代码库样本（涵盖完整规模范围的开源社区项目），从而获得关于GitHub Actions整体使用情况与分布模式的普适性结论及最新发现。本研究旨在深化对人机交互机制及支持工具对软件工程团队影响效应的认知。