TY - JOUR
T1 - The power of bots
T2 - Understanding bots in OSS projects
AU - Wessel, Mairieli
AU - De Souza, Bruno Mendes
AU - Steinmacher, Igor
AU - Wiese, Igor S.
AU - Polato, Ivanilton
AU - Chaves, Ana Paula
AU - Gerosa, Marco A.
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/11
Y1 - 2018/11
N2 - Leveraging the pull request model of social coding platforms, Open Source Software (OSS) integrators review developers' contributions, checking aspects like license, code quality, and testability. Some projects use bots to automate predened, sometimes repetitive tasks, thereby assisting integrators' and contributors' work. Our research investigates the usage and impact of such bots. We sampled 351 popular projects from GitHub and found that 93 (26%) use bots. We classied the bots, collected metrics from before and after bot adoption, and surveyed 228 developers and integrators. Our results indicate that bots perform numerous tasks. Although integrators reported that bots are useful for maintenance tasks, we did not nd a consistent, statistically signicant dierence between before and after bot adoption across the analyzed projects in terms of number of comments, commits, changed les, and time to close pull requests. Our survey respondents deem the current bots as not smart enough and provided insights into the bots' relevance for specic tasks, challenges, and potential new features. We discuss some of the raised suggestions and challenges in light of the literature in order to help GitHub bot designers reuse and test ideas and technologies already investigated in other contexts.
AB - Leveraging the pull request model of social coding platforms, Open Source Software (OSS) integrators review developers' contributions, checking aspects like license, code quality, and testability. Some projects use bots to automate predened, sometimes repetitive tasks, thereby assisting integrators' and contributors' work. Our research investigates the usage and impact of such bots. We sampled 351 popular projects from GitHub and found that 93 (26%) use bots. We classied the bots, collected metrics from before and after bot adoption, and surveyed 228 developers and integrators. Our results indicate that bots perform numerous tasks. Although integrators reported that bots are useful for maintenance tasks, we did not nd a consistent, statistically signicant dierence between before and after bot adoption across the analyzed projects in terms of number of comments, commits, changed les, and time to close pull requests. Our survey respondents deem the current bots as not smart enough and provided insights into the bots' relevance for specic tasks, challenges, and potential new features. We discuss some of the raised suggestions and challenges in light of the literature in order to help GitHub bot designers reuse and test ideas and technologies already investigated in other contexts.
KW - Automated agents
KW - Bots
KW - Chatbots
KW - Open source software
KW - Pull request
KW - Pull-based model
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U2 - 10.1145/3274451
DO - 10.1145/3274451
M3 - Article
AN - SCOPUS:85064157845
SN - 2573-0142
VL - 2
JO - Proceedings of the ACM on Human-Computer Interaction
JF - Proceedings of the ACM on Human-Computer Interaction
IS - CSCW
M1 - 182
ER -