Don't Disturb Me: Challenges of Interacting with SoftwareBots on Open Source Software Projects
Mairieli Wessel, Igor Wiese, Igor Steinmacher, Marco A. Gerosa
TL;DR
This study investigates how software bots in OSS pull request workflows disrupt human collaboration, revealing noise as the central challenge. Through 21 semi-structured interviews with maintainers, contributors, and bot developers, the authors develop a Noise Theory linking bot behaviors (verbosity, high frequency, unsolicited actions) to information overload and disrupted communication. They identify 25 challenges across bot development, adoption, and interaction, and offer practical countermeasures (reconfiguring, redesigning, opt-in governance) along with implications for developers, platforms, and researchers. The work highlights the socio-technical nature of bots in social coding platforms and provides a foundation for designing more human-centered, governance-aware bot ecosystems with reduced information overload and clearer interaction semantics.
Abstract
Software bots are used to streamline tasks in Open Source Software (OSS) projects' pull requests, saving development cost, time, and effort. However, their presence can be disruptive to the community. We identified several challenges caused by bots in pull request interactions by interviewing 21 practitioners, including project maintainers, contributors, and bot developers. In particular, our findings indicate noise as a recurrent and central problem. Noise affects both human communication and development workflow by overwhelming and distracting developers. Our main contribution is a theory of how human developers perceive annoying bot behaviors as noise on social coding platforms. This contribution may help practitioners understand the effects of adopting a bot, and researchers and tool designers may leverage our results to better support human-bot interaction on social coding platforms.