Don't Disturb Me: Challenges of Interacting with SoftwareBots on Open Source Software Projects
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Abstract (arXiv)
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.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Mar 2021.
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Citing papers per year: 2023: 2; 2024: 3; 2025: 0; 2026: 3.
8 papers.
- 2026AIDev: Studying AI Coding Agents on GitHubcited by 17
- 2024Motivations, Challenges, Best Practices, and Benefits for Bots and Conversational Agents in Software Engineering: A Multivocal Literature Reviewcited by 6
- 2023Predicting the First Response Latency of Maintainers and Contributors in Pull Requestscited by 3
- 2024On the Utility of Domain Modeling Assistance with Large Language Modelscited by 3
- 2023Understanding the Helpfulness of Stale Bot for Pull-based Development: An Empirical Study of 20 Large Open-Source Projectscited by 2
- 2024Trust Calibration in IDEs: Paving the Way for Widespread Adoption of AI Refactoringcited by 1
- 2026Beyond Simpson's Paradox: A Cascade of Confounders in AI Agent Pull-Request Co-Authorshipcited by 1
- 2026Govern the Repository, Not the Agent: Measuring Ecosystem-Level Risk in AI-Native Softwarecited by 0
- 2026Govern the Repository, Not the Agent: Measuring Ecosystem-Level Risk in AI-Native Software26 Jun 2026
- 2026Beyond Simpson's Paradox: A Cascade of Confounders in AI Agent Pull-Request Co-Authorship21 Jun 2026
- 2026AIDev: Studying AI Coding Agents on GitHub9 Feb 2026
- 2024Trust Calibration in IDEs: Paving the Way for Widespread Adoption of AI Refactoring20 Dec 2024
- 2024On the Utility of Domain Modeling Assistance with Large Language Models16 Oct 2024
- 2024Motivations, Challenges, Best Practices, and Benefits for Bots and Conversational Agents in Software Engineering: A Multivocal Literature Review18 Sep 2024
- 2023Predicting the First Response Latency of Maintainers and Contributors in Pull Requests13 Nov 2023
- 2023Understanding the Helpfulness of Stale Bot for Pull-based Development: An Empirical Study of 20 Large Open-Source Projects29 May 2023