# Don't Disturb Me: Challenges of Interacting with SoftwareBots on Open Source Software Projects

arXiv: https://arxiv.org/abs/2103.13950 · HTML: https://mlsanity.com/paper/2103.13950/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Mar 2021.

## Built on by (most cited first, 8 of 8)

- [AIDev: Studying AI Coding Agents on GitHub](https://mlsanity.com/paper/2602.09185/) (2026)
- [Motivations, Challenges, Best Practices, and Benefits for Bots and Conversational Agents in Software Engineering: A Multivocal Literature Review](https://mlsanity.com/paper/2409.11864/) (2024)
- [Predicting the First Response Latency of Maintainers and Contributors in Pull Requests](https://mlsanity.com/paper/2311.07786/) (2023)
- [On the Utility of Domain Modeling Assistance with Large Language Models](https://mlsanity.com/paper/2410.12577/) (2024)
- [Understanding the Helpfulness of Stale Bot for Pull-based Development: An Empirical Study of 20 Large Open-Source Projects](https://mlsanity.com/paper/2305.18150/) (2023)
- [Trust Calibration in IDEs: Paving the Way for Widespread Adoption of AI Refactoring](https://mlsanity.com/paper/2412.15948/) (2024)
- [Beyond Simpson's Paradox: A Cascade of Confounders in AI Agent Pull-Request Co-Authorship](https://mlsanity.com/paper/2606.22711/) (2026)
- [Govern the Repository, Not the Agent: Measuring Ecosystem-Level Risk in AI-Native Software](https://mlsanity.com/paper/2606.28235/) (2026)

## 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.