AI slop cut first-time contributor merge rates 18.18% across 294 repos
A new study shows that low-quality AI-generated contributions, termed "AI-DDoS," are overwhelming open source communities. Analyzing 294 repositories with over 2 million pull requests and issues, the study found that while PR volume increased in 2025, merge rates declined, with first-time contributors experiencing an 18.18% drop in merge rates relative to the counterfactual. The research also identified 11 remediation strategies.
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[Submitted on 4 Jul 2026]
Title:"AI Slop is DDoSing Open Source": Understanding the Impact of AI-Generated Contributions on Open Source Sustainability
View a PDF of the paper titled "AI Slop is DDoSing Open Source": Understanding the Impact of AI-Generated Contributions on Open Source Sustainability, by Sadia Afroz and 5 other authors
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Abstract:Open source software (OSS) communities are facing increasing pressure from Generative AI (GenAI) tools. We call it AI-DDoS: a denial-of-service effect in which plausible but low-quality AI-generated contributions overwhelm OSS community capacity. Using a phenomenon-based mixed-methods approach, we first analyze practitioner accounts from Reddit, OSS mentor mailing lists, and blogs to identify six recurring themes and derive hypotheses. We then evaluate these hypotheses using Bayesian Structural Time Series analysis across 294 repositories with over 2 million pull requests and issues. Our results show that while PR volume increased in 2025, merge rates declined, with one-time contributors experiencing an 18.18% drop in PR merge rates relative to the counterfactual. Finally, we identify 11 remediation strategies through practitioners' interviews and validate them with a survey of 229 OSS practitioners, grouping them into preservative, adaptive, and transformative orientations. Our findings show that AI-DDoS is not only a contribution-volume problem but a sustainability trap: communities often default to low-effort defensive strategies that protect short-term review capacity while making openness difficult to sustain.
Subjects:
Software Engineering (cs.SE)
Cite as: arXiv:2607.04003 [cs.SE]
(or arXiv:2607.04003v1 [cs.SE] for this version)
https://doi.org/10.48550/arXiv.2607.04003
arXiv-issued DOI via DataCite
Submission history
From: Sadia Afroz [view email] [v1] Sat, 4 Jul 2026 19:55:11 UTC (1,510 KB)
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