# Artificial Intelligence in Open Source Software Engineering: A Foundation for Sustainability

arXiv: https://arxiv.org/abs/2602.07071 · HTML: https://mlsanity.com/paper/2602.07071/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 25 of its 50 references that are in the map.
- First posted on arXiv 5 Feb 2026.

## Builds on (most cited first, 25 of 25)

- [Sustainable AI: Environmental Implications, Challenges and Opportunities](https://mlsanity.com/paper/2111.00364/) (2021)
- [Perfection Not Required? Human-AI Partnerships in Code Translation](https://mlsanity.com/paper/2104.03820/) (2021)
- [Trustworthy and Synergistic Artificial Intelligence for Software Engineering: Vision and Roadmaps](https://mlsanity.com/paper/2309.04142/) (2023)
- [The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot](https://mlsanity.com/paper/2410.02091/) (2024)
- [Challenges and Paths Towards AI for Software Engineering](https://mlsanity.com/paper/2503.22625/) (2025)
- [Making Online Communities 'Better': A Taxonomy of Community Values on Reddit](https://mlsanity.com/paper/2109.05152/) (2021)
- [Generative AI and Empirical Software Engineering: A Paradigm Shift](https://mlsanity.com/paper/2502.08108/) (2025)
- [Beyond Efficiency: Scaling AI Sustainably](https://mlsanity.com/paper/2406.05303/) (2024)
- [A Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges](https://mlsanity.com/paper/2205.03824/) (2022)
- [Emoji Promotes Developer Participation and Issue Resolution on GitHub](https://mlsanity.com/paper/2308.16360/) (2023)
- [Fixing Security Vulnerabilities with AI in OSS-Fuzz](https://mlsanity.com/paper/2411.03346/) (2024)
- [The application of artificial intelligence in software engineering: a review challenging conventional wisdom](https://mlsanity.com/paper/2108.01591/) (2021)
- [AI in Software Engineering: A Survey on Project Management Applications](https://mlsanity.com/paper/2307.15224/) (2023)
- [Open-Source AI-based SE Tools: Opportunities and Challenges of Collaborative Software Learning](https://mlsanity.com/paper/2404.06201/) (2024)
- [Innovating for Tomorrow: The Convergence of SE and Green AI](https://mlsanity.com/paper/2406.18142/) (2024)
- [Free Open Source Communities Sustainability: Does It Make a Difference in Software Quality?](https://mlsanity.com/paper/2402.06916/) (2024)
- [Balancing Progress and Responsibility: A Synthesis of Sustainability Trade-Offs of AI-Based Systems](https://mlsanity.com/paper/2404.03995/) (2024)
- [SuperCode: Sustainability PER AI-driven CO-DEsign](https://mlsanity.com/paper/2412.08490/) (2024)
- [Data and System Perspectives of Sustainable Artificial Intelligence](https://mlsanity.com/paper/2501.07487/) (2025)
- [Reddit Rules and Rulers: Quantifying the Link Between Rules and Perceptions of Governance across Thousands of Communities](https://mlsanity.com/paper/2501.14163/) (2025)
- [How to Sustain a Scientific Open-Source Software Ecosystem: Learning from the Astropy Project](https://mlsanity.com/paper/2402.15081/) (2024)
- [Addressing Sustainability-IN Software Challenges](https://mlsanity.com/paper/2406.07380/) (2024)
- [Software Solutions for Newcomers' Onboarding in Software Projects: A Systematic Literature Review](https://mlsanity.com/paper/2408.15989/) (2024)
- [CROSS: A Contributor-Project Interaction Lifecycle Model for Open Source Software](https://mlsanity.com/paper/2409.08267/) (2024)
- [Revolutionizing Newcomers' Onboarding Process in OSS Communities: The Future AI Mentor](https://mlsanity.com/paper/2505.04277/) (2025)

## Built on by (most cited first, 1 of 1)

- [Trust but Verify? Uncovering the Security Debt of Autonomous Coding Agents](https://mlsanity.com/paper/2607.12428/) (2026)

## Abstract (arXiv)

Open-source software (OSS) is foundational to modern digital infrastructure, yet this context for group work continues to struggle to ensure sufficient contributions in many critical cases. This literature review explores how artificial intelligence (AI) is being leveraged to address critical challenges to OSS sustainability, including maintaining contributor engagement, securing funding, ensuring code quality and security, fostering healthy community dynamics, and preventing project abandonment. Synthesizing recent interdisciplinary research, the paper identifies key applications of AI in this domain, including automated bug triaging, system maintenance, contributor onboarding and mentorship, community health analytics, vulnerability detection, and task automation. The review also examines the limitations and ethical concerns that arise from applying AI in OSS contexts, including data availability, bias and fairness, transparency, risks of misuse, and the preservation of human-centered values in collaborative development. By framing AI not as a replacement but as a tool to augment human infrastructure, this study highlights both the promise and pitfalls of AI-driven interventions. It concludes by identifying critical research gaps and proposing future directions at the intersection of AI, sustainability, and OSS, aiming to support more resilient and equitable open-source ecosystems.