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

TL;DR

This paper reviews how artificial intelligence can enhance the sustainability of open-source software by addressing key challenges like contributor engagement, security, and community health, while also discussing ethical concerns and future research directions.

Contribution

It provides a comprehensive synthesis of recent AI applications in OSS sustainability, highlighting key opportunities, limitations, and ethical considerations for future research.

Findings

AI enables automated bug triaging and system maintenance.

AI tools support contributor onboarding and community analytics.

Limitations include data bias, transparency issues, and ethical concerns.

Abstract

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.