Open source software projects are complex socio-technical environments open for collaboration. However, contributors often have many questions about the project’s codebase, processes, and community norms, and many communities lack the resources to answer them all. Much of the information required to answer these questions is already publicly available, scattered across software artifacts such as source code, documentation, issue trackers, commit histories, and comments. In this talk, I present our group’s research aimed at helping developers find answers to their questions in natural language, including the development of a chatbot powered by an RAG approach using large language models to provide contextual answers grounded in project artifacts and a tool that connects questions to metrics derived from repository mining techniques. I discuss the lessons learned, the challenges encountered, and the implications of these approaches.

Dr. Gerosa is a Full Professor at Northern Arizona University (NAU), United States, and a member of the Computer Science Graduate Program at the University of São Paulo (USP), Brazil. He researches tools and strategies to support open source software projects and AI in Software Engineering.

Email: Marco.Gerosa@nau.edu