An Empirical Study on Developers Shared Conversations with ChatGPT in GitHub Pull Requests and Issues
CoRR(2024)
摘要
ChatGPT has significantly impacted software development practices, providing
substantial assistance to developers in a variety of tasks, including coding,
testing, and debugging. Despite its widespread adoption, the impact of ChatGPT
as an assistant in collaborative coding remains largely unexplored. In this
paper, we analyze a dataset of 210 and 370 developers shared conversations with
ChatGPT in GitHub pull requests (PRs) and issues. We manually examined the
content of the conversations and characterized the dynamics of the sharing
behavior, i.e., understanding the rationale behind the sharing, identifying the
locations where the conversations were shared, and determining the roles of the
developers who shared them. Our main observations are: (1) Developers seek
ChatGPT assistance across 16 types of software engineering inquiries. In both
conversations shared in PRs and issues, the most frequently encountered inquiry
categories include code generation, conceptual questions, how-to guides, issue
resolution, and code review. (2) Developers frequently engage with ChatGPT via
multi-turn conversations where each prompt can fulfill various roles, such as
unveiling initial or new tasks, iterative follow-up, and prompt refinement.
Multi-turn conversations account for 33.2
and 36.9
conversations with ChatGPT to facilitate their role-specific contributions,
whether as authors of PRs or issues, code reviewers, or collaborators on
issues. Our work serves as the first step towards understanding the dynamics
between developers and ChatGPT in collaborative software development and opens
up new directions for future research on the topic.
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