The emergence of large language models (LLMs) such as ChatGPT has disrupted
the landscape of software development. Many studies are investigating the
quality of responses generated by ChatGPT, the efficacy of various prompting
techniques, and its comparative performance in programming contests, to name a
few examples. Yet, we know very little about how ChatGPT is actually used by
software developers. What questions do developers present to ChatGPT? What are
the dynamics of these interactions? What is the backdrop against which these
conversations are held, and how do the conversations feedback into the
artifacts of their work? To close this gap, we introduce DevGPT, a curated
dataset which encompasses 17,913 prompts and ChatGPT's responses including
11,751 code snippets, coupled with the corresponding software development
artifacts -- ranging from source code, commits, issues, pull requests, to
discussions and Hacker News threads -- to enable the analysis of the context
and implications of these developer interactions with ChatGPT.Comment: MSR 2024 Mining Challenge Proposa