  This paper introduces DevGPT, a dataset curated to explore how software
developers interact with ChatGPT, a prominent large language model (LLM). The
dataset encompasses 29,778 prompts and responses from ChatGPT, including 19,106
code snippets, and is linked to corresponding software development artifacts
such as source code, commits, issues, pull requests, discussions, and Hacker
News threads. This comprehensive dataset is derived from shared ChatGPT
conversations collected from GitHub and Hacker News, providing a rich resource
for understanding the dynamics of developer interactions with ChatGPT, the
nature of their inquiries, and the impact of these interactions on their work.
DevGPT enables the study of developer queries, the effectiveness of ChatGPT in
code generation and problem solving, and the broader implications of
AI-assisted programming. By providing this dataset, the paper paves the way for
novel research avenues in software engineering, particularly in understanding
and improving the use of LLMs like ChatGPT by developers.
