  Issue tracking systems serve as the primary tool for incorporating external
users and customizing a software project to meet the users' requirements.
However, the limited number of contributors and the challenge of identifying
the best approach for each issue often impede effective resolution. Recently,
an increasing number of developers are turning to AI tools like ChatGPT to
enhance problem-solving efficiency. While previous studies have demonstrated
the potential of ChatGPT in areas such as automatic program repair, debugging,
and code generation, there is a lack of study on how developers explicitly
utilize ChatGPT to resolve issues in their tracking system. Hence, this study
aims to examine the interaction between ChatGPT and developers to analyze their
prevalent activities and provide a resolution. In addition, we assess the code
reliability by confirming if the code produced by ChatGPT was integrated into
the project's codebase using the clone detection tool NiCad. Our investigation
reveals that developers mainly use ChatGPT for brainstorming solutions but
often opt to write their code instead of using ChatGPT-generated code, possibly
due to concerns over the generation of "hallucinated code", as highlighted in
the literature.
