ASE2024
ChatBR: Automated assessment and improvement of bug report quality using ChatGPT
Lili Bo, Wangjie Ji, Xiaobing Sun, Ting Zhang, Xiaoxue Wu, Ying Wei
被引用 5 次
摘要
Bug reports, containing crucial information such as the Observed Behavior (OB), the Expected Behavior (EB), and the Steps to Reproduce (S2R), can help developers localize and fix bugs efficiently. However, due to the increasing complexity of some bugs and the limited experience of some reporters, large numbers of bug reports miss this crucial information. Although machine learning (ML)-based and information retrieval (IR)-based approaches are proposed to detect and supplement the missing information in bug reports, the performance of these approaches depends heavily on the size and quality of bug report datasets.