Bug triaging aims to assign a bug to the most appropriate fixer. That task is crucial in reducing time and efforts in a bug fixing process. In this paper, we propose Bugzie, a novel approach for automatic bug triaging based on fuzzy set and cache-based modeling of the bug-fixing expertise of developers. Bugzie considers a software system to have multiple technical aspects, each of which is associated with technical terms. For each technical term, it uses a fuzzy set to represent the developers who are capable/competent of fixing the bugs relevant to the corresponding aspect. The fixing correlation of a developer toward a technical term is represented by his/her membership score toward the corresponding fuzzy set. The score is calculated based on the bug reports that (s)he has fixed, and is updated as the newly fixed bug reports are available. For a new bug report, Bugzie combines the fuzzy sets corresponding to its terms and ranks the developers based on their membership scores toward that combined fuzzy set to find the most capable fixers. Our empirical results show that Bugzie achieves significantly higher accuracy and time efficiency than existing state-of-the-art approaches.
Tamrawi et al. REF , on the other hand, employed fuzzy sets to model bug-fixing expertise of developers such that developers who recently fixed bugs are more likely to fix similar bugs in the near future.
Fuzzy set and cache-based approach for bug triaging
ESEC/FSE '11
Computer Science