Intuitionistic Fuzzy Set Based Ensemble Approaches for Software Bug Triaging

Modern-day software is developed by multiple developers working remotely in various locations. Software bugs emerge in large numbers during the maintenance of software. Understanding these bugs and identifying suitable developers to fix these bugs are the most important tasks for the triager. However, a bug can occur for multiple reasons, and multiple developers may be involved in its creation. To address the aforementioned problems and improve the bug triaging process, intuitionistic fuzzy set-based ensemble bug triaging models are developed in this paper using the intuitionistic fuzzy similarity measures (IFSM) of the developer on the terms, categories, and topics associated with software bugs. The proposed ensemble techniques outperform other bug triaging techniques across multiple available software bug repositories and are able to identify suitable developers to fix the bugs with the highest accuracy of 0.947 and the highest F-measure of 0.944.