In software development projects, bugs are common phenomena. Developers report bugs in open source repositories. There is a need to develop high quality developer prediction model that considers developer work satisfaction, keep within limited development cost, and improve bug resolution time. To address and resolve bug report as soon as possible is the main focus of triager when a new bug is reported. Thus, developer work efficiency is an important factor in bug-fixing. To address these issues, a proposed approach recommends a set of developers that could potentially share their knowledge with each other to fix new bug reports. The proposed approach is called developer working efficiency and social network based developer recommendation (DweSn). It is a composite model that builds developers’ profile by using developer average bug fixing time, work efficiency to fix variety of bugs, as well as the developer’s social interactions with other developers. A similarity measure is applied between new bug and bugs in corpus to extract the list of capable developers from the corpus. The proposed approach only selects those developers who are active and less loaded with work. The developer with the highest profile score is assigned the bugs. We evaluated our approach on the subset of five large open-source projects including Mozilla, Netbeans, Eclipse, Firefox and OpenOffice, and compared it with the state-of-the-art. The results demonstrate that combination of developers’ efficiency with their average bug fixing time and interactions in their social network gives good accuracy and efficiently reduces bug tossing length. This approach shows an improvement in prediction accuracy, precision, recall, F-score and reduced bug tossing length up to 93.89%, 93.12%, 93.46%, 93.27% and 93.25%, respectively. The proposed approach achieved a 93% hit ratio and 93.34% mean reciprocal rank, indicating that our proposed triager is able to efficiently assign bugs to correct developers.
YADAV Asmita1*, SINGH Kumar Sandeep1，2
. Automated Time Based Multi-Criteria Bug Triage Approach: Developer Working Efficiency and Social Network Based Developer Recommendation[J]. Journal of Shanghai Jiaotong University(Science), 2024
, 29(3)
: 566
-578
.
DOI: 10.1007/s12204-022-2448-z
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