TY - GEN
T1 - Utilizing a multi-developer network-based developer recommendation algorithm to fix bugs effectively
AU - Yang, Geunseok
AU - Zhang, Tao
AU - Lee, Byungjeong
PY - 2014
Y1 - 2014
N2 - Recently, bug fixing has become an important part of software maintenance. In large-scale projects, developers rely on bug reports to guide any bug-fixing activities. Due to a great number of bug reports submitted into the bug repository, the workload of the triagers who are responsible for arranging developers to fix the given bugs is very high. In order to reduce the triagers' workload, a number of approaches (e.g., machine learning algorithms and social network metrics) were proposed to study who should fix the bug report. In this study, we propose a novel algorithm for developer recommendation. We first introduce a component and a similar bug-based selection process to verify the candidate fixers, then by adopting the number of comments and commits, we construct a multi-developer network so that ranking these candidates for finding the most appropriate fixer to resolve the given bug. In order to evaluate our work, we measured the effectiveness of our approach based on 3,008 bug reports from the JBoss Issue bug repository. We also compared the proposed approach to three previous studies. The result shows that our approach performs the task of bug triage effectively.
AB - Recently, bug fixing has become an important part of software maintenance. In large-scale projects, developers rely on bug reports to guide any bug-fixing activities. Due to a great number of bug reports submitted into the bug repository, the workload of the triagers who are responsible for arranging developers to fix the given bugs is very high. In order to reduce the triagers' workload, a number of approaches (e.g., machine learning algorithms and social network metrics) were proposed to study who should fix the bug report. In this study, we propose a novel algorithm for developer recommendation. We first introduce a component and a similar bug-based selection process to verify the candidate fixers, then by adopting the number of comments and commits, we construct a multi-developer network so that ranking these candidates for finding the most appropriate fixer to resolve the given bug. In order to evaluate our work, we measured the effectiveness of our approach based on 3,008 bug reports from the JBoss Issue bug repository. We also compared the proposed approach to three previous studies. The result shows that our approach performs the task of bug triage effectively.
KW - Bug fixing
KW - Bug triage
KW - Developer recommendation
KW - Multi-developer network
KW - Software maintenance
UR - http://www.scopus.com/inward/record.url?scp=84905639732&partnerID=8YFLogxK
U2 - 10.1145/2554850.2555008
DO - 10.1145/2554850.2555008
M3 - Conference contribution
AN - SCOPUS:84905639732
SN - 9781450324694
T3 - Proceedings of the ACM Symposium on Applied Computing
SP - 1134
EP - 1139
BT - Proceedings of the 29th Annual ACM Symposium on Applied Computing, SAC 2014
PB - Association for Computing Machinery
T2 - 29th Annual ACM Symposium on Applied Computing, SAC 2014
Y2 - 24 March 2014 through 28 March 2014
ER -