TY - GEN
T1 - Predicting severity of bug report by mining bug repository with concept profile
AU - Zhang, Tao
AU - Yang, Geunseok
AU - Lee, Byungjeong
AU - Chan, Alvin T.S.
N1 - Publisher Copyright:
Copyright 2015 ACM.
PY - 2015/4/13
Y1 - 2015/4/13
N2 - Recently, for large scale software projects, developers rely on bug reports for corrective software maintenance. The severity of a reported bug is an important feature to decide how fast it needs to be fixed. Therefore, to arrange a new submitted bug to an appropriate fixer, it is necessary to recognize the severity of each bug report. Unfortunately, reporters need to decide the severity of bugs manually. Even if there are guidelines on how to verify the severity of a bug, it is still a time-consuming work. Utilizing the concept profiles by mining bug repositories is a good way to resolve this problem. In this paper, we propose a concept profile-based prediction technique to assign the severity of a given bug. In detail, we analyze historical bug reports in the bug repositories and build the concept profiles from them. We evaluate the performance of our method on the bug reports from the bug repositories of popular open-source projects that include Eclipse and Mozilla Firefox, the result shows that the proposed technique can effectively predict the severity of a given bug.
AB - Recently, for large scale software projects, developers rely on bug reports for corrective software maintenance. The severity of a reported bug is an important feature to decide how fast it needs to be fixed. Therefore, to arrange a new submitted bug to an appropriate fixer, it is necessary to recognize the severity of each bug report. Unfortunately, reporters need to decide the severity of bugs manually. Even if there are guidelines on how to verify the severity of a bug, it is still a time-consuming work. Utilizing the concept profiles by mining bug repositories is a good way to resolve this problem. In this paper, we propose a concept profile-based prediction technique to assign the severity of a given bug. In detail, we analyze historical bug reports in the bug repositories and build the concept profiles from them. We evaluate the performance of our method on the bug reports from the bug repositories of popular open-source projects that include Eclipse and Mozilla Firefox, the result shows that the proposed technique can effectively predict the severity of a given bug.
KW - Bug report
KW - Bug triage
KW - Concept profile
KW - Mining bug repository
KW - Severity prediction
KW - Software maintenance
UR - http://www.scopus.com/inward/record.url?scp=84955458298&partnerID=8YFLogxK
U2 - 10.1145/2695664.2695872
DO - 10.1145/2695664.2695872
M3 - Conference contribution
AN - SCOPUS:84955458298
T3 - Proceedings of the ACM Symposium on Applied Computing
SP - 1553
EP - 1558
BT - 2015 Symposium on Applied Computing, SAC 2015
A2 - Shin, Dongwan
PB - Association for Computing Machinery
T2 - 30th Annual ACM Symposium on Applied Computing, SAC 2015
Y2 - 13 April 2015 through 17 April 2015
ER -