BugMiner: Software reliability analysis via data mining of bug reports

Leon Wu, Boyi Xie, Gail Kaiser, Rebecca Jane Passonneau

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Software bugs reported by human users and automatic error reporting software are often stored in some bug tracking tools (e.g., Bugzilia and Debbugs). These accumulated bug reports may contain valuable information that could be used to improve the quality of the bug reporting, reduce the quality assurance effort and cost, analyze software reliability, and predict future bug report trend. In this paper, we present BugMiner, a tool that is able to derive useful information from historic bug report database using data mining, use these information to do completion check and redundancy check on a new or given bug report, and to estimate the bug report trend using statistical analysis. Our empirical studies of the tool using several real-world bug report repositories show that it is effective, easy to implement, and has relatively high accuracy despite low quality data.

Original languageEnglish (US)
Title of host publicationSEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering
Pages95-100
Number of pages6
StatePublished - Dec 1 2011
EventSEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering - Miami, FL, United States
Duration: Jul 7 2011Jul 9 2011

Publication series

NameSEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering

Other

OtherSEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering
CountryUnited States
CityMiami, FL
Period7/7/117/9/11

All Science Journal Classification (ASJC) codes

  • Software

Fingerprint Dive into the research topics of 'BugMiner: Software reliability analysis via data mining of bug reports'. Together they form a unique fingerprint.

  • Cite this

    Wu, L., Xie, B., Kaiser, G., & Passonneau, R. J. (2011). BugMiner: Software reliability analysis via data mining of bug reports. In SEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering (pp. 95-100). (SEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering).