DocumentCode
52589
Title
Automatic Summarization of Bug Reports
Author
Rastkar, Sarah ; Murphy, Gail C. ; Murray, Glen
Author_Institution
Dept. of Comput. Sci., Univ. of British Columbia, Vancouver, BC, Canada
Volume
40
Issue
4
fYear
2014
fDate
Apr-14
Firstpage
366
Lastpage
380
Abstract
Software developers access bug reports in a project´s bug repository to help with a number of different tasks, including understanding how previous changes have been made and understanding multiple aspects of particular defects. A developer´s interaction with existing bug reports often requires perusing a substantial amount of text. In this article, we investigate whether it is possible to summarize bug reports automatically so that developers can perform their tasks by consulting shorter summaries instead of entire bug reports. We investigated whether existing conversation-based automated summarizers are applicable to bug reports and found that the quality of generated summaries is similar to summaries produced for e-mail threads and other conversations. We also trained a summarizer on a bug report corpus. This summarizer produces summaries that are statistically better than summaries produced by existing conversation-based generators. To determine if automatically produced bug report summaries can help a developer with their work, we conducted a task-based evaluation that considered the use of summaries for bug report duplicate detection tasks. We found that summaries helped the study participants save time, that there was no evidence that accuracy degraded when summaries were used and that most participants preferred working with summaries to working with original bug reports.
Keywords
electronic mail; program debugging; software engineering; automatic summarization; bug report corpus; bug report duplicate detection tasks; bug report summaries; bug reports; bug repository; conversation-based automated summarizers; conversation-based generators; e-mail threads; software developers; task-based evaluation; Computer bugs; Detectors; Electronic mail; Feature extraction; Natural languages; Software; Empirical software engineering; bug report duplicate detection; summarization of software artifacts;
fLanguage
English
Journal_Title
Software Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0098-5589
Type
jour
DOI
10.1109/TSE.2013.2297712
Filename
6704866
Link To Document