NDLI: An approach to detecting duplicate bug reports using natural language and execution information

Content Provider	IEEE Xplore Digital Library
Author	Xiaoyin Wang Lu Zhang Tao Xie Anvik, J. Jiasu Sun
Copyright Year	2008
Description	Author affiliation: Inst. of Software, Peking Univ., Beijing (Xiaoyin Wang; Lu Zhang; Jiasu Sun) \|\| Dept. of Comput. Sci., North Carolina State Univ., Raleigh, NC (Tao Xie) \|\| Dept. of Comput. Sci., Univ. of Victoria, Victoria, BC (Anvik, J.)
Abstract	An open source project typically maintains an open bug repository so that bug reports from all over the world can be gathered. When a new bug report is submitted to the repository, a person, called a triager, examines whether it is a duplicate of an existing bug report. If it is, the triager marks it as duplicate and the bug report is removed from consideration for further work. In the literature, there are approaches exploiting only natural language information to detect duplicate bug reports. In this paper we present a new approach that further involves execution information. In our approach, when a new bug report arrives, its natural language information and execution information are compared with those of the existing bug reports. Then, a small number of existing bug reports are suggested to the triager as the most similar bug reports to the new bug report. Finally, the triager examines the suggested bug reports to determine whether the new bug report duplicates an existing bug report. We calibrated our approach on a subset of the Eclipse bug repository and evaluated our approach on a subset of the Firefox bug repository. The experimental results show that our approach can detect 67%-93% of duplicate bug reports in the Firefox bug repository, compared to 43%-72% using natural language information alone.
Starting Page	461
Ending Page	470
File Size	292528
Page Count	10
File Format	PDF
ISBN	9781424444861
ISSN	02705257
e-ISBN	9781605580791
DOI	10.1145/1368088.1368151
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-10
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Association for Computing Machinery, Inc. (ACM)
Subject Keyword	Natural languages Costs Software maintenance Software quality Testing Computer bugs Laboratories Educational technology Computer science education Open source software information retrieval duplicate bug report execution information
Content Type	Text
Resource Type	Article
Subject	Software

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