DocumentCode
3406857
Title
A contextual approach towards more accurate duplicate bug report detection
Author
Alipour, Anahita ; Hindle, Adrian ; Stroulia, Eleni
Author_Institution
Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
fYear
2013
fDate
18-19 May 2013
Firstpage
183
Lastpage
192
Abstract
Bug-tracking and issue-tracking systems tend to be populated with bugs, issues, or tickets written by a wide variety of bug reporters, with different levels of training and knowledge about the system being discussed. Many bug reporters lack the skills, vocabulary, knowledge, or time to efficiently search the issue tracker for similar issues. As a result, issue trackers are often full of duplicate issues and bugs, and bug triaging is time consuming and error prone. Many researchers have approached the bug-deduplication problem using off-the-shelf information-retrieval tools, such as BM25F used by Sun et al. In our work, we extend the state of the art by investigating how contextual information, relying on our prior knowledge of software quality, software architecture, and system-development (LDA) topics, can be exploited to improve bug-deduplication. We demonstrate the effectiveness of our contextual bug-deduplication method on the bug repository of the Android ecosystem. Based on this experience, we conclude that researchers should not ignore the context of software engineering when using IR tools for deduplication.
Keywords
Linux; information retrieval; program debugging; software architecture; software quality; Android ecosystem; IR tools; LDA topics; bug repository; contextual bug-deduplication method; contextual information; duplicate bug report detection; information-retrieval tools; software architecture; software engineering; software quality; system-development; Accuracy; Androids; Computer bugs; Context; Humanoid robots; Software; Sun; contextual information; deduplication; duplicate bug reports; information retrieval; machine learning; textual similarity; triaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Mining Software Repositories (MSR), 2013 10th IEEE Working Conference on
Conference_Location
San Francisco, CA
ISSN
2160-1852
Print_ISBN
978-1-4799-0345-0
Type
conf
DOI
10.1109/MSR.2013.6624026
Filename
6624026
Link To Document