Enhancing supervised bug localization with metadata and stack-trace

Locating relevant source files for a given bug report is an important task in software development and maintenance. To make the locating process easier, information retrieval methods have been widely used to compute the content similarities between bug reports and source files. In addition to conten...

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Published in:	Knowledge and information systems Vol. 62; no. 6; pp. 2461 - 2484
Main Authors:	Wang, Yaojing, Yao, Yuan, Tong, Hanghang, Huo, Xuan, Li, Ming, Xu, Feng, Lu, Jian
Format:	Journal Article
Language:	English
Published:	London Springer London 01-06-2020 Springer Nature B.V
Subjects:	Accuracy Analogies Computer Science Data Mining and Knowledge Discovery Database Management Debugging Information retrieval Information Storage and Retrieval Information Systems and Communication Service Information Systems Applications (incl.Internet) IT in Business Localization Metadata Modelling Regular Paper Software development Bug reports Supervised topic modeling Metadata Bug localization Stack-trace
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Abstract	Locating relevant source files for a given bug report is an important task in software development and maintenance. To make the locating process easier, information retrieval methods have been widely used to compute the content similarities between bug reports and source files. In addition to content similarities, various other sources of information such as the metadata and the stack-trace in the bug report can be used to enhance the localization accuracy. In this paper, we propose a supervised topic modeling approach for automatically locating the relevant source files of a bug report. In our approach, we take into account the following five key observations. First, supervised modeling can effectively make use of the existing fixing histories. Second, certain words in bug reports tend to appear multiple times in their relevant source files. Third, longer source files tend to have more bugs. Fourth, metainformation brings additional guidance on the search space. Fifth, buggy source files could be already contained in the stack-trace. By integrating the above five observations, we experimentally show that the proposed method can achieve up to 67.1% improvement in terms of prediction accuracy over its best competitors and scales linearly with the size of the data.
AbstractList	Locating relevant source files for a given bug report is an important task in software development and maintenance. To make the locating process easier, information retrieval methods have been widely used to compute the content similarities between bug reports and source files. In addition to content similarities, various other sources of information such as the metadata and the stack-trace in the bug report can be used to enhance the localization accuracy. In this paper, we propose a supervised topic modeling approach for automatically locating the relevant source files of a bug report. In our approach, we take into account the following five key observations. First, supervised modeling can effectively make use of the existing fixing histories. Second, certain words in bug reports tend to appear multiple times in their relevant source files. Third, longer source files tend to have more bugs. Fourth, metainformation brings additional guidance on the search space. Fifth, buggy source files could be already contained in the stack-trace. By integrating the above five observations, we experimentally show that the proposed method can achieve up to 67.1% improvement in terms of prediction accuracy over its best competitors and scales linearly with the size of the data.
Author	Tong, Hanghang Li, Ming Xu, Feng Lu, Jian Yao, Yuan Wang, Yaojing Huo, Xuan
Author_xml	– sequence: 1 givenname: Yaojing surname: Wang fullname: Wang, Yaojing email: wyj@smail.nju.edu.cn organization: The State Key Laboratory of Novel Software Technology, Nanjing University – sequence: 2 givenname: Yuan surname: Yao fullname: Yao, Yuan organization: The State Key Laboratory of Novel Software Technology, Nanjing University – sequence: 3 givenname: Hanghang surname: Tong fullname: Tong, Hanghang organization: University of Illinois Urbana-Champaign – sequence: 4 givenname: Xuan surname: Huo fullname: Huo, Xuan organization: The State Key Laboratory of Novel Software Technology, Nanjing University – sequence: 5 givenname: Ming surname: Li fullname: Li, Ming organization: The State Key Laboratory of Novel Software Technology, Nanjing University – sequence: 6 givenname: Feng surname: Xu fullname: Xu, Feng organization: The State Key Laboratory of Novel Software Technology, Nanjing University – sequence: 7 givenname: Jian surname: Lu fullname: Lu, Jian organization: The State Key Laboratory of Novel Software Technology, Nanjing University
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Snippet	Locating relevant source files for a given bug report is an important task in software development and maintenance. To make the locating process easier,...
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SubjectTerms	Accuracy Analogies Computer Science Data Mining and Knowledge Discovery Database Management Debugging Information retrieval Information Storage and Retrieval Information Systems and Communication Service Information Systems Applications (incl.Internet) IT in Business Localization Metadata Modelling Regular Paper Software development
Title	Enhancing supervised bug localization with metadata and stack-trace
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