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Locating bugs without looking back

Dilshener, Tezcan; Wermelinger, Michel and Yu, Yijun (2017). Locating bugs without looking back. Automated Software Engineering (Early view).

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DOI (Digital Object Identifier) Link: https://doi.org/10.1007/s10515-017-0226-1
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Abstract

Bug localisation is a core program comprehension task in software maintenance: given the observation of a bug, e.g. via a bug report, where is it located in the source code? Information retrieval (IR) approaches see the bug report as the query, and the source code files as the documents to be retrieved, ranked by relevance. Such approaches have the advantage of not requiring expensive static or dynamic analysis of the code. However, current state-of-the-art IR approaches rely on project history, in particular previously fixed bugs or previous versions of the source code. We present a novel approach that directly scores each current file against the given report, thus not requiring past code and reports. The scoring method is based on heuristics identified through manual inspection of a small sample of bug reports. We compare our approach to eight others, using their own five metrics on their own six open source projects. Out of 30 performance indicators, we improve 27 and equal 2. Over the projects analysed, on average we find one or more affected files in the top 10 ranked files for 76% of the bug reports. These results show the applicability of our approach to software projects without history.

Item Type: Journal Item
Copyright Holders: 2017 The Authors
ISSN: 1573-7535
Keywords: bug localisation; information retrieval; empirical study; software maintenance
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Centre for Policing Research and Learning (CPRL)
Item ID: 51576
Depositing User: Michel Wermelinger
Date Deposited: 16 Oct 2017 09:58
Last Modified: 16 Oct 2017 10:07
URI: http://oro.open.ac.uk/id/eprint/51576
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