NDLI: Ask the Mutants: Mutating Faulty Programs for Fault Localization

Content Provider	IEEE Xplore Digital Library
Author	Seokhyeon Moon Yunho Kim Moonzoo Kim Shin Yoo
Copyright Year	2014
Description	Author affiliation: CS Dept., KAIST, Daejeon, South Korea (Seokhyeon Moon; Yunho Kim; Moonzoo Kim) \|\| CS Dept., Univ. Coll. London, London, UK (Shin Yoo)
Abstract	We present MUSE (MUtation-baSEd fault localization technique), a new fault localization technique based on mutation analysis. A key idea of MUSE is to identify a faulty statement by utilizing different characteristics of two groups of mutants-one that mutates a faulty statement and the other that mutates a correct statement. We also propose a new evaluation metric for fault localization techniques based on information theory, called Locality Information Loss (LIL): it can measure the aptitude of a localization technique for automated fault repair systems as well as human debuggers. The empirical evaluation using 14 faulty versions of the five real-world programs shows that MUSE localizes a fault after reviewing 7.4 statements on average, which is about 25 times more precise than the state-of-the-art SBFL technique Op2.
Starting Page	153
Ending Page	162
File Size	424763
Page Count	10
File Format	PDF
ISBN	9781479922550
DOI	10.1109/ICST.2014.28
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-03-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	mutation Frequency modulation fault localization Maintenance engineering Educational institutions Loss measurement Information theory Testing
Content Type	Text
Resource Type	Article

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