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Article: Non-parametric statistical fault localization

TitleNon-parametric statistical fault localization
Authors
KeywordsFault localization
Hypothesis testing
Non-parametric method
Parametric method
Issue Date2011
PublisherElsevier Inc. The Journal's web site is located at http://www.elsevier.com/locate/jss
Citation
Journal Of Systems And Software, 2011, v. 84 n. 6, p. 885-905 How to Cite?
AbstractFault localization is a major activity in program debugging. To automate this time-consuming task, many existing fault-localization techniques compare passed executions and failed executions, and suggest suspicious program elements, such as predicates or statements, to facilitate the identification of faults. To do that, these techniques propose statistical models and use hypothesis testing methods to test the similarity or dissimilarity of proposed program features between passed and failed executions. Furthermore, when applying their models, these techniques presume that the feature spectra come from populations with specific distributions. The accuracy of using a model to describe feature spectra is related to and may be affected by the underlying distribution of the feature spectra, and the use of a (sound) model on inapplicable circumstances to describe real-life feature spectra may lower the effectiveness of these fault-localization techniques. In this paper, we make use of hypothesis testing methods as the core concept in developing a predicate-based fault-localization framework. We report a controlled experiment to compare, within our framework, the efficacy, scalability, and efficiency of applying three categories of hypothesis testing methods, namely, standard non-parametric hypothesis testing methods, standard parametric hypothesis testing methods, and debugging-specific parametric testing methods. We also conduct a case study to compare the effectiveness of the winner of these three categories with the effectiveness of 33 existing statement-level fault-localization techniques. The experimental results show that the use of non-parametric hypothesis testing methods in our proposed predicate-based fault-localization model is the most promising. © 2011 Elsevier Inc. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/142943
ISSN
2015 Impact Factor: 1.424
2015 SCImago Journal Rankings: 0.897
ISI Accession Number ID
Funding AgencyGrant Number
National Natural Science Foundations of China61003027
61073006
Research Grants Council of Hong Kong111410
123206
123207
716507
City University of Hong Kong7002464
Funding Information:

The research is supported in part by grants of the National Natural Science Foundations of China (project nos. 61003027 and 61073006), the Research Grants Council of Hong Kong (project nos. 111410, 123206, 123207 and 716507), and City University of Hong Kong (project no. 7002464).

References

 

DC FieldValueLanguage
dc.contributor.authorZhang, Zen_HK
dc.contributor.authorChan, WKen_HK
dc.contributor.authorTse, THen_HK
dc.contributor.authorYu, YTen_HK
dc.contributor.authorHu, Pen_HK
dc.date.accessioned2011-10-28T02:59:38Z-
dc.date.available2011-10-28T02:59:38Z-
dc.date.issued2011en_HK
dc.identifier.citationJournal Of Systems And Software, 2011, v. 84 n. 6, p. 885-905en_HK
dc.identifier.issn0164-1212en_HK
dc.identifier.urihttp://hdl.handle.net/10722/142943-
dc.description.abstractFault localization is a major activity in program debugging. To automate this time-consuming task, many existing fault-localization techniques compare passed executions and failed executions, and suggest suspicious program elements, such as predicates or statements, to facilitate the identification of faults. To do that, these techniques propose statistical models and use hypothesis testing methods to test the similarity or dissimilarity of proposed program features between passed and failed executions. Furthermore, when applying their models, these techniques presume that the feature spectra come from populations with specific distributions. The accuracy of using a model to describe feature spectra is related to and may be affected by the underlying distribution of the feature spectra, and the use of a (sound) model on inapplicable circumstances to describe real-life feature spectra may lower the effectiveness of these fault-localization techniques. In this paper, we make use of hypothesis testing methods as the core concept in developing a predicate-based fault-localization framework. We report a controlled experiment to compare, within our framework, the efficacy, scalability, and efficiency of applying three categories of hypothesis testing methods, namely, standard non-parametric hypothesis testing methods, standard parametric hypothesis testing methods, and debugging-specific parametric testing methods. We also conduct a case study to compare the effectiveness of the winner of these three categories with the effectiveness of 33 existing statement-level fault-localization techniques. The experimental results show that the use of non-parametric hypothesis testing methods in our proposed predicate-based fault-localization model is the most promising. © 2011 Elsevier Inc. All rights reserved.en_HK
dc.languageengen_US
dc.publisherElsevier Inc. The Journal's web site is located at http://www.elsevier.com/locate/jssen_HK
dc.relation.ispartofJournal of Systems and Softwareen_HK
dc.subjectFault localizationen_HK
dc.subjectHypothesis testingen_HK
dc.subjectNon-parametric methoden_HK
dc.subjectParametric methoden_HK
dc.titleNon-parametric statistical fault localizationen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0164-1212&volume=84&issue=6&spage=885−905&epage=&date=2011&atitle=Non-parametric+statistical+fault+localizationen_US
dc.identifier.emailTse, TH: thtse@cs.hku.hken_HK
dc.identifier.authorityTse, TH=rp00546en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jss.2010.12.048en_HK
dc.identifier.scopuseid_2-s2.0-79953688693en_HK
dc.identifier.hkuros185039en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79953688693&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume84en_HK
dc.identifier.issue6en_HK
dc.identifier.spage885en_HK
dc.identifier.epage905en_HK
dc.identifier.isiWOS:000290073600001-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridZhang, Z=34769232200en_HK
dc.identifier.scopusauthoridChan, WK=23967779900en_HK
dc.identifier.scopusauthoridTse, TH=7005496974en_HK
dc.identifier.scopusauthoridYu, YT=7406250621en_HK
dc.identifier.scopusauthoridHu, P=7201989692en_HK
dc.identifier.citeulike8676087-

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