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Article: Normalized restricted random testing

TitleNormalized restricted random testing
Authors
Issue Date2003
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
Lecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2003, v. 2655, p. 368-381 How to Cite?
AbstractRestricted Random Testing (RRT) is a new method of testing software that improves upon traditional random testing (RT) techniques. This paper presents new data in support of the efficiency of RRT, and presents a variation of the algorithm, Normalized Restricted Random Testing (NRRT). NRRT permits the tester to have better information about the target exclusion rate (R) of RRT, the main control parameter of the method. We examine the performance of the NRRT and Original RRT (ORRT) methods using simulations and experiments, and offer some guidance for their use in practice. © Springer-Verlag Berlin Heidelberg 2003.
Persistent Identifierhttp://hdl.handle.net/10722/93246
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorChan, KPen_HK
dc.contributor.authorChen, TYen_HK
dc.contributor.authorTowey, Den_HK
dc.date.accessioned2010-09-25T14:55:18Z-
dc.date.available2010-09-25T14:55:18Z-
dc.date.issued2003en_HK
dc.identifier.citationLecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2003, v. 2655, p. 368-381en_HK
dc.identifier.issn0302-9743en_HK
dc.identifier.urihttp://hdl.handle.net/10722/93246-
dc.description.abstractRestricted Random Testing (RRT) is a new method of testing software that improves upon traditional random testing (RT) techniques. This paper presents new data in support of the efficiency of RRT, and presents a variation of the algorithm, Normalized Restricted Random Testing (NRRT). NRRT permits the tester to have better information about the target exclusion rate (R) of RRT, the main control parameter of the method. We examine the performance of the NRRT and Original RRT (ORRT) methods using simulations and experiments, and offer some guidance for their use in practice. © Springer-Verlag Berlin Heidelberg 2003.en_HK
dc.languageengen_HK
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_HK
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_HK
dc.titleNormalized restricted random testingen_HK
dc.typeArticleen_HK
dc.identifier.emailChan, KP:kpchan@cs.hku.hken_HK
dc.identifier.authorityChan, KP=rp00092en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-35248885659en_HK
dc.identifier.hkuros82109en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-35248885659&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume2655en_HK
dc.identifier.spage368en_HK
dc.identifier.epage381en_HK
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridChan, KP=7406032820en_HK
dc.identifier.scopusauthoridChen, TY=13104290200en_HK
dc.identifier.scopusauthoridTowey, D=8362064600en_HK

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