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Article: Restricted random testing: Adaptive random testing by exclusion

TitleRestricted random testing: Adaptive random testing by exclusion
Authors
KeywordsAdaptive random testing
Random testing
Restricted random testing
Software testing
Issue Date2006
PublisherWorld Scientific Publishing Co Pte Ltd. The Journal's web site is located at http://www.worldscinet.com/ijseke/ijseke.shtml
Citation
International Journal Of Software Engineering And Knowledge Engineering, 2006, v. 16 n. 4, p. 553-584 How to Cite?
AbstractRestricted Random Testing (RRT) is a new method of testing software that improves upon traditional Random Testing (RT) techniques. Research has indicated that failure patterns (portions of an input domain which, when executed, cause the program to fail or reveal an error) can influence the effectiveness of testing strategies. For certain types of failure patterns, it has been found that a widespread and even distribution of test cases in the input domain can be significantly more effective at detecting failure compared with ordinary RT. Testing methods based on RT, but which aim to achieve even and widespread distributions, have been called Adaptive Random Testing (ART) strategies. One implementation of ART is RRT. RRT uses exclusion zones around executed, but non-failure-causing, test cases to restrict the regions of the input domain from which subsequent test cases may be drawn. In this paper, we introduce the motivation behind RRT, explain the algorithm and detail some empirical analyses carried out to examine the effectiveness of the method. Two versions of RRT are presented: Ordinary RRT (ORRT) and Normalized RRT (NRRT). The two versions share the same fundamental algorithm, but differ in their treatment of non-homogeneous input domains. Investigations into the use of alternative exclusion shapes are outlined, and a simple technique for reducing the computational overheads of RRT, prompted by the alternative exclusion shape investigations, is also explained. The performance of RRT is compared with RT and another ART method based on maximized minimum test case separation (DART), showing excellent improvement over RT and a very favorable comparison with DART. © World Scientific Publishing Company.
Persistent Identifierhttp://hdl.handle.net/10722/88940
ISSN
2015 Impact Factor: 0.24
2015 SCImago Journal Rankings: 0.249
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChan, KPen_HK
dc.contributor.authorChen, TYen_HK
dc.contributor.authorTowey, Den_HK
dc.date.accessioned2010-09-06T09:50:24Z-
dc.date.available2010-09-06T09:50:24Z-
dc.date.issued2006en_HK
dc.identifier.citationInternational Journal Of Software Engineering And Knowledge Engineering, 2006, v. 16 n. 4, p. 553-584en_HK
dc.identifier.issn0218-1940en_HK
dc.identifier.urihttp://hdl.handle.net/10722/88940-
dc.description.abstractRestricted Random Testing (RRT) is a new method of testing software that improves upon traditional Random Testing (RT) techniques. Research has indicated that failure patterns (portions of an input domain which, when executed, cause the program to fail or reveal an error) can influence the effectiveness of testing strategies. For certain types of failure patterns, it has been found that a widespread and even distribution of test cases in the input domain can be significantly more effective at detecting failure compared with ordinary RT. Testing methods based on RT, but which aim to achieve even and widespread distributions, have been called Adaptive Random Testing (ART) strategies. One implementation of ART is RRT. RRT uses exclusion zones around executed, but non-failure-causing, test cases to restrict the regions of the input domain from which subsequent test cases may be drawn. In this paper, we introduce the motivation behind RRT, explain the algorithm and detail some empirical analyses carried out to examine the effectiveness of the method. Two versions of RRT are presented: Ordinary RRT (ORRT) and Normalized RRT (NRRT). The two versions share the same fundamental algorithm, but differ in their treatment of non-homogeneous input domains. Investigations into the use of alternative exclusion shapes are outlined, and a simple technique for reducing the computational overheads of RRT, prompted by the alternative exclusion shape investigations, is also explained. The performance of RRT is compared with RT and another ART method based on maximized minimum test case separation (DART), showing excellent improvement over RT and a very favorable comparison with DART. © World Scientific Publishing Company.en_HK
dc.languageengen_HK
dc.publisherWorld Scientific Publishing Co Pte Ltd. The Journal's web site is located at http://www.worldscinet.com/ijseke/ijseke.shtmlen_HK
dc.relation.ispartofInternational Journal of Software Engineering and Knowledge Engineeringen_HK
dc.subjectAdaptive random testingen_HK
dc.subjectRandom testingen_HK
dc.subjectRestricted random testingen_HK
dc.subjectSoftware testingen_HK
dc.titleRestricted random testing: Adaptive random testing by exclusionen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0218-1940&volume=16&issue=4&spage=553&epage=584&date=2005&atitle=Restricted+Random+Testing:+Adaptive+Random+Testing+by+Exclusionen_HK
dc.identifier.emailChan, KP:kpchan@cs.hku.hken_HK
dc.identifier.authorityChan, KP=rp00092en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1142/S0218194006002926en_HK
dc.identifier.scopuseid_2-s2.0-33748187592en_HK
dc.identifier.hkuros112617en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33748187592&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume16en_HK
dc.identifier.issue4en_HK
dc.identifier.spage553en_HK
dc.identifier.epage584en_HK
dc.identifier.isiWOS:000240606000003-
dc.publisher.placeSingaporeen_HK
dc.identifier.scopusauthoridChan, KP=7406032820en_HK
dc.identifier.scopusauthoridChen, TY=13104290200en_HK
dc.identifier.scopusauthoridTowey, D=8362064600en_HK

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