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Conference Paper: Forgetting test cases

TitleForgetting test cases
Authors
Issue Date2006
Citation
Proceedings - International Computer Software And Applications Conference, 2006, v. 1, p. 485-492 How to Cite?
AbstractAdaptive Random Testing (ART) methods are Software Testing methods which are based on Random Testing, but which use additional mechanisms to ensure more even and widespread distributions of test cases over an input domain. Restricted Random Testing (RRT) is a version of ART which uses exclusion regions and restriction of test case generation to outside these regions. RRT has been found to perform very well, but incurs some additional computational cost in its restriction of the input domain. This paper presents a method of reducing overheads called Forgetting, where the number of test cases used in the restriction algorithm can be limited, and thus the computational overheads reduced. The motivation for Forgetting comes from its importance as a human strategy for learning. Several implementations are presented and examined using simulations. The results are very encouraging. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/93424
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorChan, KPen_HK
dc.contributor.authorChen, TYen_HK
dc.contributor.authorTowey, Den_HK
dc.date.accessioned2010-09-25T15:00:44Z-
dc.date.available2010-09-25T15:00:44Z-
dc.date.issued2006en_HK
dc.identifier.citationProceedings - International Computer Software And Applications Conference, 2006, v. 1, p. 485-492en_HK
dc.identifier.issn0730-3157en_HK
dc.identifier.urihttp://hdl.handle.net/10722/93424-
dc.description.abstractAdaptive Random Testing (ART) methods are Software Testing methods which are based on Random Testing, but which use additional mechanisms to ensure more even and widespread distributions of test cases over an input domain. Restricted Random Testing (RRT) is a version of ART which uses exclusion regions and restriction of test case generation to outside these regions. RRT has been found to perform very well, but incurs some additional computational cost in its restriction of the input domain. This paper presents a method of reducing overheads called Forgetting, where the number of test cases used in the restriction algorithm can be limited, and thus the computational overheads reduced. The motivation for Forgetting comes from its importance as a human strategy for learning. Several implementations are presented and examined using simulations. The results are very encouraging. © 2006 IEEE.en_HK
dc.languageengen_HK
dc.relation.ispartofProceedings - International Computer Software and Applications Conferenceen_HK
dc.titleForgetting test casesen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailChan, KP:kpchan@cs.hku.hken_HK
dc.identifier.authorityChan, KP=rp00092en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/COMPSAC.2006.43en_HK
dc.identifier.scopuseid_2-s2.0-34247518264en_HK
dc.identifier.hkuros129386en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34247518264&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume1en_HK
dc.identifier.spage485en_HK
dc.identifier.epage492en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridChan, KP=7406032820en_HK
dc.identifier.scopusauthoridChen, TY=13104290200en_HK
dc.identifier.scopusauthoridTowey, D=8362064600en_HK

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