Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/340
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dc.contributor.authorGuo, Q-
dc.contributor.authorHierons, RM-
dc.contributor.authorHarman, M-
dc.contributor.authorDerderian, K-
dc.coverage.spatial14en
dc.date.accessioned2006-11-03T15:28:46Z-
dc.date.available2006-11-03T15:28:46Z-
dc.date.issued2005-
dc.identifier.citationIEE Proceedings - Software 152 (3): 127-140, Jun 2005en
dc.identifier.urihttp://www.iee.org/Publish/Journals/ProfJourn/Proc/SEN/index.cfmen
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/340-
dc.description.abstractMultiple unique input/output sequences (UIOs) are often used to generate robust and compact test sequences in finite state machine (FSM) based testing. However, computing UIOs is NP-hard. Metaheuristic optimisation techniques (MOTs) such as genetic algorithms (GAs) and simulated annealing (SA) are effective in providing good solutions for some NP-hard problems. In the paper, the authors investigate the construction of UIOs by using MOTs. They define a fitness function to guide the search for potential UIOs and use sharing techniques to encourage MOTs to locate UIOs that are calculated as local optima in a search domain. They also compare the performance of GA and SA for UIO construction. Experimental results suggest that, after using a sharing technique, both GA and SA can find a majority of UIOs from the models under test.en
dc.format.extent1162982 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherInstitution of Engineering and Technologyen
dc.subjectHeuristic methoden
dc.subjectNP hard problemen
dc.subjectGenetic algorithmen
dc.subjectSimulated annealingen
dc.subjectOptimization methoden
dc.titleConstructing multiple unique input/output sequences using metaheuristic optimisation techniquesen
dc.typeResearch Paperen
dc.identifier.doihttp://dx.doi.org/10.1049/ip-sen:20045001-
Appears in Collections:Computer Science
Dept of Computer Science Research Papers
Software Engineering (B-SERC)

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