Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/4059
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dc.contributor.authorKalaji, AS-
dc.contributor.authorHierons, RM-
dc.contributor.authorSwift, S-
dc.coverage.spatial2en
dc.date.accessioned2010-01-22T10:42:43Z-
dc.date.available2010-01-22T10:42:43Z-
dc.date.issued2009-
dc.identifier.citationTesting: Academic and Industrial Conference - Practice and Research Techniques (TAIC PART '09), Windsor, pp. 131-132, Sep 2009en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/4059-
dc.description.abstractThe extended finite state machine is a powerful model that can capture almost all the aspects of a system. However, testing from an EFSM is yet a challenging task due to two main problems: path feasibility and path test data generation. Although optimization algorithms are efficient, their applications to EFSM testing have received very little attention. The aim of this paper is to develop a novel approach that utilizes optimization algorithms to test from EFSM models.en
dc.language.isoenen
dc.publisherIEEEen
dc.subjectEvolutionary testingen
dc.subjectModel-based testingen
dc.subjectSearch-based testingen
dc.subjectTest data generationen
dc.subjectTransition path (TP)en
dc.subjectExtended finite state machineen
dc.titleA search-based approach for automatic test generation from extended finite state machine (EFSM)en
dc.typeConference Paperen
dc.identifier.doihttp://dx.doi.org/10.1109/TAICPART.2009.19-
Appears in Collections:Computer Science
Dept of Computer Science Research Papers
Software Engineering (B-SERC)

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