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Test Case Evaluation and Input Domain Reduction strategies for the Evolutionary Testing of Object-Oriented software

2009-07-05Journal article Open access
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datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
dc.contributor.authorRibeiro, José Carlos Bregieiro
dc.contributor.authorMário Alberto Zenha-Rela
dc.contributor.authorFrancisco Fernández de Vega
dc.date.accessioned2025-05-16T15:31:32Z
dc.date.available2025-05-16T15:31:32Z
dc.date.issued2009-07-05
dc.description.abstractIn Evolutionary Testing, meta-heuristic search techniques are used for generating test data. The focus of our research is on employing evolutionary algorithms for the structural unit-testing of Object-Oriented programs. Relevant contributions include the introduction of novel methodologies for automation, search guidance and Input Domain Reduction; the strategies proposed were empirically evaluated with encouraging results. Test cases are evolved using the Strongly-Typed Genetic Programming technique. Test data quality evaluation includes instrumenting the test object, executing it with the generated test cases, and tracing the structures traversed in order to derive coverage metrics. The methodology for efficiently guiding the search process towards achieving full structural coverage involves favouring test cases that exercise problematic structures. Purity Analysis is employed as a systematic strategy for reducing the search space.eng
dc.description.sponsorshipThis paper has been partially funded by Projects TIN2007-68083-C02 (Spanish Ministry of Education and Culture, NoHNES – Non-Hierarchical Network Evolutionary System Project), and Project GRU09105, Junta de Extremadura, Consejeria de Economia-Comercio e Innovación and FEDER.
dc.identifier.citationJosé Carlos Bregieiro Ribeiro, Mário Alberto Zenha-Rela, Francisco Fernández de Vega, Test Case Evaluation and Input Domain Reduction strategies for the Evolutionary Testing of Object-Oriented software, Information and Software Technology, Volume 51, Issue 11, 2009, Pages 1534-1548, ISSN 0950-5849, https://doi.org/10.1016/j.infsof.2009.06.009.
dc.identifier.doi10.1016/j.infsof.2009.06.009
dc.identifier.issn0950-5849
dc.identifier.urihttp://hdl.handle.net/10400.8/12909
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier
dc.relationTIN2007-68083-C02
dc.relation.hasversionhttps://www.sciencedirect.com/science/article/pii/S0950584909001001?via%3Dihub
dc.relation.ispartofInformation and Software Technology
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectEvolutionary Testing
dc.subjectSearch-Based Software Engineering
dc.subjectTest Case Evaluation
dc.subjectInput Domain Reduction
dc.titleTest Case Evaluation and Input Domain Reduction strategies for the Evolutionary Testing of Object-Oriented softwareeng
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage1548
oaire.citation.issue11
oaire.citation.startPage1534
oaire.citation.titleInformation and Software Technology
oaire.citation.volume51
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameRibeiro
person.givenNameJosé
person.identifier662638
person.identifier.ciencia-id0C1B-5E3F-6830
person.identifier.orcid0000-0003-3019-1330
person.identifier.scopus-author-id55947747200
relation.isAuthorOfPublication4ad743c6-5db7-4208-be72-c182c7b0f8ef
relation.isAuthorOfPublication.latestForDiscovery4ad743c6-5db7-4208-be72-c182c7b0f8ef

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In Evolutionary Testing, meta-heuristic search techniques are used for generating test data. The focus of our research is on employing evolutionary algorithms for the structural unit-testing of Object-Oriented programs. Relevant contributions include the introduction of novel methodologies for automation, search guidance and Input Domain Reduction; the strategies proposed were empirically evaluated with encouraging results. Test cases are evolved using the Strongly-Typed Genetic Programming technique. Test data quality evaluation includes instrumenting the test object, executing it with the generated test cases, and tracing the structures traversed in order to derive coverage metrics. The methodology for efficiently guiding the search process towards achieving full structural coverage involves favouring test cases that exercise problematic structures. Purity Analysis is employed as a systematic strategy for reducing the search space.
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