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dc.creatorSánchez Jerez, Ana Belénes
dc.creatorSegura Rueda, Sergioes
dc.creatorParejo Maestre, José Antonioes
dc.creatorRuiz Cortés, Antonioes
dc.date.accessioned2017-06-01T09:15:22Z
dc.date.available2017-06-01T09:15:22Z
dc.date.issued2017
dc.identifier.citationSánchez Jerez, A.B., Segura Rueda, S., Parejo Maestre, J.A. y Ruiz Cortés, A. (2017). Variability testing in the wild: the Drupal case study. Software and Systems Modeling, 16 (1), 173-194.
dc.identifier.issn1619-1366es
dc.identifier.urihttp://hdl.handle.net/11441/60715
dc.description.abstractVariability testing techniques search for effective and manageable test suites that lead to the rapid detection of faults in systems with high variability. Evaluating the effectiveness of these techniques in realistic settings is a must, but challenging due to the lack of variability intensive systems with available code, automated tests and fault reports. In this article, we propose using the Drupal framework as a case study to evaluate variability testing techniques. First, we represent the framework variability using a feature model. Then, we report on extensive non–functional data extracted from the Drupal Git repository and the Drupal issue tracking system. Among other results, we identified 3,392 faults in single features and 160 faults triggered by the interaction of up to 4 features in Drupal v7.23. We also found positive correlations relating the number of bugs in Drupal features to their size, cyclomatic complexity, number of changes and fault history. To show the feasibility of our work, we evaluated the effectiveness of non–functional data for test case prioritization in Drupal. Results show that non–functional attributes are effective at accelerating the detection of faults, outperforming related prioritization criteria as test case similarity.es
dc.description.sponsorshipMinisterio de Economía y Competitividad IPT-2012-0890-390000es
dc.description.sponsorshipMinisterio de Economía y Competitividad TIN2012-32273es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherSpringeres
dc.relation.ispartofSoftware and Systems Modeling, 16 (1), 173-194.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleVariability testing in the wild: the Drupal case studyes
dc.typeinfo:eu-repo/semantics/articlees
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessrightsinfo:eu-repo/semantics/embargoAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticoses
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/IPT-2012-0890-390000es
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/TIN2012-32273es
dc.date.embargoEndDate2019-02
dc.relation.publisherversionhttps://link.springer.com/article/10.1007/s10270-015-0459-zes
dc.identifier.doi10.1007/s10270-015-0459-zes
dc.contributor.groupUniversidad de Sevilla. TIC205: Ingeniería del Software Aplicadaes
idus.format.extent24 p.es
dc.journaltitleSoftware and Systems Modelinges
dc.publication.volumen16es
dc.publication.issue1es
dc.publication.initialPage173es
dc.publication.endPage194es
dc.contributor.funderMinisterio de Economía y Competitividad (MINECO). España

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