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A systematic review on cloud testing

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dc.affiliation.dptoUC3M. Departamento de Ingeniería Telemáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Aplicaciones y Servicios Telemáticos (GAST)es
dc.contributor.authorBertolino, Antonia
dc.contributor.authorDe Angelis, Guglielmo
dc.contributor.authorGallego, Micael
dc.contributor.authorGarcía Gutiérrez, Boni
dc.contributor.authorGortázar, Francisco
dc.contributor.authorLonetti, Francesca
dc.contributor.authorMarchetti, Eda
dc.contributor.funderComunidad de Madrides
dc.contributor.funderEuropean Commissionen
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2021-05-06T10:45:30Z
dc.date.available2021-05-06T10:45:30Z
dc.date.issued2019-09
dc.description.abstractA systematic literature review is presented that surveyed the topic of cloud testing over the period (2012-2017). Cloud testing can refer either to testing cloud-based systems (testing of the cloud), or to leveraging the cloud for testing purposes (testing in the cloud): both approaches (and their combination into testing of the cloud in the cloud) have drawn research interest. An extensive paper search was conducted by both automated query of popular digital libraries and snowballing, which resulted into the final selection of 147 primary studies. Along the survey a framework has been incrementally derived that classifies cloud testing research along six main areas and their topics. The paper includes a detailed analysis of the selected primary studies to identify trends and gaps, as well as an extensive report of the state of art as it emerges by answering the identified Research Questions. We find that cloud testing is an active research field, although not all topics have received so far enough attention, and conclude by presenting the most relevant open research challenges for each area of the classification framework.en
dc.description.sponsorshipThis paper describes research work mostly undertaken in the context of the European Project H2020 731535: ElasTest. This work has also been partially supported by: the Italian MIUR PRIN 2015 Project: GAUSS; the Regional Government of Madrid (CM) under project Cloud4BigData (S2013/ICE-2894) cofunded by FSE & FEDER; and the Spanish Government under project LERNIM (RTC-2016-4674-7) cofunded by the Ministry of Economy and Competitiveness, FEDER & AEI.en
dc.format.extent42es
dc.identifier.bibliographicCitationACM computing surveys, 52(5), 93, Sept. 2019, 42 pp.en
dc.identifier.doihttps://doi.org/10.1145/3331447
dc.identifier.issn0360-0300
dc.identifier.issn1557-7341 (online)
dc.identifier.publicationfirstpage1es
dc.identifier.publicationissue5, 93es
dc.identifier.publicationlastpage42es
dc.identifier.publicationtitleACM COMPUTING SURVEYSen
dc.identifier.publicationvolume52es
dc.identifier.urihttps://hdl.handle.net/10016/32548
dc.identifier.uxxiAR/0000026602
dc.language.isoengen
dc.publisherACMen
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/731535/ElasTesten
dc.relation.projectIDComunidad de Madrid. S2013/ICE-2894/Cloud4BigDataes
dc.relation.projectIDGobierno de España. RTC-2016-4674-7/LERNIMes
dc.rights© 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM.en
dc.rights.accessRightsopen accesses
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherCloud computingen
dc.subject.otherTestingen
dc.titleA systematic review on cloud testingen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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