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dc.contributor.authorArcuri, Andrea
dc.date.accessioned2021-08-31T12:05:45Z
dc.date.available2021-08-31T12:05:45Z
dc.date.created2020-09-27T20:46:15Z
dc.date.issued2020-08-03
dc.identifier.issn0740-7459
dc.identifier.issn1937-4194
dc.identifier.urihttps://hdl.handle.net/11250/2771980
dc.description.abstractRESTful APIs are very popular in industry, especially when developing enterprise systems using a microservice architecture. Testing such APIs is challenging, as tests will be composed of not only HTTP calls, but also settings of the environment, like databases. Different blackbox testing techniques have been shown to easily find real faults in many RESTful APIs, with very little human effort from software engineers. However, whitebox techniques could lead to much better results, although having an up-front cost for the engineers. In this paper, we report on the use of the open-source tool EvoMaster, on eight RESTful APIs. We show how EvoMaster can be used to automatically generate test cases that can find several bugs, even when using a naive blackbox approach. When enhancing the search with whitebox information, significantly better results are achieved. However, there are several challenges that need to be taken into account when an engineer wants to use a tool such as EvoMaster to test their projects.en_US
dc.description.sponsorshipThis work is funded by the Research Council of Norway (project on Evolutionary Enterprise Testing, grant agreement No 274385).en_US
dc.language.isoengen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.ispartofseriesIEEE Software;Volume: 38, Issue: 3
dc.subjectProgramming interfacesen_US
dc.subjectTest casesen_US
dc.subjectComputer bugsen_US
dc.subjectRESTful APIsen_US
dc.subjectTestingen_US
dc.titleAutomated Blackbox and Whitebox Testing of RESTful APIs with EvoMasteren_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© IEEE 2020en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.doihttps://doi.org/10.1109/MS.2020.3013820
dc.identifier.cristin1833877
dc.source.journalIEEE Softwareen_US
dc.source.volume38en_US
dc.source.issue3en_US
dc.source.pagenumber1-10en_US
dc.relation.projectNotur/NorStore: NN9476Ken_US
dc.relation.projectNorges forskningsråd: 274385en_US


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