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dc.contributor.authorBelhadi, Asma
dc.contributor.authorZhang, Man
dc.contributor.authorArcuri, Andrea
dc.date.accessioned2023-02-24T08:11:53Z
dc.date.available2023-02-24T08:11:53Z
dc.date.created2022-08-03T10:27:09Z
dc.date.issued2022
dc.identifier.isbn9781450392686
dc.identifier.urihttps://hdl.handle.net/11250/3053743
dc.description.abstractThe Graph Query Language (GraphQL) is a powerful language for APIs manipulation in web services. It has been recently introduced as an alternative solution for addressing the limitations of RESTful APIs. This paper introduces an automated solution for GraphQL APIs testing. We present a full framework for automated APIs testing, from the schema extraction to test case generation. Our approach is based on evolutionary search. Test cases are evolved to intelligently explore the solution space while maximizing code coverage criteria. The proposed framework is implemented and integrated in the open-source EvoMaster tool. Experiments on two open-source GraphQL APIs show statistically significant improvement of the evolutionary approach compared to the baseline random search.en_US
dc.language.isoengen_US
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.ispartofGECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion
dc.relation.ispartofseriesGECCO: Genetic and Evolutionary Computation Conference;GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion
dc.titleEvolutionary-based automated testing for GraphQL APIsen_US
dc.typeConference objecten_US
dc.description.versionpublishedVersionen_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.doihttps://doi.org/10.1145/3520304.3528952
dc.identifier.cristin2040853
dc.source.volume24en_US
dc.source.issue24en_US
dc.source.pagenumber4en_US
dc.relation.projectERC-European Research Council: 864972en_US


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