Big data testing framework for recommendation systems in e-science and e-commerce domains

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dc.authorid0000-0002-4958-4575en_US
dc.authorscopusid55355863500en_US
dc.authorwosidABH-8073-2020en_US
dc.contributor.authorUzun-Per, Meryem
dc.contributor.authorCan, Ali Burak
dc.contributor.authorGürel, Ahmet Volkan
dc.contributor.authorAktaş, Mehmet S.
dc.date.accessioned2022-01-18T07:05:32Z
dc.date.available2022-01-18T07:05:32Z
dc.date.issued2021en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractSoftware testing is an important process to evaluate whether the developed software applications meet the required specifications. There is an emerging need for testing frameworks for big data software projects to ensure the quality of the big data applications and satisfy the user requirements. In this study, we propose a software testing framework that can be utilized in big data projects both in e-science and e-commerce. In particular, we design the proposed framework to test big data-based recommendation applications. To show the usability of the proposed framework, we provide a reference prototype implementation and use the prototype to test a big data recommendation application. We apply the prototype implementation to test both functional and non-functional methods of the recommendation application. The results indicate that the proposed testing framework is usable and efficient for testing the recommendation systems that use big data processing techniques.en_US
dc.identifier.citationUzun-Per, M., Can, A. B., Gürel, A. V., & Aktaş, M. S. (2021). Big data testing framework for recommendation systems in e-science and e-commerce domains. 2021 IEEE International Conference on Big Data, pp. 2353-2361. https://doi.org/10.1109/bigdata52589.2021.9672082en_US
dc.identifier.doi10.1109/bigdata52589.2021.9672082en_US
dc.identifier.endpage2361en_US
dc.identifier.scopus2-s2.0-85125363741en_US
dc.identifier.startpage2353en_US
dc.identifier.urihttps://doi.org/10.1109/bigdata52589.2021.9672082
dc.identifier.urihttps://hdl.handle.net/20.500.13055/138
dc.identifier.wosWOS:000800559502059en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynak.otherCPCI-S - Conference Proceedings Citation Index-Scienceen_US
dc.institutionauthorUzun-Per, Meryem
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2021 IEEE International Conference on Big Dataen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectTesting Frameworken_US
dc.subjectTesting for Big Data Projectsen_US
dc.subjectEcommendation Systemsen_US
dc.subjectBig Data Algorithmsen_US
dc.subjectDistributed Systemsen_US
dc.subjectSpark MLliben_US
dc.titleBig data testing framework for recommendation systems in e-science and e-commerce domainsen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

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