Prospects of intelligent automation in software testing process

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dc.contributor.authorBilovus, A.
dc.date.accessioned2022-02-10T13:44:58Z
dc.date.available2022-02-10T13:44:58Z
dc.date.issued2021
dc.descriptionBilovus A. Prospects of intelligent automation in software testing process / A. Bilovus // Black Sea Science 2021. Information Technology, Automation and Robotics : рroc. of the Intern. Competition of Student Scientific Works / Odessa Nat. Acad. of Food Technologies ; eds. B. Yegorov, M. Mardar, S. Kotlyk [et al.]. – Odessa : ONAFT, 2021. – P. 344-348 : fig. – Ref.: 6 tit.ru_RU
dc.description.abstractThis paper provides an overview of using Artificial intelligence (AI) for building test automation frameworks in a way with less human interventions. The analytical framework of the article is built on new modern enterprise prototypes. This article deals with opportunities as well as ideas to drive process of incorporation of AI in software testing process. The article provides analysis of areas to be augmented by use of Machine learning methods in testing tools (frameworks) from integrated reports as well as from own experience. This article refers to improvement of software quality validation, discovering potentiality and challenges of AI in terms of testing activities. Schema of integrated process with use of AI technology and traditional testing techniques is presented. By engaging with presented ideas, the article contributes to creation of open-source automated tool with power of AI. The main contribution of this study is to identify hands-on perspectives of AI to test software.ru_RU
dc.identifier.urihttps://card-file.ontu.edu.ua/handle/123456789/19662
dc.language.isoen_USru_RU
dc.subjectartificial intelligenceru_RU
dc.subjectautomation testingru_RU
dc.subjectdeep neural networksru_RU
dc.subjecttestingru_RU
dc.subjectdeep learningru_RU
dc.subjectDNNru_RU
dc.subjectAIru_RU
dc.subjectmachine learningru_RU
dc.titleProspects of intelligent automation in software testing processru_RU
dc.typeArticleru_RU
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