Ве молиме користете го овој идентификатор да го цитирате или поврзете овој запис: http://hdl.handle.net/20.500.12188/33918
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dc.contributor.authorTrifunova, Andreaen_US
dc.contributor.authorJakimovski, Boroen_US
dc.contributor.authorChorbev, Ivanen_US
dc.contributor.authorLameski, Petreen_US
dc.date.accessioned2025-08-18T09:38:38Z-
dc.date.available2025-08-18T09:38:38Z-
dc.date.issued2024-11-26-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/33918-
dc.description.abstractArtificial intelligence (AI) is an area of tremendous potential, especially in the software testing domain, where it has changed the dynamics of the process, storms in efficiency, accuracy, and flexibility in a given SDLC. This paper presents findings from recent investigations of AI in the testing and quality assurance focusing on its transformational potential. Particular attention is paid to such issues as automation of testing processes through AI, testing process enhancement, and possible changes in software engineering due to AI implementation. In this paper, various research perspectives have been integrated to reveal the effectiveness of AI in enhancing the perceived quality assurance processes, improving product quality, and adopting principles of agile methodology in today's software development.en_US
dc.publisherIEEEen_US
dc.subjectArtificial intelligence, Software testingen_US
dc.titleAI in Software Testing: Revolutionizing Quality Assuranceen_US
dc.typeProceeding articleen_US
dc.relation.conference2024 32nd Telecommunications Forum (TELFOR)en_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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