Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/33918
Title: AI in Software Testing: Revolutionizing Quality Assurance
Authors: Trifunova, Andrea
Jakimovski, Boro 
Chorbev, Ivan
Lameski, Petre 
Keywords: Artificial intelligence, Software testing
Issue Date: 26-Nov-2024
Publisher: IEEE
Conference: 2024 32nd Telecommunications Forum (TELFOR)
Abstract: Artificial 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.
URI: http://hdl.handle.net/20.500.12188/33918
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers

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