AI in Software Testing: Revolutionizing Quality Assurance
Andrea Trifunova, Boro Jakimovski, Ivan Chorbev, Petre Lameski
Ss. Cyril and Methodius University in Skopje
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摘要与影响
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.
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计算机 / AIAnomaly Detection Techniques and Applications
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