Authors: Dr. Kumarswamy S, Darshith L, Aditya B N, Mohammed Waseem, Nagraj, Nitin Reddy
Abstract: This review explores the effectiveness of Artificial Intelligence (AI) methods in software testing, addressing the high costs and challenges of traditional approaches. It examines key AI and Machine Learning (ML) techniques, their applications in test suite optimization, test case generation, and test case prioritization, highlighting quantitative improvements. The paper also discusses current challenges like data availability and model bias, and outlines future research directions for more adaptable and scalable AI solutions in software engineering.
