EXPLORING THE USE OF ARTIFICIAL INTELLIGENCE FOR SOFTWARE TESTING AND DEBUGGING

The use of artificial intelligence (AI) has the potential to bring about major improvements in both the quality of software and the productivity with which it is tested and debugged. In this article, we give a comprehensive literature analysis on the subject of artificial intelligence (AI) in software testing and debugging. In this paper, we discuss the challenges faced in software testing and debugging, as well as the prospective applications of AI in these areas, and we offer a brief summary of the methodologies, techniques, and approaches that are currently used in this field. Recent advancements in the industry are also discussed, including the use of deep learning to produce test cases, explainable AI to debug, reinforcement learning to optimize test suites, natural language processing (NLP) to evaluate requirements, artificial intelligence to automate testing, and continuous integration and continuous delivery to simplify the entire process. In the final part of this article, we discuss the unfinished business in this industry, which includes the creation of AI-human hybrid systems, the development of AI that is more explainable and transparent, and the necessity of developing AI-based tools and methodologies that are more sophisticated.