Abstract: This survey explores the quality of software engineering and highlights the important role of artificial intelligence (AI) in improving software testing. It emphasizes the importance of software testing to determine the effectiveness and capabilities of software programs. This paper highlights inconsistencies in measurement guidance and the need for automation. It will also provide a better look at the changing ecosystem of automation products driven by roles in the convergence of the artificial intelligence and machine learning (ML) eras. An AI-powered machine is made based on machine learning principles and is known as a tool that performs test models, provides logic, solves problems and performs tasks correctly. The main purpose of this evaluation is to explain the practical use of artificial intelligence in software testing and to conduct an in-depth analysis of its impact on software performance and development, improving agility. In summary, this communication provides a vision for the future by demonstrating the effectiveness of intelligent automation tools in the software testing environment, making the transition to software development reliable and convenient. More generally, this survey paper discusses today's practices of using AI to improve software development and continually unlock problem-solving innovation in software testing and software engineering along with making UI testing more reliable.
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