Abstract

Automation testing has become an integral part of modern software development, significantly improving efficiency, reducing human error, and enhancing testing accuracy. Over the last seven years, significant advancements have been made in automation testing optimization, focusing on enhancing the effectiveness of testing procedures and optimizing resource allocation. This paper provides a comprehensive review of the recent techniques and trends in automation testing optimization. The review highlights the evolution of automation testing strategies, investigates novel optimization methods, identifies datasets commonly used in research, and discusses the emerging trends that are shaping the future of automation testing. A comparative analysis of various optimization models and their performance is also presented, leading to the identification of the most effective approaches in current research. The paper concludes with insights into the future of automation testing optimization, exploring areas of potential improvement and innovation.