Automated Software Testing

Automated software testing aims to improve software quality and reduce development time by automating various testing phases, from generating test cases to analyzing results. Current research heavily utilizes large language models (LLMs) and evolutionary algorithms like genetic programming to enhance test case generation, failure analysis, and metric validation, addressing challenges in areas such as visual testing, microservices, and natural language processing (NLP) software. These advancements are significant because they improve the efficiency and effectiveness of software testing, leading to more robust and reliable software systems across diverse applications.