The Evolving Role of Artificial Intelligence in Software Testing: Prospects and Challenges

Samenvatting

The ability of a computer to replicate human intellect in areas such as learning, reasoning, problem-solving, and decision-mak
ing is known as artificial intelligence (AI). Among the many tools used in AI are rule-based systems, expert systems, neural 
networks, and machine learning. AI makes use of algorithms and procedures to analyze data, derive inferences from laws and 
patterns, and improve performance gradually. Software testing is the procedure by which the anticipated functioning of a soft
ware program or product is examined and confirmed. Bug avoidance, reduced development costs, and enhanced performance 
are some of testing’s advantages. Artificial intelligence (AI) has the potential to revolutionize software testing by automating test 
script creation, test data generation, and test generation. This would not only improve the product quality but also streamline 
the manual testing operations. It takes a lot of time, effort, and energy to test software. In an effort to improve both quality 
and delivery time, automation solutions have been developed to aid in the automation of certain processes within the testing 
process. Automation solutions have a diminishing return on investment (ROI) when CI/CD pipelines are integrated. Because 
AI can scan code for errors and bugs far faster than humans and without human interaction, the testing community is turning 
to AI to fill the void. Our goal in doing this research is to get a better understanding of how AI is influencing different STLC 
activities and software testing components. Some of the most significant difficulties encountered by software testers while using 
AI in testing are also attempted to be identified and explained in the research. The paper goes on to list a number of major ways 
AI may improve software testing.