ARTIFICIAL INTELLIGENCE FOR AUTOMATED TESTING AND BUG TRACKING

Abstract The article is dedicated to the use of artificial intelligence for software testing automation and bug tracking. It describes the key aspects of implementing intelligent testing systems, including automatic test scenario generation, code analysis, defect prediction, and log analysis. Specific examples of tools that demonstrate an increase in the speed and efficiency of testing are considered. The article provides statistical data confirming the growing popularity of the use of intelligent systems in software testing among large companies, which allows improving product quality and optimising processes.