Automated Test Case Generation with AI: A Novel Framework for Improving Software Quality and Coverage

Modern software testing has become imperative as testing is being automated test case generation: it makes the test efficient, accurate and completely covered. Traditionally, scalability, adaptability, and completeness are the Achilles heels of scalability of traditional testing methods as manual and scripted. In this paper, we introduce a novel AI driven framework for automated test case generation based on deep learning and reinforcement learning using evolutionary algorithm to improve test case generation process. It provides an effective test coverage by dynamically generating and prioritizing test cases according to their historical data, execution patterns and real time software update. AI driven testing reduce manual effort, reduce test execution time, and detects defect earlier in the development cycle as per results. Although the challenge includes the quality of the data, the computing resource demand and application to the complex software system, the future advancement of AI and integration of AI & CI/CD pipelines will further increase the ability of automation in test case generation.