How does generative ai contribute during the testing phase of the sdlc??

Generative AI plays a transformative role in the testing phase of the Software Development Life Cycle (SDLC) by automating test creation, optimizing coverage, and enhancing defect detection. It leverages advanced algorithms to analyze application requirements, automatically generate test cases, and identify high-risk areas, ensuring more comprehensive and efficient testing.

One of the key contributions of generative AI is its ability to dynamically create and maintain test scripts, adapting to changes in the application without manual intervention. This significantly reduces test maintenance efforts and accelerates the testing process. AI-driven predictive analytics help identify defects early by analyzing patterns in code behavior, allowing teams to address potential issues before they impact production.

By improving test efficiency, reducing manual workload, and enhancing accuracy, generative AI streamlines the software testing process, enabling faster releases, improved software quality, and a more resilient development lifecycle. Its ability to intelligently optimize test coverage and automate repetitive tasks makes it an invaluable asset in modern software testing strategies.