This topic delves into the paradigm shift brought by Generative Artificial Intelligence (AI) in the domain of software testing. In recent times, Generative AI has emerged as a powerful tool, revolutionizing traditional testing methodologies by introducing automation, efficiency, and adaptability.
Discussion will cover following key points:
– Overview of the conventional software testing life-cycle – (encompassing stages such as requirement analysis, test planning, test case development, execution, and reporting)
– Challenges in Traditional Testing – (highlighting manual effort intensiveness, time constraints, rapidly evolving technological landscape and increased application complexity)
– Introduction to Gen-AI – (Explain the concept of Generative AI)
– Integration of Gen-AI in Testing Life-Cycle – (to enhance efficiency and effectiveness incl. automated test case generation, code generation and other art of the possible use-case)
– Benefits and Advantages – (such as improved quality, faster time to market and increased productivity)
– Challenges and Considerations – (security, algorithm complexity, data quality requirements, and ethical implications)
– Case Studies (if feasible)
Takeaways from your talk
Emphasizing the transformative potential of Gen-AI in revolutionizing the testing life-cycle and ensuring software quality in the rapidly evolving complex technological landscape.