AI-Driven E2E Testing and Cucumber Test Generation: A GPT-Powered Approach for Improved Software Quality and Collaboration

This research proposes leveraging Generative Pretrained Transformer (GPT) to train on software requirements and create a custom model. The model will power an intelligent chatbot for developers and generate Cucumber test scenarios, improving E2E testing efficiency and collaboration. This approach enhances test coverage, reduces maintenance overhead, and accelerates test case creation, providing valuable insights into AI-driven testing in software development.