Feature-Driven End-To-End Test Generation

Understand

End-to-end (E2E) testing is essential for ensuring web application quality.

• However, manual test creation is time-consuming, and current test generation techniques produce incoherent tests.
• In this paper, we present AutoE2E, a novel approach that leverages Large Language Models (LLMs) to automate the generation of semantically meaningful feature-driven E2E test cases for web applications.
• AutoE2E intelligently infers potential features within a web application and translates them into executable test scenarios.