Leveraging Large Language Models for Explicit Wait Management in End-to-End Web Testing

End-to-end (E2E) testing is an approach in which an application is automatically tested through scripts that simulate the actions a user would perform. Properly managing asynchronous interactions is crucial in this approach to avoid test failures and flakiness. In the Selenium WebDriver framework, this is typically addressed by using thread sleeps (which pause the test for a fixed time) or explicit waits (function calls that pause the test execution until a specified condition is met). Explicit waits require the selection of both a condition to wait for (e.g., element visibility, element clickability) and an element on which that condition applies. Since thread sleeps are unreliable and replacing them with appropriate explicit waits is a time consuming task, in this work, we leverage a Large Language Model (LLM) to assist testers in selecting the most appropriate explicit waits. We defined a structured procedure (a series of prompts) for engaging with the LLM and validated this approach empirically on three test suites affected by asynchronous waiting issues, as well as on 12 synthetic examples. Additionally, we compared our approach with SleepReplacer, the current state-of-the-art tool for replacing thread sleeps with explicit waits in E2E web test suites. The results show that the LLM-based approach can automatically replace the majority of thread sleeps in a test suite on the first attempt, outperforming SleepReplacer.