TestCaseMig: LLM-Driven Test Case Migration for Evolving Codebases

As software systems evolve, test cases must adapt to code changes to remain valid and effective. Traditional test migration approaches, including symbolic execution and diff-based heuristics, often require significant manual effort and struggle to handle complex behavioral changes. Recent advances in large language models (LLMs) offer new opportunities for context-aware and automated test adaptation. However, existing LLM-based approaches are not well-suited for test case migration under evolving code, as they typically lack explicit modeling of code changes and original test context. In this paper, we present TestCaseMig, a framework that integrates LLMs with static analysis to migrate existing test cases in response to code modifications. TestCaseMig constructs change-sensitive, context-rich prompts and employs a multi-round, feedback-driven generation process with validation and coverage analysis to ensure the correctness, completeness, and adaptability of migrated test cases.