Large Language Models for Automated Network Protocol Testing: A Survey

This paper surveys state-of-the-art methods leveraging Large Language Models (LLMs) for automated test case generation in network protocols, with a focus on addressing ambiguities in protocol specifications and enhancing test coverage. Traditional approaches face challenges in scaling and ensuring thorough compliance. LLMs, with their natural language understanding capabilities, offer a promising solution by automating the extraction of specifications from Request for Comments (RFCs) and generating structured models and test cases. Relevant studies, tools and frameworks are reviewed and analyzed to understand how LLMs are used in this area. The paper discusses their strengths and limitations, aiming to support further research on LLMs to improve the reliability and efficiency of network protocol testing.