Tell Me Why: Language Models Help Explain the Rationale Behind Internet Protocol Design

Request for Comments (RFCs) serve as guidebooks for the implementation of Internet protocols or network mechanisms. They reveal how these protocols and mechanisms work, but the underlying reasons for their operation are not always available in RFCs. We present an attempt to automate the discovery of these reasons in mailing list archives via natural language processing methods. Our approach leverages the known relationship between text changes and the discussions leading to these changes in the Working Group (WG) GitHub repositories of the Internet Engineering Task Force (IETF) to obtain labeled training data. We find that our model is able to generalize, and it can indeed discover emails that have led to formulations in RFCs. This is a first step towards facilitating a deeper understanding of these often complex documents, which can be helpful for developers, protocol designers, and educators alike.