Framework and Automation Levels for AI-Assisted Network Protocol Testing
draft-cui-nmrg-auto-test-00
| Document | Type |
Expired Internet-Draft
(individual)
Expired & archived
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|---|---|---|---|
| Authors | Yong Cui , Yunze Wei , Kaiwen Chi , Xiaohui Xie | ||
| Last updated | 2026-01-05 (Latest revision 2025-07-04) | ||
| RFC stream | (None) | ||
| Intended RFC status | (None) | ||
| Formats | |||
| Stream | Stream state | (No stream defined) | |
| Consensus boilerplate | Unknown | ||
| RFC Editor Note | (None) | ||
| IESG | IESG state | Expired | |
| Telechat date | (None) | ||
| Responsible AD | (None) | ||
| Send notices to | (None) |
This Internet-Draft is no longer active. A copy of the expired Internet-Draft is available in these formats:
Abstract
This document presents an AI-assisted framework for automating the testing of network protocol implementations. The proposed framework encompasses essential components such as protocol comprehension, test case generation, automated script and configuration synthesis, and iterative refinement through feedback mechanisms. In addition, the document defines a multi-level model of test automation maturity, ranging from fully manual procedures (Level 0) to fully autonomous and adaptive systems (Level 5), providing a structured approach to evaluating and advancing automation capabilities. Leveraging recent advancements in artificial intelligence, particularly large language models (LLMs), the framework illustrates how AI technologies can be applied to enhance the efficiency, scalability, and consistency of protocol testing. This document serves both as a reference architecture and as a roadmap to guide the evolution of protocol testing practices in light of emerging AI capabilities.
Authors
Yong Cui
Yunze Wei
Kaiwen Chi
Xiaohui Xie
(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)