Towards a Modeling Assistant for Capturing CRML Requirements

Abstract

The Common Requirement Modeling Language (CRML) is a domain-specific controled natural language intended to capture requirements in a format that is readable by multidisciplinary stakeholders. However, similarly to other domain-specific languages, CRML suffers from limited available human expertise and material. LLMs provide a tool for experts to increase their productivity, but as CRML is largely excluded from LLM training data or only represented by outdated versions, LLMs and AI assistants cannot directly synthesize correct CRML models. We propose a modeling assistant that enables off-the-shelf LLMs and tools to work with CRML models to formalize natural language requirements in CRML. We leverage CRML specification and tooling to provide LLMs with condensed, usage-focused documentation and interactive syntactic checks of CRML models via the Model Context Protocol (MCP). We provide an initial evaluation of syntactic correctness for CRML models using an open-weight LLM.