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LLM-Driven Approach to Modeling Tool Interoperability in Automotive Domain

arXiv 2607.14659 ↗First posted 16 Jul 2026cs.SE cs.AIcited by 0

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Abstract (arXiv)

Interoperability between heterogeneous modeling tools remains a significant challenge in Model-Driven Engineering (MDE), particularly in the automotive domain where multiple modeling languages, as well as defacto standard proprietary and open-source tools coexist. This paper presents an LLM-driven approach for automated model interoperability by considering two relevant aspects: 1) mapping model instances to a target metamodel 2) merging of metamodels. The proposed methodology is demonstrated through transformations involving Ecore and SysML v2 based metamodels and incorporates structural validation of generated model instances against user-defined target models. Automotive case studies illustrate the feasibility of the approach and show that large language models can significantly reduce manual transformation effort while generating structurally valid target models for cross-tool interoperability.

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References · 6

  1. 2025Survey of GenAI for Automotive Software Development: From Requirements to Executable Codecited by 5
  2. 2025GenAI for Automotive Software Development: From Requirements to Wheelscited by 5
  3. 2025LLM-based Iterative Approach to Metamodeling in Automotivecited by 4
  4. 2025LLM-Assisted Semantic Alignment and Integration in Collaborative Model-Based Systems Engineering Using SysML v2cited by 4
  5. 2025Querying Large Automotive Software Models: Agentic vs. Direct LLM Approachescited by 3
  6. 2025Text to model via SysML: Automated generation of dynamical system computational models from unstructured natural language text via enhanced System Modeling Language diagramscited by 3

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