LLM-based Iterative Approach to Metamodeling in Automotive
March 07, 2025 Β· Declared Dead Β· π 2025 2nd International Generative AI and Computational Language Modelling Conference (GACLM)
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Authors
Nenad Petrovic, Fengjunjie Pan, Vahid Zolfaghari, Alois Knoll
arXiv ID
2503.05449
Category
cs.SE: Software Engineering
Cross-listed
cs.AI
Citations
5
Venue
2025 2nd International Generative AI and Computational Language Modelling Conference (GACLM)
Last Checked
4 months ago
Abstract
In this paper, we introduce an automated approach to domain-specific metamodel construction relying on Large Language Model (LLM). The main focus is adoption in automotive domain. As outcome, a prototype was implemented as web service using Python programming language, while OpenAI's GPT-4o was used as the underlying LLM. Based on the initial experiments, this approach successfully constructs Ecore metamodel based on set of automotive requirements and visualizes it making use of PlantUML notation, so human experts can provide feedback in order to refine the result. Finally, locally deployable solution is also considered, including the limitations and additional steps required.
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