Leveraging LLMs for Grammar Adaptation: A Study on Metamodel-Grammar Co-Evolution
Researchers have developed a new method using Large Language Models (LLMs) to automatically adapt grammars following metamodel evolution in model-driven engineering. This LLM-based approach learns adaptations from previous versions, outperforming traditional rule-based methods in consistency and output similarity on smaller datasets. While effective for complex grammar scenarios, the study found LLMs struggled with adaptation consistency on very large grammars, indicating limitations for large-scale applications. AI
IMPACT LLM-based grammar adaptation shows potential for automating complex software engineering tasks, though scalability remains a challenge.