A Hybrid Approach for EMF Code Generation:Code Templates Meet Large Language Models

2025-12-05

AI Summary

To address the tension between rigid template-based code generation and the high error rates of large language model (LLM)-generated code, this paper proposes iEcoreGen—a hybrid framework for LLM-augmented model-driven development. It leverages EMF/Ecore metamodels to formally specify system structure, decomposes requirements into operation-level specifications, and employs domain-specific templates to generate Java skeleton code annotated with specification-conforming docstrings; remaining method bodies are then completed by an LLM. This approach synergistically combines the correctness guarantees of model-driven engineering with the flexibility of LLMs. Evaluation across five mainstream LLMs and 20 diverse tasks shows that iEcoreGen achieves significantly higher pass@k than pure-LLM baselines, while maintaining comparable compilation@k. Ablation studies confirm the effectiveness of three core components: template-guided scaffolding, specification embedding in docstrings, and collaborative LLM-based method completion.

Technology Category

• Natural Language Processing: Code Generation / Program Synthesis from Natural Language
• Machine Learning: Large Multimodal Models (LMMs)
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

Template-based and LLM-based code generation are both key enablers of automated software development. The former provides correctness guarantees but are rigid for complex requirements, whereas LLMs offer high flexibility at the risk of producing faulty code.This paper proposes iEcoreGen, a hybrid approach that integrates Eclipse Modeling Framework (EMF) and LLMs. In EMF, an Ecore model defines a system structure and acts as a blueprint for code-generation.iEcoreGen decomposes requirements to derive operation specifications, uses EMF's template-based generator to produce initial Java code, and serializes specifications into docstrings. LLMs are then invoked to complete and fix unimplemented methods. We assessed iEcoreGen on twenty code-generation tasks across five LLMs. It surpasses LLM-only baselines on pass@k and performs on par with them on compilation@k. An ablation study clarified the contribution of each component of iEcoreGen. Overall, the findings indicate that LLM-enhanced model-driven development is a promising path toward more efficient software automation.

Problem

• Integrates EMF templates with LLMs for code generation
• Ensures correctness while handling complex software requirements
• Improves automated development by combining structured and flexible methods

Innovation

• Hybrid approach integrates EMF templates with LLMs
• Decomposes requirements to generate initial Java code
• Uses LLMs to complete and fix unimplemented methods