LLM-Assisted Repository-Level Generation with Structured Spec-Driven Engineering
📰 ArXiv cs.AI
Learn how to improve LLM-assisted code generation at the repository level using structured spec-driven engineering
Action Steps
- Define structured specifications for your repository-level system using tools like JSON or XML
- Use LLMs to generate code based on these specifications
- Verify and validate the generated code using automated testing and review
- Refine the specifications and repeat the generation process to improve output quality
- Integrate the generated code into your existing repository and test for compatibility
Who Needs to Know This
Software engineers and AI researchers can benefit from this approach to generate high-quality code at the repository level
Key Insight
💡 Using structured specifications can significantly improve the quality of LLM-generated code at the repository level
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🚀 Improve LLM-assisted code generation with structured spec-driven engineering! 📈
Key Takeaways
Learn how to improve LLM-assisted code generation at the repository level using structured spec-driven engineering
Full Article
Title: LLM-Assisted Repository-Level Generation with Structured Spec-Driven Engineering
Abstract:
arXiv:2605.02455v1 Announce Type: cross Abstract: State-of-the-art Large Language Models (LLMs) excel in code generation at the function level. However, the output quality significantly declines when scaling to repository-level systems. Current workflows relying only on natural language prompts suffer from inherent ambiguity and a lack of verifiability. To address this, we propose structured spec-driven engineering (SSDE), a paradigm that leverages structured artifacts to guide LLM generation. W
Abstract:
arXiv:2605.02455v1 Announce Type: cross Abstract: State-of-the-art Large Language Models (LLMs) excel in code generation at the function level. However, the output quality significantly declines when scaling to repository-level systems. Current workflows relying only on natural language prompts suffer from inherent ambiguity and a lack of verifiability. To address this, we propose structured spec-driven engineering (SSDE), a paradigm that leverages structured artifacts to guide LLM generation. W
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