AI RESEARCH
Effective LLM Code Refinement via Property-Oriented and Structurally Minimal Feedback
arXiv CS.AI
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ArXi:2506.18315v2 Announce Type: replace-cross LLMs excel at code generation, yet ensuring the functional correctness of their outputs remains a persistent challenge. While recent studies have applied Test-Driven Development (TDD) to refine code, these methods are often undermined by poor feedback quality, stemming from the scarcity of high-quality test cases and noisy signals from auto-generated ones. In this work, we shift the focus from test quantity to feedback quality. We