arXivPaperNeeds Review
MineValiCoder: Reliable Code Generation with Test Case Quality Mining and Bipartite Graph-Based Mutual Validation
MineValiCoder filters generated tests, refines several code candidates, then scores code and tests together. The pattern targets a core agent risk: unreliable tests steering implementation.
arXiv · Jul 24, 2026
Source Summary
MineValiCoder links three modules: **TCQM, Parallel TDD Refinement, and BiCoTeV**. They filter faulty generated tests, refine multiple code candidates, and score code-test interactions through a bipartite graph.
Practical Implication
For coding-agent harnesses, treat generated tests as uncertain evidence rather than ground truth. Validate tests before feeding failures back into implementation, preserve multiple candidates, and select using agreement across code and test behavior.
Agent-Ready Context
MineValiCoder links three modules: **TCQM, Parallel TDD Refinement, and BiCoTeV**. They filter faulty generated tests, refine multiple code candidates, and score code-test interactions through a bipartite graph. For coding-agent harnesses, treat generated tests as uncertain evidence rather than ground truth. Validate tests before feeding failures back into implementation, preserve multiple candidates, and select using agreement across code and test behavior. Across four LLMs, reported Pass@1 reached **96.34% on HumanEval** and **51.33% on LiveCodeBench**, with intermediate results on MBPP and APPS. These benchmark scores do not establish how the added loop performs on long-horizon repository changes.
Context Map
agentcoding#harness-engineering#agent-reliability#coding-agentsUncertainty
Across four LLMs, reported Pass@1 reached **96.34% on HumanEval** and **51.33% on LiveCodeBench**, with intermediate results on MBPP and APPS. These benchmark scores do not establish how the added loop performs on long-horizon repository changes.