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Paper · arXiv

Self-Spec Verifiable Code Generation

Large language models (LLMs) may generate unreliable code on corner cases missed by testing, while formal verification can provide machine-checkable guarantees. Recently, researchers have proposed several benchmarks to evaluate the capabilities of LLMs in generating formally verifiable code, where LLMs need to formulate formal specifications, generate the corresponding code, and verify its correctness. However, existing benchmarks have two key limitations: (I) They primarily evaluate specification and code generation stage-wise, with code generation typically conditioned on an oracle specification. This setup overlooks whether strong stage-wise performance translates into end-to-end succe...

AuthorsJiaru Qian, Yihong Dong, Yongmin Li et al.
Primary categorycs.SE
Published30 September 2026
Last updated at source30 September 2026
cs.SEcs.AI
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