Zian Wang, Qin Li, Weisong Sun, Haibin Cai · 2026 · arXiv
DOI: 10.48550/arXiv.2610.30725 · open-access PDF
AI-assisted code generation amplifies the demand for automated formal verification. Generated programs must not only be executable but also accompanied by machine-checkable evidence of correctness. Existing approaches can synthesize functionally plausible code or plausible-looking specifications from natural-language prompts; however, they do not explicitly co-design the implementation and specification as a unified artifact optimized for verification. Consequently, automated verifiers often fail to discharge proof obligations. Typical failure modes include missing or implicit proof anchors, p
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