AxDafny: Agentic Verified Code Generation in Dafny

• URL: http://arxiv.org/abs/2606.32007v1
• Date: Tue, 30 Jun 2026 17:39:43 GMT
• Title: AxDafny: Agentic Verified Code Generation in Dafny
• Abstract summary: We study agentic code generation in Dafny, where a model must generate both executable code and the proof artifacts for verification.<n>We present AxDafny, a verifier-guided repair framework that iteratively generates implementations, invariants, assertions, and termination arguments.<n>We also introduce LiveCodeBench-Pro-Dafny, a benchmark of 250 competition-style programming problems translated into Dafny with formal specifications and a verifier-based evaluation harness.
• Score: 0.3499870393443268
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We study agentic code generation in Dafny, where a model must generate both executable code and the proof artifacts for verification. We present AxDafny, a verifier-guided repair framework that iteratively generates implementations, invariants, assertions, and termination arguments. We also introduce LiveCodeBench-Pro-Dafny (LCB-Pro-Dafny), a benchmark of 250 competition-style programming problems translated into Dafny with formal specifications and a verifier-based evaluation harness. On LCB-Pro-Dafny, AxDafny substantially improves verification success over baseline GPT-5.5 performance. On DafnyBench, AxDafny achieves 92.7\% verification success, outperforming the strongest previously reported proof-hint baseline by 6.5 percentage points. Lastly, we show that verification success and runtime test performance measure different aspects of generated code.

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