AxDafny: Agentic Verified Code Generation in Dafny
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.
Cite
@article{arxiv.2606.32007,
title = {AxDafny: Agentic Verified Code Generation in Dafny},
author = {Benjamin Breen and Austin Letson and Borja Requena Pozo and Leopoldo Sarra},
journal= {arXiv preprint arXiv:2606.32007},
year = {2026}
}