FVSpec: Real-World Property-Based Tests as Lean Challenges
As AI systems generate an ever-growing share of the world's code, formal verification offers a principled way to ensure that code is correct, and AI itself may be able to shoulder much of the verification burden. Yet we lack a clear picture of how well today's models and agents perform on verification tasks drawn from real-world software, since existing benchmarks rely largely on curated or synthetic problems, or focus on math rather than program verification. To close this gap, we present a benchmark for evaluating AI on real-world formal software verification tasks. We first scrape 7,413 distinct property-based tests (PBTs) from real-world Python repositories, then automatically transla...
| Authors | Quinn Dougherty, Max von Hippel, Simon Henniger et al. |
|---|---|
| Primary category | cs.SE |
| Published | 31 May 2026 |
| Last updated at source | 14 September 2026 |
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