DafnyBench: A Benchmark for Formal Software Verification

We introduce DafnyBench, the largest benchmark of its kind for training and evaluating machine learning systems for formal software verification. We test the ability of LLMs such as GPT-4 and Claude 3 to auto-generate enough hints for the Dafny formal verification engine to successfully verify over...

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Bibliographic Details
Published inarXiv.org
Main Authors Loughridge, Chloe, Sun, Qinyi, Ahrenbach, Seth, Cassano, Federico, Sun, Chuyue, Sheng, Ying, Mudide, Anish, Md Rakib Hossain Misu, Amin, Nada, Tegmark, Max
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 12.06.2024
Subjects
Benchmarks
Large language models
Machine learning
Program verification (computers)
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Summary:We introduce DafnyBench, the largest benchmark of its kind for training and evaluating machine learning systems for formal software verification. We test the ability of LLMs such as GPT-4 and Claude 3 to auto-generate enough hints for the Dafny formal verification engine to successfully verify over 750 programs with about 53,000 lines of code. The best model and prompting scheme achieved 68% success rate, and we quantify how this rate improves when retrying with error message feedback and how it deteriorates with the amount of required code and hints. We hope that DafnyBench will enable rapid improvements from this baseline as LLMs and verification techniques grow in quality.
ISSN:2331-8422