Recent work has shown that Large Language Models (LLMs) are not only a suitable tool for code generation but also capable of generating annotation-based code specifications. Scaling these methodologies may allow us to deduce provable correctness guarantees for large-scale software systems. In comparison to other LLM tasks, the application field of deductive verification has the notable advantage of providing a rigorous toolset to check LLM-generated solutions. This short paper provides early results on how this rigorous toolset can be used to reliably elicit correct specification annotations from an unreliable LLM oracle.
@article{arxiv.2502.01573,
title = {Next Steps in LLM-Supported Java Verification},
author = {Samuel Teuber and Bernhard Beckert},
journal= {arXiv preprint arXiv:2502.01573},
year = {2025}
}
Comments
Accepted to NSE 2025, 1st International Workshop on Neuro-Symbolic Software Engineering (ICSE Workshop), 6 pages, 3 figures