Computer Science > Programming Languages
arXiv:2310.09342 (cs)
[Submitted on 13 Oct 2023 (v1), last revised 12 Feb 2024 (this version, v3)]
Title:Ranking LLM-Generated Loop Invariants for Program Verification
Authors:Saikat Chakraborty,Shuvendu K. Lahiri,Sarah Fakhoury,Madanlal Musuvathi,Akash Lal,Aseem Rastogi,Aditya Senthilnathan,Rahul Sharma,Nikhil Swamy
View a PDF of the paper titled Ranking LLM-Generated Loop Invariants for Program Verification, by Saikat Chakraborty and 8 other authors
View PDFHTML (experimental)Abstract:Synthesizing inductive loop invariants is fundamental to automating program verification. In this work, we observe that Large Language Models (such as gpt-3.5 or gpt-4) are capable of synthesizing loop invariants for a class of programs in a 0-shot setting, yet require several samples to generate the correct invariants. This can lead to a large number of calls to a program verifier to establish an invariant. To address this issue, we propose a {\it re-ranking} approach for the generated results of LLMs. We have designed a ranker that can distinguish between correct inductive invariants and incorrect attempts based on the problem definition. The ranker is optimized as a contrastive ranker. Experimental results demonstrate that this re-ranking mechanism significantly improves the ranking of correct invariants among the generated candidates, leading to a notable reduction in the number of calls to a verifier. The source code and the experimental data for this paper are available in \url{this https URL}.
| Comments: | Findings of The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP-findings 2023) |
| Subjects: | Programming Languages (cs.PL); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Software Engineering (cs.SE) |
| Cite as: | arXiv:2310.09342 [cs.PL] |
| (orarXiv:2310.09342v3 [cs.PL] for this version) | |
| https://doi.org/10.48550/arXiv.2310.09342 arXiv-issued DOI via DataCite |
Submission history
From: Saikat Chakraborty [view email][v1] Fri, 13 Oct 2023 18:13:52 UTC (813 KB)
[v2] Wed, 18 Oct 2023 18:18:43 UTC (811 KB)
[v3] Mon, 12 Feb 2024 20:25:31 UTC (811 KB)
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View a PDF of the paper titled Ranking LLM-Generated Loop Invariants for Program Verification, by Saikat Chakraborty and 8 other authors
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