LLM-Based Scheme for Synthesis of Formal Verification Algorithms

Itay Cohen, Doron Peled

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The research of Large Language Models (LLMs) has significant ground to cover in the context of formal verification. In this work, we present a methodology that aims to increase the reliability of code synthesized through the use of LLMs. Our approach capitalizes on the intrinsic knowledge embedded within LLMs to achieve a more reliable code synthesis. We specifically illustrate the possibility of teaching model checking and runtime verification (RV) algorithms through our approach. Our experiments demonstrate that LLMs grasp the concept of dynamic programming, allowing them to synthesize code for these verification tasks with minimal guidance.

Original languageEnglish
Title of host publicationBridging the Gap Between AI and Reality - 2nd International Conference, AISoLA 2024, Proceedings
EditorsBernhard Steffen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages167-182
Number of pages16
ISBN (Print)9783031754333
DOIs
StatePublished - 2025
Event2nd International Conference on Bridging the Gap Between AI and Reality, AISoLA 2024 - Crete, Greece
Duration: 30 Oct 20243 Nov 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15217 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Bridging the Gap Between AI and Reality, AISoLA 2024
Country/TerritoryGreece
CityCrete
Period30/10/243/11/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

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