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 language | English |
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Title of host publication | Bridging the Gap Between AI and Reality - 2nd International Conference, AISoLA 2024, Proceedings |
Editors | Bernhard Steffen |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 167-182 |
Number of pages | 16 |
ISBN (Print) | 9783031754333 |
DOIs | |
State | Published - 2025 |
Event | 2nd International Conference on Bridging the Gap Between AI and Reality, AISoLA 2024 - Crete, Greece Duration: 30 Oct 2024 → 3 Nov 2024 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 15217 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 2nd International Conference on Bridging the Gap Between AI and Reality, AISoLA 2024 |
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Country/Territory | Greece |
City | Crete |
Period | 30/10/24 → 3/11/24 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.