Leveraging LLMs for Formal Software Requirements -- Challenges and Prospects
Abstract
Software correctness is ensured mathematically through formal verification, which involves the resources of generating formal requirement specifications and having an implementation that must be verified. Tools such as model-checkers and theorem provers ensure software correctness by verifying the implementation against the specification. Formal methods deployment is regularly enforced in the development of safety-critical systems e.g. aerospace, medical devices and autonomous systems. Generating these specifications from informal and ambiguous natural language requirements remains the key challenge. Our project, VERIFAI^{1}, aims to investigate automated and semi-automated approaches to bridge this gap, using techniques from Natural Language Processing (NLP), ontology-based domain modelling, artefact reuse, and large language models (LLMs). This position paper presents a preliminary synthesis of relevant literature to identify recurring challenges and prospective research directions in the generation of verifiable specifications from informal requirements.
Cite
@article{arxiv.2507.14330,
title = {Leveraging LLMs for Formal Software Requirements -- Challenges and Prospects},
author = {Arshad Beg and Diarmuid O'Donoghue and Rosemary Monahan},
journal= {arXiv preprint arXiv:2507.14330},
year = {2025}
}
Comments
Overlay2025 - 7th International Workshop on Artificial Intelligence and fOrmal VERification, Logic, Automata, and sYnthesis. [Accepted]. To be held on 26th of October, 2025