TrustedCode: Evaluating Large Language Models for Developing Trusted Code through Automated Program Verification

Muhammad Danial, Muhammad Taimoor Khan · 2026 · arXiv

DOI: 10.48550/arXiv.2610.30432 · open-access PDF

Abstract

Recent reports, such as "Who is using AI to code?", indicate that approximately 30\% of Python code contributions to GitHub are AI-generated. Given the inherent unreliability of this code, formal verification emerges as a promising approach to establish trust in software correctness. Although leveraging large language models (LLMs) for formal verification has garnered increasing attention, practical adoption remains limited due to the challenges in writing formal specifications and verifying program correctness against them. Existing tools predominantly support verification for languages such

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