PyVeritas: On Verifying Python via LLM-Based Transpilation and Bounded Model Checking for C
Image credit: P-AI-FM-26 WorkshopAbstract
Python has become the dominant language for general-purpose programming, yet it lacks robust tools for formal verification. In contrast, programmers working in languages such as C benefit from mature model checkers, for example CBMC, which enable exhaustive symbolic reasoning and fault localisation. The inherent complexity of Python, coupled with the verbosity and low-level nature of existing transpilers (e.g., Cython), have historically limited the applicability of formal verification to Python programs. In this talk, I am going to present PyVeritas, a novel framework that leverages Large Language Models (LLMs) for high-level transpilation from Python to C, followed by bounded model checking and MaxSAT-based fault localisation in the generated C code. PyVeritas enables verification and bug localisation for Python code using existing model checking tools for C. Our empirical evaluation on two Python benchmarks demonstrates that LLM-based transpilation can achieve a high degree of accuracy, up to 80–90% for some LLMs, enabling effective development environment that supports assertion-based verification and interpretable fault diagnosis for small yet non-trivial Python programs.
Date
Jan 26, 2026 9:00 AM — 9:15 AM
Event
Location
AAAI 2026
Singapore, Singapore.