LLMs Generate Formal Semantics for Lean-Verified Interpreters

1 reports archived1 independent sourcesupdated 10/20/2026, 09:57:24

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Basis AI researchers used LLMs to generate formal semantics for a small programming language and employed Lean to prove that the interpreter adheres to these rules even after compilation to RISC-V instructions. This study highlights progress in creating 'verified software' with machine-checked mathematical proofs to eliminate bug classes, aiming to extend this rigor to complex systems like CPython.

LATEST/Basis AI researchers used LLMs to generate formal semantics for a small programming language and employed Lean to prove that the interpreter adheres to these rules even after compilation to RISC-V instructions. This study highlights progress in creating 'verified software' with machine-checked mathematical proofs to eliminate bug classes, aiming to extend this rigor to complex systems like CPython.

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Hacker News AIT2·Oct 20, 09:5778 pts
LLMs Generate Formal Semantics for Lean-Verified Interpreters
- LLMs are utilized to automatically generate precise formal semantics for programming languages.
- Lean theorem prover verifies interpreter behavioral consistency from high-level code down to RISC-V assembly.
- The goal is to apply this machine-verified methodology to complex runtimes like CPython.
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