Machine-Generated, Machine-Checked Proofs for a Verified Compiler (arxiv.org)

In a significant development for the AI and programming languages community, a new report details the use of Claude Code, an AI-driven coding assistant, to automate the generation of machine-checked proofs for a verified compiler. This groundbreaking project involved mechanizing a substantial correctness proof for the administrative normal form (ANF) transformation in the CertiCoq compiler, a task that previously required months of effort from human experts for its closely related continuation-passing style (CPS) proof. The ANF proof ultimately spanned around 7,800 lines and was completed in about 96 hours, showcasing the potential for AI to streamline complex verification processes in compiler design. This accomplishment is significant as it demonstrates how advanced machine learning models can assist in formal verification tasks, challenging traditional notions of human expertise in proof writing. While the project underscores the promising capabilities of AI in enhancing productivity and efficiency in software verification, it also highlights limitations, such as the need for human oversight to guide the proof adaptation process. Overall, this work could pave the way for more automated solutions within the realm of verified compilers, potentially accelerating advancements in secure and reliable software development.