IDS is an agentic LLM system that incrementally synthesizes both implementation and proof for distributed key-value stores, succeeding on all 7 specs where prior agents succeeded on only 2.
miniCodeProps: A minimal benchmark for proving code properties
4 Pith papers cite this work. Polarity classification is still indexing.
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s2n-bignum-bench is a new benchmark requiring LLMs to synthesize HOL Light proofs for real-world low-level cryptographic assembly code.
VeriContest supplies 946 problems with specs, code, proofs, and tests to benchmark verifiable code generation in Rust/Verus, showing models reach 92% on code but only 5% end-to-end on full verifiable synthesis.
BRIDGE improves Lean executable correctness up to 1.5x and sample efficiency roughly 2x over direct prompting by using domain-guided intermediate representations across code, specs, and proofs.
citing papers explorer
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Inductive Deductive Synthesis: Enabling AI to Generate Formally Verified Systems
IDS is an agentic LLM system that incrementally synthesizes both implementation and proof for distributed key-value stores, succeeding on all 7 specs where prior agents succeeded on only 2.
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s2n-bignum-bench: A practical benchmark for evaluating low-level code reasoning of LLMs
s2n-bignum-bench is a new benchmark requiring LLMs to synthesize HOL Light proofs for real-world low-level cryptographic assembly code.
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VeriContest: A Competitive-Programming Benchmark for Verifiable Code Generation
VeriContest supplies 946 problems with specs, code, proofs, and tests to benchmark verifiable code generation in Rust/Verus, showing models reach 92% on code but only 5% end-to-end on full verifiable synthesis.
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BRIDGE: Building Representations In Domain Guided Program Synthesis
BRIDGE improves Lean executable correctness up to 1.5x and sample efficiency roughly 2x over direct prompting by using domain-guided intermediate representations across code, specs, and proofs.