LeanCSP: A Framework for Certifying Constraint Reformulation and Solving in Lean
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Abstract (arXiv)
Constraint programming is a core technology for solving complex combinatorial problems in scheduling, planning, configuration, and verification. Trusting its results therefore demands guarantees at two levels: that reformulations applied beforehand are semantics-preserving, and that solvers produce correct answers. In this work, we introduce a framework that addresses both verification levels in the Lean theorem prover: it can be used to prove formulation-level properties, such as equivalence, equisatisfiability, and the correctness of symmetry-breaking constraints, parametrically for entire problem families; and to check solver-produced certificates for individual instances via translation backends to external formats such as MiniZinc, SMT-LIB, and OPB. Combining both levels yields an end-to-end workflow that establishes the satisfiability or unsatisfiability of a constraint problem without trusting the external solver. Experimental results show that our framework's verified symmetry breaking also pays off in practice: a single parametric proof per problem family, reused across all instance sizes, reduces solver search effort by a factor of up to 2x10^7, while the entire in-Lean certification stays affordable, taking at most a few minutes for our largest instances.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 47 references that are in the map. First posted on arXiv 30 Jul 2026.
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References · 12
- 2019The Lean mathematical librarycited by 127
- 2022Certifying Parity Reasoning Efficiently Using Pseudo-Boolean Proofscited by 14
- 2022Certified Symmetry and Dominance Breaking for Combinatorial Optimisationcited by 13
- 2016Efficient Certified RAT Verificationcited by 12
- 2025Lean-SMT: An SMT tactic for discharging proof goals in Leancited by 9
- 2022Formalising the h-principle and sphere eversioncited by 6
- 2024Lean4Lean: Verifying a Typechecker for Lean, in Leancited by 5
- 2020Detecting Critical Bugs in SMT Solvers Using Blackbox Mutational Fuzzingcited by 4
- 2024Formal Verification of the Empty Hexagon Numbercited by 4
- 2020Formally Verified SAT-Based AI Planningcited by 3
- 2020Formally Verified Transformation of Non-binary Constraints into Binary Constraintscited by 1
- 2026PBLean: Pseudo-Boolean Proof Certificates for Lean 4cited by 1
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