Runtime vs. Extracted Proof Size: An Exponential Gap for CDCL on QBFs

Abstract Conflict-driven clause learning (CDCL) is the dominating algorithmic paradigm for SAT solving and hugely successful in practice. In its lifted version QCDCL, it is one of the main approaches for solving quantified Boolean formulas (QBF). In both SAT and QBF, proofs can be efficiently extracted from runs of (Q)CDCL solvers. While for CDCL, it is known that the proof size in the underlying proof system propositional resolution matches the CDCL runtime up to a polynomial factor, we show that in QBF there is an exponential gap between QCDCL runtime and the size of the extracted proofs in QBF resolution systems. We demonstrate that this is not just a gap between QCDCL runtime and the size of any QBF resolution proof, but even the extracted proofs are exponentially smaller for some instances. Hence searching for a small proof via QCDCL (even with non-deterministic decision policies) will provably incur an exponential overhead for some instances.

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Publication Details

Journal
Journal of Automated Reasoning
Published
2025-11-12
DOI
https://doi.org/10.1007/s10817-025-09745-6
Primary Topic
Constraint Satisfaction and Optimization
Type
article
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article

Runtime vs. Extracted Proof Size: An Exponential Gap for CDCL on QBFs

Meena Mahajan, Olaf Beyersdorff, Benjamin Böhm
Journal of Automated Reasoning
Constraint Satisfaction and Optimization
article

Runtime vs. Extracted Proof Size: An Exponential Gap for CDCL on QBFs

Meena Mahajan, Olaf Beyersdorff, Benjamin Böhm
article en

Abstract

Abstract Conflict-driven clause learning (CDCL) is the dominating algorithmic paradigm for SAT solving and hugely successful in practice. In its lifted version QCDCL, it is one of the main approaches for solving quantified Boolean formulas (QBF). In both SAT and QBF, proofs can be efficiently extracted from runs of (Q)CDCL solvers. While for CDCL, it is known that the proof size in the underlying proof system propositional resolution matches the CDCL runtime up to a polynomial factor, we show that in QBF there is an exponential gap between QCDCL runtime and the size of the extracted proofs in QBF resolution systems. We demonstrate that this is not just a gap between QCDCL runtime and the size of any QBF resolution proof, but even the extracted proofs are exponentially smaller for some instances. Hence searching for a small proof via QCDCL (even with non-deterministic decision policies) will provably incur an exponential overhead for some instances.

Journal of Automated ReasoningVol. 69(4)
Homi Bhabha National Institute (IN), Institute of Mathematical Sciences (IN), Friedrich Schiller University Jena (DE)
Openalex Percentile: Top 61%
Constraint Satisfaction and Optimization
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Runtime vs. Extracted Proof Size: An Exponential Gap for CDCL on QBFs — Meena Mahajan, Olaf Beyersdorff, et al. · Journal of Automated Reasoning (2025) | TGRS Research Map | TGRS