The hard problems are almost everywhere for random CNF-XOR formulas

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Abstract

Recent universal-hashing based approaches to sampling and counting crucially depend on the runtime performance of SAT solvers on formulas expressed as the conjunction of both CNF constraints and variable-width XOR constraints (known as CNF-XOR formulas). In this paper, we present the first study of the runtime behavior of SAT solvers equipped with XOR-reasoning techniques on random CNF-XOR formulas. We empirically demonstrate that a state-of-the-art SAT solver scales exponentially on random CNF-XOR formulas across a wide range of XOR-clause densities, peaking around the empirical phase-transition location. On the theoretical front, we prove that the solution space of a random CNF-XOR formula 'shatters' at all nonzero XOR-clause densities into wellseparated components, similar to the behavior seen in random CNF formulas known to be difficult for many SAT-solving algorithms.

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Dudek, J. M., Meel, K. S., & Vardi, M. Y. (2017). The hard problems are almost everywhere for random CNF-XOR formulas. In IJCAI International Joint Conference on Artificial Intelligence (Vol. 0, pp. 600–606). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2017/84

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