Random CNF-XOR Formulas

Date
2017-04-21
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Abstract

Boolean Satisfiability (SAT) is fundamental in many diverse areas such as artificial intelligence, formal verification, and biology. Recent universal-hashing based approaches to the problems of sampling and counting crucially depend on the runtime performance of specialized SAT solvers on formulas expressed as the conjunction of both k-CNF constraints and variable-width XOR constraints (known as CNF-XOR formulas), but random CNF-XOR formulas are unexplored in prior work.

In this work, we present the first study of random CNF-XOR formulas. We prove that a phase-transition in the satisfiability of random CNF-XOR formulas exists for k=2 and (when the number of k-CNF constraints is small) for k>2. We empirically demonstrate that a state-of-the-art SAT solver scales exponentially on random CNF-XOR formulas across many clause densities, peaking around the empirical phase-transition location. Finally, we prove that the solution space of random CNF-XOR formulas 'shatters' at all nonzero XOR-clause densities into well-separated components.

Description
Degree
Master of Science
Type
Thesis
Keywords
Boolean Satisfiability, SAT, Constrained Counting, Constrained Sampling, Hashing-Based Algorithms, Phase Transition, Satisfiability Threshold
Citation

Dudek, Jeffrey M. "Random CNF-XOR Formulas." (2017) Master’s Thesis, Rice University. https://hdl.handle.net/1911/96156.

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