FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints

TL;DR

FourierSAT introduces a novel algebraic framework using Fourier analysis of Boolean functions to solve hybrid Boolean constraints, improving robustness on specific benchmark classes by guiding search with gradient information.

Contribution

The paper presents FourierSAT, a new incomplete SAT solver based on Fourier analysis, capable of handling diverse constraints through a continuous optimization approach.

Findings

FourierSAT outperforms existing solvers on certain benchmark classes.

The algebraic Fourier framework effectively guides the search process.

FourierSAT demonstrates robustness in solving hybrid Boolean constraints.

Abstract

The Boolean SATisfiability problem (SAT) is of central importance in computer science. Although SAT is known to be NP-complete, progress on the engineering side, especially that of Conflict-Driven Clause Learning (CDCL) and Local Search SAT solvers, has been remarkable. Yet, while SAT solvers aimed at solving industrial-scale benchmarks in Conjunctive Normal Form (CNF) have become quite mature, SAT solvers that are effective on other types of constraints, e.g., cardinality constraints and XORs, are less well studied; a general approach to handling non-CNF constraints is still lacking. In addition, previous work indicated that for specific classes of benchmarks, the running time of extant SAT solvers depends heavily on properties of the formula and details of encoding, instead of the scale of the benchmarks, which adds uncertainty to expectations of running time. To address the issues above, we design FourierSAT, an incomplete SAT solver based on Fourier analysis of Boolean functions, a technique to represent Boolean functions by multilinear polynomials. By such a reduction to continuous optimization, we propose an algebraic framework for solving systems consisting of different types of constraints. The idea is to leverage gradient information to guide the search process in the direction of local improvements. Empirical results demonstrate that FourierSAT is more robust than other solvers on certain classes of benchmarks.