An Improved Algorithm for Sparse Instances of SAT
Data Structures and Algorithms
2024-11-13 v1
Abstract
We show that the CNF satisfiability problem (SAT) can be solved in time , where is either the maximum number of occurrences of any variable or the average number of occurrences of all variables if no variable occurs only once. This improves upon the known upper bound of by Wahlstrm (SAT 2005) and by Peng and Xiao (IJCAI 2023). For , our algorithm is better than previous results. Our main technical result is an algorithm that runs in for 3-occur-SAT, a restricted instance of SAT where all variables have at most 3 occurrences. Through deeper case analysis and a reduction rule that allows us to resolve many variables under a relatively broad criteria, we are able to circumvent the bottlenecks in previous algorithms.
Cite
@article{arxiv.2411.07389,
title = {An Improved Algorithm for Sparse Instances of SAT},
author = {Sanjay Jain and Tzeh Yuan Neoh and Frank Stephan},
journal= {arXiv preprint arXiv:2411.07389},
year = {2024}
}