Deep Combination of CDCL(T) and Local Search for Satisfiability Modulo Non-Linear Integer Arithmetic Theory
Xindi Zhang, Bohan Li, Shaowei Cai
Abstract
Satisfiability Modulo Theory (SMT) generalizes the propositional satisfiability problem (SAT) by extending support for various first-order background theories. In this paper, we focus on the SMT problems in Non-Linear Integer Arithmetic (NIA) theory, referred to as SMT(NIA), which has wide applications in software engineering. The dominant paradigm for SMT(NIA) is the CDCL(T) framework, while recently stochastic local search (SLS) has also shown its effectiveness. However, the cooperation between the two methods has not been studied yet. Motivated by the great success of the deep cooperation of CDCL and SLS for SAT, we propose a two-layer hybrid approach for SMT(NIA). The outer-layer interleaves between the inner-layer and an independent SLS solver. In the inner-layer, we take CDCL(T) as the main body, and design DCL(T)-guided SLS solver, which is invoked at branches corresponding to skeleton solutions and returns useful information to improve the branching heuristics of CDCL(T). We implement our ideas on top of the CDCL(T) tactic of Z3 with an SLS solver called LocalSMT, resulting in a hybrid solver dubbed HybridSMT. Extensive experiments are carried out on the standard SMT(NIA) benchmarks from SMT-LIB, where most of the instances are from real-world software engineering applications of termination and non-termination analysis. Experiment results show that HybridSMT significantly improves the CDCL(T) solver in Z3. Moreover, our solver can solve 10.36% more instances than the currently best SMT(NIA) solver, and is more efficient for software verification instances.
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