SAT-based explicit LTL_f satisfiability checking

Linear Temporal Logic over finite traces (LTL_f) was proposed in 2013 and has attracted increasing interest around the AI community. Though the theoretic basis for LTL_f has been thoroughly explored since that time, there are still few algorithmic tools that are able to provide an efficient reasoning strategy for LTL_f. In this paper, we present a SAT-based framework for LTL_f satisfiability checking, which is the foundation of LTL_f reasoning. We use propositional SAT-solving techniques to construct a transition system, which is an automata-style structure, for an input LTL_f formula; satisfiability checking is then reduced to a path-search problem over this transition system. Based on this framework, we further present CDLSC (Conflict-Driven LTL_f Satisfiability Checking), a novel algorithm (heuristic) that leverages information produced by propositional SAT solvers, utilizing both satisfiability and unsatisfiability results. More specifically, the satisfiable results of the SAT solver are used to create new states of the transition system and the unsatisfiable results to accelerate the path search over the system. We evaluate all 5 off-the-shelf LTL_f satisfiability algorithms against our new approach CDLSC. Based on a comprehensive evaluation over 4 different LTL_f benchmark suits with a total amount of 9317 formulas, our time-cost analysis shows that 1) CDLSC performs best on checking unsatisfiable formulas by achieving approximately a 4X time speedup, compared to the second-best solution (K-LIVE [1]); 2) Although no approaches dominate checking satisfiable formulas, CDLSC performs best on 2 of the total 4 tested satisfiable benchmark suits; and 3) CDLSC gains the best overall performance when considering both satisfiable and unsatisfiable instances.