16 research outputs found
SAT-based Explicit LTLf Satisfiability Checking
We present here a SAT-based framework for LTLf (Linear Temporal Logic on
Finite Traces) satisfiability checking. We use propositional SAT-solving
techniques to construct a transition system for the input LTLf formula;
satisfiability checking is then reduced to a path-search problem over this
transition system. Furthermore, we introduce CDLSC (Conflict-Driven LTLf
Satisfiability Checking), a novel algorithm that leverages information produced
by propositional SAT solvers from both satisfiability and unsatisfiability
results. Experimental evaluations show that CDLSC outperforms all other
existing approaches for LTLf satisfiability checking, by demonstrating an
approximate four-fold speedup compared to the second-best solver
Towards compositional automated planning
The development of efficient propositional satisfiability problem solving algorithms (SAT solvers) in the past two decades has made automated planning using SAT-solvers\ua0an established AI planning approach. Modern SAT solvers can\ua0accommodate a wide variety of planning problems with a large number of variables. However, fast computing of reasonably long\ua0plans proves challenging for planning as satisfiability. In order to address this challenge, we present a compositional approach based on abstraction refinement that iteratively generates, solves and composes partial solutions from a parameterized planning problem. We show that this approach decomposes the monolithic planning problem into smaller problems and thus significantly speeds up plan calculation, at least for a class of tested planning problems
Decidable Fragments of LTLf Modulo Theories
We study Linear Temporal Logic Modulo Theories over Finite Traces (LTLMTf), a recently introduced extension of LTL over finite traces (LTLf) where propositions are replaced by first-order formulas and where first-order variables referring to different time points can be compared. In general, LTLMTf was shown to be semi-decidable for any decidable first-order theory (e.g., linear arithmetics), with a tableau-based semi-decision procedure. In this paper we present a sound and complete pruning rule for the LTLMTf tableau. We show that for any LTLMTf formula that satisfies an abstract, semantic condition, that we call finite memory, the tableau augmented with the new rule is also guaranteed to terminate. Last but not least, this technique allows us to establish novel decidability results for the satisfiability of several fragments of LTLMTf, as well as to give new decidability proofs for classes that are already known
Synthesis from Weighted Specifications with Partial Domains over Finite Words
info:eu-repo/semantics/publishe
Streamlining Temporal Formal Verification over Columnar Databases
Recent findings demonstrate how database technology enhances the computation of formal verification tasks expressible in linear time logic for finite traces (LTLf). Human-readable declarative languages also help the common practitioner to express temporal constraints in a straightforward and accessible language. Notwithstanding the former, this technology is in its infancy, and therefore, few optimization algorithms are known for dealing with massive amounts of information audited from real systems. We, therefore, present four novel algorithms subsuming entire LTLf expressions while outperforming previous state-of-the-art implementations on top of KnoBAB, thus postulating the need for the corresponding, leading to the formulation of novel xtLTLf-derived algebraic operators