22 research outputs found
Integrating Conflict Driven Clause Learning to Local Search
This article introduces SatHyS (SAT HYbrid Solver), a novel hybrid approach
for propositional satisfiability. It combines local search and conflict driven
clause learning (CDCL) scheme. Each time the local search part reaches a local
minimum, the CDCL is launched. For SAT problems it behaves like a tabu list,
whereas for UNSAT ones, the CDCL part tries to focus on minimum unsatisfiable
sub-formula (MUS). Experimental results show good performances on many classes
of SAT instances from the last SAT competitions
Anytime Computation of Cautious Consequences in Answer Set Programming
Query answering in Answer Set Programming (ASP) is usually solved by
computing (a subset of) the cautious consequences of a logic program. This task
is computationally very hard, and there are programs for which computing
cautious consequences is not viable in reasonable time. However, current ASP
solvers produce the (whole) set of cautious consequences only at the end of
their computation. This paper reports on strategies for computing cautious
consequences, also introducing anytime algorithms able to produce sound answers
during the computation.Comment: To appear in Theory and Practice of Logic Programmin
Handling Conflicts in Depth-First Search for LTL Tableau to Debug Compliance Based Languages
Providing adequate tools to tackle the problem of inconsistent compliance
rules is a critical research topic. This problem is of paramount importance to
achieve automatic support for early declarative design and to support evolution
of rules in contract-based or service-based systems. In this paper we
investigate the problem of extracting temporal unsatisfiable cores in order to
detect the inconsistent part of a specification. We extend conflict-driven
SAT-solver to provide a new conflict-driven depth-first-search solver for
temporal logic. We use this solver to compute LTL unsatisfiable cores without
re-exploring the history of the solver.Comment: In Proceedings FLACOS 2011, arXiv:1109.239
On Algorithms and Complexity for Sets with Cardinality Constraints
Typestate systems ensure many desirable properties of imperative programs,
including initialization of object fields and correct use of stateful library
interfaces. Abstract sets with cardinality constraints naturally generalize
typestate properties: relationships between the typestates of objects can be
expressed as subset and disjointness relations on sets, and elements of sets
can be represented as sets of cardinality one. Motivated by these applications,
this paper presents new algorithms and new complexity results for constraints
on sets and their cardinalities. We study several classes of constraints and
demonstrate a trade-off between their expressive power and their complexity.
Our first result concerns a quantifier-free fragment of Boolean Algebra with
Presburger Arithmetic. We give a nondeterministic polynomial-time algorithm for
reducing the satisfiability of sets with symbolic cardinalities to constraints
on constant cardinalities, and give a polynomial-space algorithm for the
resulting problem.
In a quest for more efficient fragments, we identify several subclasses of
sets with cardinality constraints whose satisfiability is NP-hard. Finally, we
identify a class of constraints that has polynomial-time satisfiability and
entailment problems and can serve as a foundation for efficient program
analysis.Comment: 20 pages. 12 figure
SAT Competition 2020
The SAT Competitions constitute a well-established series of yearly open international algorithm implementation competitions, focusing on the Boolean satisfiability (or propositional satisfiability, SAT) problem. In this article, we provide a detailed account on the 2020 instantiation of the SAT Competition, including the new competition tracks and benchmark selection procedures, overview of solving strategies implemented in top-performing solvers, and a detailed analysis of the empirical data obtained from running the competition. (C) 2021 The Authors. Published by Elsevier B.V.Peer reviewe