18,801 research outputs found
Efficient CTL Verification via Horn Constraints Solving
The use of temporal logics has long been recognised as a fundamental approach
to the formal specification and verification of reactive systems. In this
paper, we take on the problem of automatically verifying a temporal property,
given by a CTL formula, for a given (possibly infinite-state) program. We
propose a method based on encoding the problem as a set of Horn constraints.
The method takes a program, modeled as a transition system, and a property
given by a CTL formula as input. It first generates a set of forall-exists
quantified Horn constraints and well-foundedness constraints by exploiting the
syntactic structure of the CTL formula. Then, the generated set of constraints
are solved by applying an off-the-shelf Horn constraints solving engine. The
program is said to satisfy the property if and only if the generated set of
constraints has a solution. We demonstrate the practical promises of the method
by applying it on a set of challenging examples. Although our method is based
on a generic Horn constraint solving engine, it is able to outperform
state-of-art methods specialised for CTL verification.Comment: In Proceedings HCVS2016, arXiv:1607.0403
SAT-based Explicit LTL Reasoning
We present here a new explicit reasoning framework for linear temporal logic
(LTL), which is built on top of propositional satisfiability (SAT) solving. As
a proof-of-concept of this framework, we describe a new LTL satisfiability
tool, Aalta\_v2.0, which is built on top of the MiniSAT SAT solver. We test the
effectiveness of this approach by demonnstrating that Aalta\_v2.0 significantly
outperforms all existing LTL satisfiability solvers. Furthermore, we show that
the framework can be extended from propositional LTL to assertional LTL (where
we allow theory atoms), by replacing MiniSAT with the Z3 SMT solver, and
demonstrating that this can yield an exponential improvement in performance
Expressive Stream Reasoning with Laser
An increasing number of use cases require a timely extraction of non-trivial
knowledge from semantically annotated data streams, especially on the Web and
for the Internet of Things (IoT). Often, this extraction requires expressive
reasoning, which is challenging to compute on large streams. We propose Laser,
a new reasoner that supports a pragmatic, non-trivial fragment of the logic
LARS which extends Answer Set Programming (ASP) for streams. At its core, Laser
implements a novel evaluation procedure which annotates formulae to avoid the
re-computation of duplicates at multiple time points. This procedure, combined
with a judicious implementation of the LARS operators, is responsible for
significantly better runtimes than the ones of other state-of-the-art systems
like C-SPARQL and CQELS, or an implementation of LARS which runs on the ASP
solver Clingo. This enables the application of expressive logic-based reasoning
to large streams and opens the door to a wider range of stream reasoning use
cases.Comment: 19 pages, 5 figures. Extended version of accepted paper at ISWC 201
MCMAS-SLK: A Model Checker for the Verification of Strategy Logic Specifications
We introduce MCMAS-SLK, a BDD-based model checker for the verification of
systems against specifications expressed in a novel, epistemic variant of
strategy logic. We give syntax and semantics of the specification language and
introduce a labelling algorithm for epistemic and strategy logic modalities. We
provide details of the checker which can also be used for synthesising agents'
strategies so that a specification is satisfied by the system. We evaluate the
efficiency of the implementation by discussing the results obtained for the
dining cryptographers protocol and a variant of the cake-cutting problem
- …