1,267 research outputs found
Adapting Real Quantifier Elimination Methods for Conflict Set Computation
The satisfiability problem in real closed fields is decidable. In the context
of satisfiability modulo theories, the problem restricted to conjunctive sets
of literals, that is, sets of polynomial constraints, is of particular
importance. One of the central problems is the computation of good explanations
of the unsatisfiability of such sets, i.e.\ obtaining a small subset of the
input constraints whose conjunction is already unsatisfiable. We adapt two
commonly used real quantifier elimination methods, cylindrical algebraic
decomposition and virtual substitution, to provide such conflict sets and
demonstrate the performance of our method in practice
An Instantiation-Based Approach for Solving Quantified Linear Arithmetic
This paper presents a framework to derive instantiation-based decision
procedures for satisfiability of quantified formulas in first-order theories,
including its correctness, implementation, and evaluation. Using this framework
we derive decision procedures for linear real arithmetic (LRA) and linear
integer arithmetic (LIA) formulas with one quantifier alternation. Our
procedure can be integrated into the solving architecture used by typical SMT
solvers. Experimental results on standardized benchmarks from model checking,
static analysis, and synthesis show that our implementation of the procedure in
the SMT solver CVC4 outperforms existing tools for quantified linear
arithmetic
A Survey of Satisfiability Modulo Theory
Satisfiability modulo theory (SMT) consists in testing the satisfiability of
first-order formulas over linear integer or real arithmetic, or other theories.
In this survey, we explain the combination of propositional satisfiability and
decision procedures for conjunctions known as DPLL(T), and the alternative
"natural domain" approaches. We also cover quantifiers, Craig interpolants,
polynomial arithmetic, and how SMT solvers are used in automated software
analysis.Comment: Computer Algebra in Scientific Computing, Sep 2016, Bucharest,
Romania. 201
SMT-based Model Checking for Recursive Programs
We present an SMT-based symbolic model checking algorithm for safety
verification of recursive programs. The algorithm is modular and analyzes
procedures individually. Unlike other SMT-based approaches, it maintains both
"over-" and "under-approximations" of procedure summaries. Under-approximations
are used to analyze procedure calls without inlining. Over-approximations are
used to block infeasible counterexamples and detect convergence to a proof. We
show that for programs and properties over a decidable theory, the algorithm is
guaranteed to find a counterexample, if one exists. However, efficiency depends
on an oracle for quantifier elimination (QE). For Boolean Programs, the
algorithm is a polynomial decision procedure, matching the worst-case bounds of
the best BDD-based algorithms. For Linear Arithmetic (integers and rationals),
we give an efficient instantiation of the algorithm by applying QE "lazily". We
use existing interpolation techniques to over-approximate QE and introduce
"Model Based Projection" to under-approximate QE. Empirical evaluation on
SV-COMP benchmarks shows that our algorithm improves significantly on the
state-of-the-art.Comment: originally published as part of the proceedings of CAV 2014; fixed
typos, better wording at some place
A Generalized Framework for Virtual Substitution
We generalize the framework of virtual substitution for real quantifier
elimination to arbitrary but bounded degrees. We make explicit the
representation of test points in elimination sets using roots of parametric
univariate polynomials described by Thom codes. Our approach follows an early
suggestion by Weispfenning, which has never been carried out explicitly.
Inspired by virtual substitution for linear formulas, we show how to
systematically construct elimination sets containing only test points
representing lower bounds
A CDCL-style calculus for solving non-linear constraints
In this paper we propose a novel approach for checking satisfiability of
non-linear constraints over the reals, called ksmt. The procedure is based on
conflict resolution in CDCL style calculus, using a composition of symbolical
and numerical methods. To deal with the non-linear components in case of
conflicts we use numerically constructed restricted linearisations. This
approach covers a large number of computable non-linear real functions such as
polynomials, rational or trigonometrical functions and beyond. A prototypical
implementation has been evaluated on several non-linear SMT-LIB examples and
the results have been compared with state-of-the-art SMT solvers.Comment: 17 pages, 3 figures; accepted at FroCoS 2019; software available at
<http://informatik.uni-trier.de/~brausse/ksmt/
A Lazy SMT-Solver for a Non-Linear Subset of Real Algebra
There are several methods for the synthesis and analysis of hybrid
systems that require efficient algorithms and tools for satisfiability
checking. For analysis, e.g., bounded model checking describes
counterexamples of a fixed length by logical formulas, whose
satisfiability corresponds to the existence of such a counterexample.
As an example for parameter synthesis, we can state the correctness of
a parameterized system by a logical formula; the solution set of
the formula gives us possible safe instances of the parameters.
For discrete systems, which can be described by propositional logic
formulas, SAT-solvers can be used for the satisfiability checks. For
hybrid systems, having mixed discrete-continuous behavior, SMT-solvers
are needed. SMT-solving extends SAT with theories, and has its main
focus on linear arithmetic, which is sufficient to handle, e.g.,
linear hybrid systems. However, there are only few solvers for
more expressive but still decidable logics like the
first-order theory of the reals with addition and multiplication --
real algebra. Since the synthesis and analysis of non-linear
hybrid systems requires such a powerful logic, we need efficient
SMT-solvers for real algebra. Our goal is to develop such an
SMT-solver for the real algebra, which is both complete and
efficient
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