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/******************************************************************************
* Top contributors (to current version):
* Yoni Zohar
*
* This file is part of the cvc5 project.
*
* Copyright (c) 2009-2021 by the authors listed in the file AUTHORS
* in the top-level source directory and their institutional affiliations.
* All rights reserved. See the file COPYING in the top-level source
* directory for licensing information.
* ****************************************************************************
*
* A simple demonstration of the api capabilities of cvc5.
*
*/
#include <cvc5/cvc5.h>
#include <iostream>
using namespace std;
using namespace cvc5::api;
int main()
{
// Create a solver
Solver solver;
// We will ask the solver to produce models and unsat cores,
// hence these options should be turned on.
solver.setOption("produce-models", "true");
solver.setOption("produce-unsat-cores", "true");
// The simplest way to set a logic for the solver is to choose "ALL".
// This enables all logics in the solver.
// Alternatively, "QF_ALL" enables all logics without quantifiers.
// To optimize the solver's behavior for a more specific logic,
// use the logic name, e.g. "QF_BV" or "QF_AUFBV".
// Set the logic
solver.setLogic("ALL");
// In this example, we will define constraints over reals and integers.
// Hence, we first obtain the corresponding sorts.
Sort realSort = solver.getRealSort();
Sort intSort = solver.getIntegerSort();
// x and y will be real variables, while a and b will be integer variables.
// Formally, their cpp type is Term,
// and they are called "constants" in SMT jargon:
Term x = solver.mkConst(realSort, "x");
Term y = solver.mkConst(realSort, "y");
Term a = solver.mkConst(intSort, "a");
Term b = solver.mkConst(intSort, "b");
// Our constraints regarding x and y will be:
//
// (1) 0 < x
// (2) 0 < y
// (3) x + y < 1
// (4) x <= y
//
// Formally, constraints are also terms. Their sort is Boolean.
// We will construct these constraints gradually,
// by defining each of their components.
// We start with the constant numerals 0 and 1:
Term zero = solver.mkReal(0);
Term one = solver.mkReal(1);
// Next, we construct the term x + y
Term xPlusY = solver.mkTerm(PLUS, x, y);
// Now we can define the constraints.
// They use the operators +, <=, and <.
// In the API, these are denoted by PLUS, LEQ, and LT.
// A list of available operators is available in:
// src/api/cpp/cvc5_kind.h
Term constraint1 = solver.mkTerm(LT, zero, x);
Term constraint2 = solver.mkTerm(LT, zero, y);
Term constraint3 = solver.mkTerm(LT, xPlusY, one);
Term constraint4 = solver.mkTerm(LEQ, x, y);
// Now we assert the constraints to the solver.
solver.assertFormula(constraint1);
solver.assertFormula(constraint2);
solver.assertFormula(constraint3);
solver.assertFormula(constraint4);
// Check if the formula is satisfiable, that is,
// are there real values for x,y,z that satisfy all the constraints?
Result r1 = solver.checkSat();
// The result is either SAT, UNSAT, or UNKNOWN.
// In this case, it is SAT.
std::cout << "expected: sat" << std::endl;
std::cout << "result:" << r1 << std::endl;
// We can get the values for x and y that satisfy the constraints.
Term xVal = solver.getValue(x);
Term yVal = solver.getValue(y);
// It is also possible to get values for compound terms,
// even if those did not appear in the original formula.
Term xMinusY = solver.mkTerm(MINUS, x, y);
Term xMinusYVal = solver.getValue(xMinusY);
// We can now obtain thestring representations of the values.
std::string xStr = xVal.getRealValue();
std::string yStr = yVal.getRealValue();
std::string xMinusYStr = xMinusYVal.getRealValue();
std::cout << "value for x: " << xStr << std::endl;
std::cout << "value for y: " << yStr << std::endl;
std::cout << "value for x - y: " << xMinusYStr << std::endl;
// Further, we can convert the values to cpp types,
// using standard cpp conversion functions.
double xDouble = std::stod(xStr);
double yDouble = std::stod(yStr);
double xMinusYDouble = std::stod(xMinusYStr);
// Another way to independently compute the value of x and y would be using
// the ordinary cpp minus operator instead of asking the solver.
// However, for more complex terms,
// it is easier to let the solver do the evaluation.
double xMinusYComputed = xDouble - yDouble;
if (xMinusYComputed == xMinusYDouble)
{
std::cout << "computed correctly" << std::endl;
}
else
{
std::cout << "computed incorrectly" << std::endl;
}
// Next, we will check satisfiability of the same formula,
// only this time over integer variables a and b.
// We start by resetting assertions added to the solver.
solver.resetAssertions();
// Next, we assert the same assertions above with integers.
// This time, we inline the construction of terms
// to the assertion command.
solver.assertFormula(solver.mkTerm(LT, solver.mkInteger(0), a));
solver.assertFormula(solver.mkTerm(LT, solver.mkInteger(0), b));
solver.assertFormula(
solver.mkTerm(LT, solver.mkTerm(PLUS, a, b), solver.mkInteger(1)));
solver.assertFormula(solver.mkTerm(LEQ, a, b));
// We check whether the revised assertion is satisfiable.
Result r2 = solver.checkSat();
// This time the formula is unsatisfiable
std::cout << "expected: unsat" << std::endl;
std::cout << "result: " << r2 << std::endl;
// We can query the solver for an unsatisfiable core, i.e., a subset
// of the assertions that is already unsatisfiable.
std::vector<Term> unsatCore = solver.getUnsatCore();
std::cout << "unsat core size: " << unsatCore.size() << std::endl;
std::cout << "unsat core: " << std::endl;
for (const Term& t : unsatCore)
{
std::cout << t << std::endl;
}
return 0;
}
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