/****************************************************************************** * 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 #include #include 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 and y 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 the string 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 std::pair xPair = xVal.getReal64Value(); std::pair yPair = yVal.getReal64Value(); std::pair xMinusYPair = xMinusYVal.getReal64Value(); std::cout << "value for x: " << xPair.first << "/" << xPair.second << std::endl; std::cout << "value for y: " << yPair.first << "/" << yPair.second << std::endl; std::cout << "value for x - y: " << xMinusYPair.first << "/" << xMinusYPair.second << std::endl; // Another way to independently compute the value of x - y would be // to perform the (rational) arithmetic manually. // However, for more complex terms, // it is easier to let the solver do the evaluation. std::pair xMinusYComputed = { xPair.first * yPair.second - xPair.second * yPair.first, xPair.second * yPair.second }; uint64_t g = std::gcd(xMinusYComputed.first, xMinusYComputed.second); xMinusYComputed = { xMinusYComputed.first / g, xMinusYComputed.second / g }; if (xMinusYComputed == xMinusYPair) { 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 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; }