#include "gtest/gtest.h" #include "storm-config.h" #include "src/logic/Formulas.h" #include "src/utility/solver.h" #include "src/storage/SymbolicModelDescription.h" #include "src/modelchecker/prctl/SymbolicMdpPrctlModelChecker.h" #include "src/modelchecker/results/SymbolicQualitativeCheckResult.h" #include "src/modelchecker/results/SymbolicQuantitativeCheckResult.h" #include "src/parser/FormulaParser.h" #include "src/parser/PrismParser.h" #include "src/builder/DdPrismModelBuilder.h" #include "src/models/symbolic/Dtmc.h" #include "src/models/symbolic/StandardRewardModel.h" #include "src/settings/SettingsManager.h" #include "src/settings/modules/NativeEquationSolverSettings.h" #include "src/settings/modules/GeneralSettings.h" TEST(SymbolicMdpPrctlModelCheckerTest, Dice_Cudd) { storm::storage::SymbolicModelDescription modelDescription = storm::parser::PrismParser::parse(STORM_CPP_TESTS_BASE_PATH "/functional/builder/two_dice.nm"); storm::prism::Program program = modelDescription.preprocess().asPrismProgram(); // A parser that we use for conveniently constructing the formulas. storm::parser::FormulaParser formulaParser; // Build the die model with its reward model. #ifdef WINDOWS storm::builder::DdPrismModelBuilder::Options options; #else typename storm::builder::DdPrismModelBuilder::Options options; #endif options.buildAllRewardModels = false; options.rewardModelsToBuild.insert("coinflips"); std::shared_ptr> model = storm::builder::DdPrismModelBuilder().build(program, options); EXPECT_EQ(169ul, model->getNumberOfStates()); EXPECT_EQ(436ul, model->getNumberOfTransitions()); ASSERT_EQ(model->getType(), storm::models::ModelType::Mdp); std::shared_ptr> mdp = model->as>(); storm::modelchecker::SymbolicMdpPrctlModelChecker> checker(*mdp, std::unique_ptr>(new storm::utility::solver::SymbolicMinMaxLinearEquationSolverFactory())); std::shared_ptr formula = formulaParser.parseSingleFormulaFromString("Pmin=? [F \"two\"]"); std::unique_ptr result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult1 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.0277777612209320068, quantitativeResult1.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.0277777612209320068, quantitativeResult1.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmax=? [F \"two\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult2 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.0277777612209320068, quantitativeResult2.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.0277777612209320068, quantitativeResult2.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmin=? [F \"three\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult3 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.0555555224418640136, quantitativeResult3.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.0555555224418640136, quantitativeResult3.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmax=? [F \"three\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult4 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.0555555224418640136, quantitativeResult4.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.0555555224418640136, quantitativeResult4.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmin=? [F \"four\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult5 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.083333283662796020508, quantitativeResult5.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.083333283662796020508, quantitativeResult5.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmax=? [F \"four\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult6 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.083333283662796020508, quantitativeResult6.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.083333283662796020508, quantitativeResult6.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Rmin=? [F \"done\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult7 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(7.3333272933959961, quantitativeResult7.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(7.3333272933959961, quantitativeResult7.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Rmax=? [F \"done\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult8 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(7.3333272933959961, quantitativeResult8.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(7.3333272933959961, quantitativeResult8.getMax(), storm::settings::getModule().getPrecision()); } TEST(SymbolicMdpPrctlModelCheckerTest, Dice_Sylvan) { storm::storage::SymbolicModelDescription modelDescription = storm::parser::PrismParser::parse(STORM_CPP_TESTS_BASE_PATH "/functional/builder/two_dice.nm"); storm::prism::Program program = modelDescription.preprocess().asPrismProgram(); // A parser that we use for conveniently constructing the formulas. storm::parser::FormulaParser formulaParser; // Build the die model with its reward model. #ifdef WINDOWS storm::builder::DdPrismModelBuilder::Options options; #else typename storm::builder::DdPrismModelBuilder::Options options; #endif options.buildAllRewardModels = false; options.rewardModelsToBuild.insert("coinflips"); std::shared_ptr> model = storm::builder::DdPrismModelBuilder().build(program, options); EXPECT_EQ(169ul, model->getNumberOfStates()); EXPECT_EQ(436ul, model->getNumberOfTransitions()); ASSERT_EQ(model->getType(), storm::models::ModelType::Mdp); std::shared_ptr> mdp = model->as>(); storm::modelchecker::SymbolicMdpPrctlModelChecker> checker(*mdp, std::unique_ptr>(new storm::utility::solver::SymbolicMinMaxLinearEquationSolverFactory())); std::shared_ptr formula = formulaParser.parseSingleFormulaFromString("Pmin=? [F \"two\"]"); std::unique_ptr result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult1 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.0277777612209320068, quantitativeResult1.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.0277777612209320068, quantitativeResult1.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmax=? [F \"two\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult2 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.0277777612209320068, quantitativeResult2.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.0277777612209320068, quantitativeResult2.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmin=? [F \"three\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult3 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.0555555224418640136, quantitativeResult3.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.0555555224418640136, quantitativeResult3.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmax=? [F \"three\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult4 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.0555555224418640136, quantitativeResult4.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.0555555224418640136, quantitativeResult4.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmin=? [F \"four\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult5 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.083333283662796020508, quantitativeResult5.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.083333283662796020508, quantitativeResult5.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmax=? [F \"four\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult6 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.083333283662796020508, quantitativeResult6.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.083333283662796020508, quantitativeResult6.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Rmin=? [F \"done\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult7 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(7.3333272933959961, quantitativeResult7.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(7.3333272933959961, quantitativeResult7.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Rmax=? [F \"done\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult8 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(7.3333272933959961, quantitativeResult8.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(7.3333272933959961, quantitativeResult8.getMax(), storm::settings::getModule().getPrecision()); } TEST(SymbolicMdpPrctlModelCheckerTest, AsynchronousLeader_Cudd) { storm::storage::SymbolicModelDescription modelDescription = storm::parser::PrismParser::parse(STORM_CPP_TESTS_BASE_PATH "/functional/builder/leader4.nm"); storm::prism::Program program = modelDescription.preprocess().asPrismProgram(); // A parser that we use for conveniently constructing the formulas. storm::parser::FormulaParser formulaParser; // Build the die model with its reward model. #ifdef WINDOWS storm::builder::DdPrismModelBuilder::Options options; #else typename storm::builder::DdPrismModelBuilder::Options options; #endif options.buildAllRewardModels = false; options.rewardModelsToBuild.insert("rounds"); std::shared_ptr> model = storm::builder::DdPrismModelBuilder().build(program, options); EXPECT_EQ(3172ul, model->getNumberOfStates()); EXPECT_EQ(7144ul, model->getNumberOfTransitions()); ASSERT_EQ(model->getType(), storm::models::ModelType::Mdp); std::shared_ptr> mdp = model->as>(); storm::modelchecker::SymbolicMdpPrctlModelChecker> checker(*mdp, std::unique_ptr>(new storm::utility::solver::SymbolicMinMaxLinearEquationSolverFactory())); std::shared_ptr formula = formulaParser.parseSingleFormulaFromString("Pmin=? [F \"elected\"]"); std::unique_ptr result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult1 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(1, quantitativeResult1.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(1, quantitativeResult1.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmax=? [F \"elected\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult2 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(1, quantitativeResult2.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(1, quantitativeResult2.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmin=? [F<=25 \"elected\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult3 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.0625, quantitativeResult3.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.0625, quantitativeResult3.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmax=? [F<=25 \"elected\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult4 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.0625, quantitativeResult4.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.0625, quantitativeResult4.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Rmin=? [F \"elected\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult5 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(4.2856890848060498, quantitativeResult5.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(4.2856890848060498, quantitativeResult5.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Rmax=? [F \"elected\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult6 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(4.2856890848060498, quantitativeResult6.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(4.2856890848060498, quantitativeResult6.getMax(), storm::settings::getModule().getPrecision()); } TEST(SymbolicMdpPrctlModelCheckerTest, AsynchronousLeader_Sylvan) { storm::storage::SymbolicModelDescription modelDescription = storm::parser::PrismParser::parse(STORM_CPP_TESTS_BASE_PATH "/functional/builder/leader4.nm"); storm::prism::Program program = modelDescription.preprocess().asPrismProgram(); // A parser that we use for conveniently constructing the formulas. storm::parser::FormulaParser formulaParser; // Build the die model with its reward model. #ifdef WINDOWS storm::builder::DdPrismModelBuilder::Options options; #else typename storm::builder::DdPrismModelBuilder::Options options; #endif options.buildAllRewardModels = false; options.rewardModelsToBuild.insert("rounds"); std::shared_ptr> model = storm::builder::DdPrismModelBuilder().build(program, options); EXPECT_EQ(3172ul, model->getNumberOfStates()); EXPECT_EQ(7144ul, model->getNumberOfTransitions()); ASSERT_EQ(model->getType(), storm::models::ModelType::Mdp); std::shared_ptr> mdp = model->as>(); storm::modelchecker::SymbolicMdpPrctlModelChecker> checker(*mdp, std::unique_ptr>(new storm::utility::solver::SymbolicMinMaxLinearEquationSolverFactory())); std::shared_ptr formula = formulaParser.parseSingleFormulaFromString("Pmin=? [F \"elected\"]"); std::unique_ptr result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult1 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(1, quantitativeResult1.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(1, quantitativeResult1.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmax=? [F \"elected\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult2 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(1, quantitativeResult2.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(1, quantitativeResult2.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmin=? [F<=25 \"elected\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult3 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.0625, quantitativeResult3.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.0625, quantitativeResult3.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Pmax=? [F<=25 \"elected\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult4 = result->asSymbolicQuantitativeCheckResult(); EXPECT_NEAR(0.0625, quantitativeResult4.getMin(), storm::settings::getModule().getPrecision()); EXPECT_NEAR(0.0625, quantitativeResult4.getMax(), storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Rmin=? [F \"elected\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult5 = result->asSymbolicQuantitativeCheckResult(); // FIXME: this precision bound is not really good. EXPECT_NEAR(4.2857, quantitativeResult5.getMin(), 100 * storm::settings::getModule().getPrecision()); EXPECT_NEAR(4.2857, quantitativeResult5.getMax(), 100 * storm::settings::getModule().getPrecision()); formula = formulaParser.parseSingleFormulaFromString("Rmax=? [F \"elected\"]"); result = checker.check(*formula); result->filter(storm::modelchecker::SymbolicQualitativeCheckResult(model->getReachableStates(), model->getInitialStates())); storm::modelchecker::SymbolicQuantitativeCheckResult& quantitativeResult6 = result->asSymbolicQuantitativeCheckResult(); // FIXME: this precision bound is not really good. EXPECT_NEAR(4.2857, quantitativeResult6.getMin(), 100 * storm::settings::getModule().getPrecision()); EXPECT_NEAR(4.2857, quantitativeResult6.getMax(), 100 * storm::settings::getModule().getPrecision()); }