#include "src/modelchecker/csl/SparseMarkovAutomatonCslModelChecker.h" #include "src/modelchecker/csl/helper/SparseMarkovAutomatonCslHelper.h" #include "src/utility/macros.h" #include "src/settings/SettingsManager.h" #include "src/settings/modules/GeneralSettings.h" #include "src/modelchecker/results/ExplicitQualitativeCheckResult.h" #include "src/modelchecker/results/ExplicitQuantitativeCheckResult.h" #include "src/exceptions/InvalidPropertyException.h" #include "src/exceptions/NotImplementedException.h" namespace storm { namespace modelchecker { template<typename SparseMarkovAutomatonModelType> SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::SparseMarkovAutomatonCslModelChecker(SparseMarkovAutomatonModelType const& model, std::unique_ptr<storm::utility::solver::MinMaxLinearEquationSolverFactory<ValueType>>&& minMaxLinearEquationSolverFactory) : SparsePropositionalModelChecker<SparseMarkovAutomatonModelType>(model), minMaxLinearEquationSolverFactory(std::move(minMaxLinearEquationSolverFactory)) { // Intentionally left empty. } template<typename SparseMarkovAutomatonModelType> SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::SparseMarkovAutomatonCslModelChecker(SparseMarkovAutomatonModelType const& model) : SparsePropositionalModelChecker<SparseMarkovAutomatonModelType>(model), minMaxLinearEquationSolverFactory(new storm::utility::solver::MinMaxLinearEquationSolverFactory<ValueType>()) { // Intentionally left empty. } template<typename SparseMarkovAutomatonModelType> bool SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::canHandle(storm::logic::Formula const& formula) const { return formula.isCslStateFormula() || formula.isCslPathFormula() || (formula.isRewardPathFormula() && formula.isReachabilityRewardFormula()); } template<typename SparseMarkovAutomatonModelType> std::unique_ptr<CheckResult> SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::computeBoundedUntilProbabilities(storm::logic::BoundedUntilFormula const& pathFormula, bool qualitative, boost::optional<storm::logic::OptimalityType> const& optimalityType) { STORM_LOG_THROW(optimalityType, storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model."); STORM_LOG_THROW(pathFormula.getLeftSubformula().isTrueFormula(), storm::exceptions::NotImplementedException, "Only bounded properties of the form 'true U[t1, t2] phi' are currently supported."); STORM_LOG_THROW(this->getModel().isClosed(), storm::exceptions::InvalidPropertyException, "Unable to compute time-bounded reachability probabilities in non-closed Markov automaton."); std::unique_ptr<CheckResult> rightResultPointer = this->check(pathFormula.getRightSubformula()); ExplicitQualitativeCheckResult const& rightResult = rightResultPointer->asExplicitQualitativeCheckResult(); std::vector<ValueType> result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper<ValueType>::computeBoundedUntilProbabilities(optimalityType.get() == storm::logic::OptimalityType::Minimize, this->getModel().getTransitionMatrix(), this->getModel().getExitRates(), this->getModel().getMarkovianStates(), rightResult.getTruthValuesVector(), pathFormula.getIntervalBounds(), *minMaxLinearEquationSolverFactory); return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(result))); } template<typename SparseMarkovAutomatonModelType> std::unique_ptr<CheckResult> SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::computeUntilProbabilities(storm::logic::UntilFormula const& pathFormula, bool qualitative, boost::optional<storm::logic::OptimalityType> const& optimalityType) { STORM_LOG_THROW(optimalityType, storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model."); std::unique_ptr<CheckResult> leftResultPointer = this->check(pathFormula.getLeftSubformula()); std::unique_ptr<CheckResult> rightResultPointer = this->check(pathFormula.getRightSubformula()); ExplicitQualitativeCheckResult& leftResult = leftResultPointer->asExplicitQualitativeCheckResult(); ExplicitQualitativeCheckResult& rightResult = rightResultPointer->asExplicitQualitativeCheckResult(); std::vector<ValueType> result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper<ValueType>::computeUntilProbabilities(optimalityType.get() == storm::logic::OptimalityType::Minimize, this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), leftResult.getTruthValuesVector(), rightResult.getTruthValuesVector(), qualitative, *minMaxLinearEquationSolverFactory); return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(result))); } template<typename SparseMarkovAutomatonModelType> std::unique_ptr<CheckResult> SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::computeReachabilityRewards(storm::logic::ReachabilityRewardFormula const& rewardPathFormula, boost::optional<std::string> const& rewardModelName, bool qualitative, boost::optional<storm::logic::OptimalityType> const& optimalityType) { STORM_LOG_THROW(optimalityType, storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model."); STORM_LOG_THROW(this->getModel().isClosed(), storm::exceptions::InvalidPropertyException, "Unable to compute reachability rewards in non-closed Markov automaton."); std::unique_ptr<CheckResult> subResultPointer = this->check(rewardPathFormula.getSubformula()); ExplicitQualitativeCheckResult const& subResult = subResultPointer->asExplicitQualitativeCheckResult(); std::vector<ValueType> result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper<ValueType>::computeReachabilityRewards(optimalityType.get() == storm::logic::OptimalityType::Minimize, this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRates(), this->getModel().getMarkovianStates(), rewardModelName ? this->getModel().getRewardModel(rewardModelName.get()) : this->getModel().getRewardModel(""), subResult.getTruthValuesVector(), qualitative, *minMaxLinearEquationSolverFactory); return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(result))); } template<typename SparseMarkovAutomatonModelType> std::unique_ptr<CheckResult> SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::computeLongRunAverage(storm::logic::StateFormula const& stateFormula, bool qualitative, boost::optional<storm::logic::OptimalityType> const& optimalityType) { STORM_LOG_THROW(optimalityType, storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model."); STORM_LOG_THROW(this->getModel().isClosed(), storm::exceptions::InvalidPropertyException, "Unable to compute long-run average in non-closed Markov automaton."); std::unique_ptr<CheckResult> subResultPointer = this->check(stateFormula); ExplicitQualitativeCheckResult const& subResult = subResultPointer->asExplicitQualitativeCheckResult(); std::vector<ValueType> result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper<ValueType>::computeLongRunAverage(optimalityType.get() == storm::logic::OptimalityType::Minimize, this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRates(), this->getModel().getMarkovianStates(), subResult.getTruthValuesVector(), qualitative, *minMaxLinearEquationSolverFactory); return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(result))); } template<typename SparseMarkovAutomatonModelType> std::unique_ptr<CheckResult> SparseMarkovAutomatonCslModelChecker<SparseMarkovAutomatonModelType>::computeExpectedTimes(storm::logic::EventuallyFormula const& eventuallyFormula, bool qualitative, boost::optional<storm::logic::OptimalityType> const& optimalityType) { STORM_LOG_THROW(optimalityType, storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model."); STORM_LOG_THROW(this->getModel().isClosed(), storm::exceptions::InvalidPropertyException, "Unable to compute expected times in non-closed Markov automaton."); std::unique_ptr<CheckResult> subResultPointer = this->check(eventuallyFormula.getSubformula()); ExplicitQualitativeCheckResult& subResult = subResultPointer->asExplicitQualitativeCheckResult(); std::vector<ValueType> result = storm::modelchecker::helper::SparseMarkovAutomatonCslHelper<ValueType>::computeExpectedTimes(optimalityType.get() == storm::logic::OptimalityType::Minimize, this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), this->getModel().getExitRates(), this->getModel().getMarkovianStates(), subResult.getTruthValuesVector(), qualitative, *minMaxLinearEquationSolverFactory); return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(std::move(result))); } template class SparseMarkovAutomatonCslModelChecker<storm::models::sparse::MarkovAutomaton<double>>; } }