#include "src/modelchecker/reachability/SparseDtmcEliminationModelChecker.h"

#include <algorithm>
#include <chrono>

#include "src/adapters/CarlAdapter.h"

#include "src/settings/modules/SparseDtmcEliminationModelCheckerSettings.h"
#include "src/settings/modules/GeneralSettings.h"
#include "src/settings/SettingsManager.h"

#include "src/storage/StronglyConnectedComponentDecomposition.h"

#include "src/models/sparse/StandardRewardModel.h"
#include "src/modelchecker/results/ExplicitQualitativeCheckResult.h"
#include "src/modelchecker/results/ExplicitQuantitativeCheckResult.h"

#include "src/utility/graph.h"
#include "src/utility/vector.h"
#include "src/utility/macros.h"

#include "src/exceptions/InvalidPropertyException.h"
#include "src/exceptions/InvalidStateException.h"

#include "src/exceptions/IllegalArgumentException.h"

namespace storm {
    namespace modelchecker {
        
        template<typename SparseDtmcModelType>
        SparseDtmcEliminationModelChecker<SparseDtmcModelType>::SparseDtmcEliminationModelChecker(storm::models::sparse::Dtmc<ValueType> const& model) : SparsePropositionalModelChecker<SparseDtmcModelType>(model) {
            // Intentionally left empty.
        }
        
        template<typename SparseDtmcModelType>
        bool SparseDtmcEliminationModelChecker<SparseDtmcModelType>::canHandle(storm::logic::Formula const& formula) const {
            if (formula.isProbabilityOperatorFormula()) {
                storm::logic::ProbabilityOperatorFormula const& probabilityOperatorFormula = formula.asProbabilityOperatorFormula();
                return this->canHandle(probabilityOperatorFormula.getSubformula());
            } else if (formula.isRewardOperatorFormula()) {
                storm::logic::RewardOperatorFormula const& rewardOperatorFormula = formula.asRewardOperatorFormula();
                return this->canHandle(rewardOperatorFormula.getSubformula());
            } else if (formula.isUntilFormula() || formula.isEventuallyFormula()) {
                if (formula.isUntilFormula()) {
                    storm::logic::UntilFormula const& untilFormula = formula.asUntilFormula();
                    if (untilFormula.getLeftSubformula().isPropositionalFormula() && untilFormula.getRightSubformula().isPropositionalFormula()) {
                        return true;
                    }
                } else if (formula.isEventuallyFormula()) {
                    storm::logic::EventuallyFormula const& eventuallyFormula = formula.asEventuallyFormula();
                    if (eventuallyFormula.getSubformula().isPropositionalFormula()) {
                        return true;
                    }
                }
            } else if (formula.isReachabilityRewardFormula()) {
                storm::logic::ReachabilityRewardFormula reachabilityRewardFormula = formula.asReachabilityRewardFormula();
                if (reachabilityRewardFormula.getSubformula().isPropositionalFormula()) {
                    return true;
                }
            } else if (formula.isConditionalPathFormula()) {
                storm::logic::ConditionalPathFormula conditionalPathFormula = formula.asConditionalPathFormula();
                if (conditionalPathFormula.getLeftSubformula().isEventuallyFormula() && conditionalPathFormula.getRightSubformula().isEventuallyFormula()) {
                    return this->canHandle(conditionalPathFormula.getLeftSubformula()) && this->canHandle(conditionalPathFormula.getRightSubformula());
                }
            } else if (formula.isPropositionalFormula()) {
                return true;
            }
            return false;
        }
        
        template<typename SparseDtmcModelType>
        std::unique_ptr<CheckResult> SparseDtmcEliminationModelChecker<SparseDtmcModelType>::computeUntilProbabilities(storm::logic::UntilFormula const& pathFormula, bool qualitative, boost::optional<OptimizationDirection> const& optimalityType) {
            // Retrieve the appropriate bitvectors by model checking the subformulas.
            std::unique_ptr<CheckResult> leftResultPointer = this->check(pathFormula.getLeftSubformula());
            std::unique_ptr<CheckResult> rightResultPointer = this->check(pathFormula.getRightSubformula());
            storm::storage::BitVector const& phiStates = leftResultPointer->asExplicitQualitativeCheckResult().getTruthValuesVector();
            storm::storage::BitVector const& psiStates = rightResultPointer->asExplicitQualitativeCheckResult().getTruthValuesVector();
            
            // Do some sanity checks to establish some required properties.
            STORM_LOG_THROW(this->getModel().getInitialStates().getNumberOfSetBits() == 1, storm::exceptions::IllegalArgumentException, "Input model is required to have exactly one initial state.");
            storm::storage::sparse::state_type initialState = *this->getModel().getInitialStates().begin();
            
            // Then, compute the subset of states that has a probability of 0 or 1, respectively.
            std::pair<storm::storage::BitVector, storm::storage::BitVector> statesWithProbability01 = storm::utility::graph::performProb01(this->getModel(), phiStates, psiStates);
            storm::storage::BitVector statesWithProbability0 = statesWithProbability01.first;
            storm::storage::BitVector statesWithProbability1 = statesWithProbability01.second;
            storm::storage::BitVector maybeStates = ~(statesWithProbability0 | statesWithProbability1);
            
            // If the initial state is known to have either probability 0 or 1, we can directly return the result.
            if (this->getModel().getInitialStates().isDisjointFrom(maybeStates)) {
                STORM_LOG_DEBUG("The probability of all initial states was found in a preprocessing step.");
                return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(initialState, statesWithProbability0.get(*this->getModel().getInitialStates().begin()) ? storm::utility::zero<ValueType>() : storm::utility::one<ValueType>()));
            }
            
            // Determine the set of states that is reachable from the initial state without jumping over a target state.
            storm::storage::BitVector reachableStates = storm::utility::graph::getReachableStates(this->getModel().getTransitionMatrix(), this->getModel().getInitialStates(), maybeStates, statesWithProbability1);
            
            // Subtract from the maybe states the set of states that is not reachable (on a path from the initial to a target state).
            maybeStates &= reachableStates;
            
            // Create a vector for the probabilities to go to a state with probability 1 in one step.
            std::vector<ValueType> oneStepProbabilities = this->getModel().getTransitionMatrix().getConstrainedRowSumVector(maybeStates, statesWithProbability1);
            
            // Determine the set of initial states of the sub-model.
            storm::storage::BitVector newInitialStates = this->getModel().getInitialStates() % maybeStates;
            
            // We then build the submatrix that only has the transitions of the maybe states.
            storm::storage::SparseMatrix<ValueType> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(false, maybeStates, maybeStates);
            storm::storage::SparseMatrix<ValueType> submatrixTransposed = submatrix.transpose();
            
            // Before starting the model checking process, we assign priorities to states so we can use them to
            // impose ordering constraints later.
            std::vector<std::size_t> statePriorities = getStatePriorities(submatrix, submatrixTransposed, newInitialStates, oneStepProbabilities);
            
            boost::optional<std::vector<ValueType>> missingStateRewards;
            return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(initialState, computeReachabilityValue(submatrix, oneStepProbabilities, submatrixTransposed, newInitialStates, phiStates, psiStates, missingStateRewards, statePriorities)));
        }
        
        template<typename SparseDtmcModelType>
        std::unique_ptr<CheckResult> SparseDtmcEliminationModelChecker<SparseDtmcModelType>::computeReachabilityRewards(storm::logic::ReachabilityRewardFormula const& rewardPathFormula, boost::optional<std::string> const& rewardModelName, bool qualitative, boost::optional<OptimizationDirection> const& optimalityType) {
            // Retrieve the appropriate bitvectors by model checking the subformulas.
            std::unique_ptr<CheckResult> subResultPointer = this->check(rewardPathFormula.getSubformula());
            storm::storage::BitVector phiStates(this->getModel().getNumberOfStates(), true);
            storm::storage::BitVector const& psiStates = subResultPointer->asExplicitQualitativeCheckResult().getTruthValuesVector();
            
            // Do some sanity checks to establish some required properties.
            RewardModelType const& rewardModel = this->getModel().getRewardModel(rewardModelName ? rewardModelName.get() : "");
            STORM_LOG_THROW(!rewardModel.empty(), storm::exceptions::IllegalArgumentException, "Input model does not have a reward model.");
            STORM_LOG_THROW(this->getModel().getInitialStates().getNumberOfSetBits() == 1, storm::exceptions::IllegalArgumentException, "Input model is required to have exactly one initial state.");
            storm::storage::sparse::state_type initialState = *this->getModel().getInitialStates().begin();
            
            // Then, compute the subset of states that has a reachability reward less than infinity.
            storm::storage::BitVector trueStates(this->getModel().getNumberOfStates(), true);
            storm::storage::BitVector infinityStates = storm::utility::graph::performProb1(this->getModel().getBackwardTransitions(), trueStates, psiStates);
            infinityStates.complement();
            storm::storage::BitVector maybeStates = ~psiStates & ~infinityStates;
            
            // If the initial state is known to have 0 reward or an infinite reward value, we can directly return the result.
            if (infinityStates.get(initialState)) {
                STORM_LOG_DEBUG("The reward of all initial states was found in a preprocessing step.");
                // This is a work around, because not all (e.g. storm::RationalFunction) data types can represent an
                // infinity value.
                return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<double>(initialState, storm::utility::infinity<double>()));
            }
            if (psiStates.get(initialState)) {
                STORM_LOG_DEBUG("The reward of all initial states was found in a preprocessing step.");
                return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(initialState, storm::utility::zero<ValueType>()));
            }
            
            // Determine the set of states that is reachable from the initial state without jumping over a target state.
            storm::storage::BitVector reachableStates = storm::utility::graph::getReachableStates(this->getModel().getTransitionMatrix(), this->getModel().getInitialStates(), maybeStates, psiStates);
            
            // Subtract from the maybe states the set of states that is not reachable (on a path from the initial to a target state).
            maybeStates &= reachableStates;
            
            // Create a vector for the probabilities to go to a state with probability 1 in one step.
            std::vector<ValueType> oneStepProbabilities = this->getModel().getTransitionMatrix().getConstrainedRowSumVector(maybeStates, psiStates);
            
            // Determine the set of initial states of the sub-model.
            storm::storage::BitVector newInitialStates = this->getModel().getInitialStates() % maybeStates;
            
            // We then build the submatrix that only has the transitions of the maybe states.
            storm::storage::SparseMatrix<ValueType> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(false, maybeStates, maybeStates);
            storm::storage::SparseMatrix<ValueType> submatrixTransposed = submatrix.transpose();
            
            // Before starting the model checking process, we assign priorities to states so we can use them to
            // impose ordering constraints later.
            std::vector<std::size_t> statePriorities = getStatePriorities(submatrix, submatrixTransposed, newInitialStates, oneStepProbabilities);
            
            // Project the state reward vector to all maybe-states.
            boost::optional<std::vector<ValueType>> optionalStateRewards = rewardModel.getTotalRewardVector(maybeStates.getNumberOfSetBits(), this->getModel().getTransitionMatrix(), maybeStates);
            return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(initialState, computeReachabilityValue(submatrix, oneStepProbabilities, submatrixTransposed, newInitialStates, phiStates, psiStates, optionalStateRewards, statePriorities)));
        }
        
        template<typename SparseDtmcModelType>
        std::unique_ptr<CheckResult> SparseDtmcEliminationModelChecker<SparseDtmcModelType>::computeConditionalProbabilities(storm::logic::ConditionalPathFormula const& pathFormula, bool qualitative, boost::optional<OptimizationDirection> const& optimalityType) {
            std::chrono::high_resolution_clock::time_point totalTimeStart = std::chrono::high_resolution_clock::now();
            
            // Retrieve the appropriate bitvectors by model checking the subformulas.
            STORM_LOG_THROW(pathFormula.getLeftSubformula().isEventuallyFormula(), storm::exceptions::InvalidPropertyException, "Expected 'eventually' formula.");
            STORM_LOG_THROW(pathFormula.getRightSubformula().isEventuallyFormula(), storm::exceptions::InvalidPropertyException, "Expected 'eventually' formula.");
            
            std::unique_ptr<CheckResult> leftResultPointer = this->check(pathFormula.getLeftSubformula().asEventuallyFormula().getSubformula());
            std::unique_ptr<CheckResult> rightResultPointer = this->check(pathFormula.getRightSubformula().asEventuallyFormula().getSubformula());
            storm::storage::BitVector phiStates = leftResultPointer->asExplicitQualitativeCheckResult().getTruthValuesVector();
            storm::storage::BitVector psiStates = rightResultPointer->asExplicitQualitativeCheckResult().getTruthValuesVector();
            storm::storage::BitVector trueStates(this->getModel().getNumberOfStates(), true);
            
            // Do some sanity checks to establish some required properties.
            // STORM_LOG_WARN_COND(storm::settings::sparseDtmcEliminationModelCheckerSettings().getEliminationMethod() == storm::settings::modules::SparseDtmcEliminationModelCheckerSettings::EliminationMethod::State, "The chosen elimination method is not available for computing conditional probabilities. Falling back to regular state elimination.");
            STORM_LOG_THROW(this->getModel().getInitialStates().getNumberOfSetBits() == 1, storm::exceptions::IllegalArgumentException, "Input model is required to have exactly one initial state.");
            storm::storage::sparse::state_type initialState = *this->getModel().getInitialStates().begin();
            
            storm::storage::SparseMatrix<ValueType> backwardTransitions = this->getModel().getBackwardTransitions();
            
            // Compute the 'true' psi states, i.e. those psi states that can be reached without passing through another psi state first.
            psiStates = storm::utility::graph::getReachableStates(this->getModel().getTransitionMatrix(), this->getModel().getInitialStates(), trueStates, psiStates) & psiStates;
            
            std::pair<storm::storage::BitVector, storm::storage::BitVector> statesWithProbability01 = storm::utility::graph::performProb01(backwardTransitions, trueStates, psiStates);
            storm::storage::BitVector statesWithProbabilityGreater0 = ~statesWithProbability01.first;
            storm::storage::BitVector statesWithProbability1 = std::move(statesWithProbability01.second);
            
            STORM_LOG_THROW(this->getModel().getInitialStates().isSubsetOf(statesWithProbabilityGreater0), storm::exceptions::InvalidPropertyException, "The condition of the conditional probability has zero probability.");
            
            // If the initial state is known to have probability 1 of satisfying the condition, we can apply regular model checking.
            if (this->getModel().getInitialStates().isSubsetOf(statesWithProbability1)) {
                STORM_LOG_INFO("The condition holds with probability 1, so the regular reachability probability is computed.");
                std::shared_ptr<storm::logic::BooleanLiteralFormula> trueFormula = std::make_shared<storm::logic::BooleanLiteralFormula>(true);
                std::shared_ptr<storm::logic::UntilFormula> untilFormula = std::make_shared<storm::logic::UntilFormula>(trueFormula, pathFormula.getLeftSubformula().asSharedPointer());
                return this->computeUntilProbabilities(*untilFormula);
            }
            
            // From now on, we know the condition does not have a trivial probability in the initial state.
            
            // Compute the states that can be reached on a path that has a psi state in it.
            storm::storage::BitVector statesWithPsiPredecessor = storm::utility::graph::performProbGreater0(this->getModel().getTransitionMatrix(), trueStates, psiStates);
            storm::storage::BitVector statesReachingPhi = storm::utility::graph::performProbGreater0(backwardTransitions, trueStates, phiStates);
            
            // The set of states we need to consider are those that have a non-zero probability to satisfy the condition or are on some path that has a psi state in it.
            STORM_LOG_TRACE("Initial state: " << this->getModel().getInitialStates());
            STORM_LOG_TRACE("Phi states: " << phiStates);
            STORM_LOG_TRACE("Psi state: " << psiStates);
            STORM_LOG_TRACE("States with probability greater 0 of satisfying the condition: " << statesWithProbabilityGreater0);
            STORM_LOG_TRACE("States with psi predecessor: " << statesWithPsiPredecessor);
            STORM_LOG_TRACE("States reaching phi: " << statesReachingPhi);
            storm::storage::BitVector maybeStates = statesWithProbabilityGreater0 | (statesWithPsiPredecessor & statesReachingPhi);
            STORM_LOG_TRACE("Found " << maybeStates.getNumberOfSetBits() << " relevant states: " << maybeStates);
            
            // Determine the set of initial states of the sub-DTMC.
            storm::storage::BitVector newInitialStates = this->getModel().getInitialStates() % maybeStates;
            STORM_LOG_TRACE("Found new initial states: " << newInitialStates << " (old: " << this->getModel().getInitialStates() << ")");

            // Create a dummy vector for the one-step probabilities.
            std::vector<ValueType> oneStepProbabilities(maybeStates.getNumberOfSetBits(), storm::utility::zero<ValueType>());
            
            // We then build the submatrix that only has the transitions of the maybe states.
            storm::storage::SparseMatrix<ValueType> submatrix = this->getModel().getTransitionMatrix().getSubmatrix(false, maybeStates, maybeStates);
            storm::storage::SparseMatrix<ValueType> submatrixTransposed = submatrix.transpose();
            
            // The states we want to eliminate are those that are tagged with "maybe" but are not a phi or psi state.
            phiStates = phiStates % maybeStates;
            
            // If there are no phi states in the reduced model, the conditional probability is trivially zero.
            if (phiStates.empty()) {
                return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(initialState, storm::utility::zero<ValueType>()));
            }
            
            psiStates = psiStates % maybeStates;
            
            // Keep only the states that we do not eliminate in the maybe states.
            maybeStates = phiStates | psiStates;
            
            STORM_LOG_TRACE("Phi states in reduced model " << phiStates);
            STORM_LOG_TRACE("Psi states in reduced model " << psiStates);
            storm::storage::BitVector statesToEliminate = ~maybeStates & ~newInitialStates;
            STORM_LOG_TRACE("Eliminating the states " << statesToEliminate);
            
            // Before starting the model checking process, we assign priorities to states so we can use them to
            // impose ordering constraints later.
            std::vector<std::size_t> statePriorities = getStatePriorities(submatrix, submatrixTransposed, newInitialStates, oneStepProbabilities);
            
            std::vector<storm::storage::sparse::state_type> states(statesToEliminate.begin(), statesToEliminate.end());
            
            // Sort the states according to the priorities.
            std::sort(states.begin(), states.end(), [&statePriorities] (storm::storage::sparse::state_type const& a, storm::storage::sparse::state_type const& b) { return statePriorities[a] < statePriorities[b]; });
            
            STORM_LOG_INFO("Computing conditional probilities." << std::endl);
            STORM_LOG_INFO("Eliminating " << states.size() << " states using the state elimination technique." << std::endl);
            boost::optional<std::vector<ValueType>> missingStateRewards;
            std::chrono::high_resolution_clock::time_point conversionStart = std::chrono::high_resolution_clock::now();
            storm::storage::FlexibleSparseMatrix<ValueType> flexibleMatrix(submatrix);
            storm::storage::FlexibleSparseMatrix<ValueType> flexibleBackwardTransitions(submatrixTransposed, true);
            std::chrono::high_resolution_clock::time_point conversionEnd = std::chrono::high_resolution_clock::now();
            std::chrono::high_resolution_clock::time_point modelCheckingStart = std::chrono::high_resolution_clock::now();
            for (auto const& state : states) {
                storm::storage::FlexibleSparseMatrix<ValueType>::eliminateState(flexibleMatrix, oneStepProbabilities, state, flexibleBackwardTransitions, missingStateRewards);
            }
            STORM_LOG_INFO("Eliminated " << states.size() << " states." << std::endl);
            
            // Eliminate the transitions going into the initial state (if there are any).
            if (!flexibleBackwardTransitions.getRow(*newInitialStates.begin()).empty()) {
                storm::storage::FlexibleSparseMatrix<ValueType>::eliminateState(flexibleMatrix, oneStepProbabilities, *newInitialStates.begin(), flexibleBackwardTransitions, missingStateRewards, false);
            }
            
            // Now we need to basically eliminate all chains of not-psi states after phi states and chains of not-phi
            // states after psi states.
            for (auto const& trans1 : flexibleMatrix.getRow(*newInitialStates.begin())) {
                auto initialStateSuccessor = trans1.getColumn();
                
                STORM_LOG_TRACE("Exploring successor " << initialStateSuccessor << " of the initial state.");
                
                if (phiStates.get(initialStateSuccessor)) {
                    STORM_LOG_TRACE("Is a phi state.");
                    
                    // If the state is both a phi and a psi state, we do not need to eliminate chains.
                    if (psiStates.get(initialStateSuccessor)) {
                        continue;
                    }
                    
                    // At this point, we know that the state satisfies phi and not psi.
                    // This means, we must compute the probability to reach psi states, which in turn means that we need
                    // to eliminate all chains of non-psi states between the current state and psi states.
                    bool hasNonPsiSuccessor = true;
                    while (hasNonPsiSuccessor) {
                        hasNonPsiSuccessor = false;
                        
                        // Only treat the state if it has an outgoing transition other than a self-loop.
                        auto const currentRow = flexibleMatrix.getRow(initialStateSuccessor);
                        if (currentRow.size() > 1 || (!currentRow.empty() && currentRow.front().getColumn() != initialStateSuccessor)) {
                            for (auto const& element : currentRow) {
                                // If any of the successors is a phi state, we eliminate it (wrt. all its phi predecessors).
                                if (!psiStates.get(element.getColumn())) {
                                    typename storm::storage::FlexibleSparseMatrix<ValueType>::row_type const& successorRow = flexibleMatrix.getRow(element.getColumn());
                                    // Eliminate the successor only if there possibly is a psi state reachable through it.
                                    if (successorRow.size() > 1 || (!successorRow.empty() && successorRow.front().getColumn() != element.getColumn())) {
                                        STORM_LOG_TRACE("Found non-psi successor " << element.getColumn() << " that needs to be eliminated.");
                                        storm::storage::FlexibleSparseMatrix<ValueType>::eliminateState(flexibleMatrix, oneStepProbabilities, element.getColumn(), flexibleBackwardTransitions, missingStateRewards, false, true, phiStates);
                                        hasNonPsiSuccessor = true;
                                    }
                                }
                            }
                            STORM_LOG_ASSERT(!flexibleMatrix.getRow(initialStateSuccessor).empty(), "(1) New transitions expected to be non-empty.");
                        }
                    }
                } else {
                    STORM_LOG_ASSERT(psiStates.get(initialStateSuccessor), "Expected psi state.");
                    STORM_LOG_TRACE("Is a psi state.");

                    // At this point, we know that the state satisfies psi and not phi.
                    // This means, we must compute the probability to reach phi states, which in turn means that we need
                    // to eliminate all chains of non-phi states between the current state and phi states.
                    
                    bool hasNonPhiSuccessor = true;
                    while (hasNonPhiSuccessor) {
                        hasNonPhiSuccessor = false;
                        
                        // Only treat the state if it has an outgoing transition other than a self-loop.
                        auto const currentRow = flexibleMatrix.getRow(initialStateSuccessor);
                        if (currentRow.size() > 1 || (!currentRow.empty() && currentRow.front().getColumn() != initialStateSuccessor)) {
                            for (auto const& element : currentRow) {
                                // If any of the successors is a psi state, we eliminate it (wrt. all its psi predecessors).
                                if (!phiStates.get(element.getColumn())) {
                                    typename storm::storage::FlexibleSparseMatrix<ValueType>::row_type const& successorRow = flexibleMatrix.getRow(element.getColumn());
                                    if (successorRow.size() > 1 || (!successorRow.empty() && successorRow.front().getColumn() != element.getColumn())) {
                                        STORM_LOG_TRACE("Found non-phi successor " << element.getColumn() << " that needs to be eliminated.");
                                        storm::storage::FlexibleSparseMatrix<ValueType>::eliminateState(flexibleMatrix, oneStepProbabilities, element.getColumn(), flexibleBackwardTransitions, missingStateRewards, false, true, psiStates);
                                        hasNonPhiSuccessor = true;
                                    }
                                }
                            }
                        }
                    }
                }
            }
            
            ValueType numerator = storm::utility::zero<ValueType>();
            ValueType denominator = storm::utility::zero<ValueType>();
            
            for (auto const& trans1 : flexibleMatrix.getRow(*newInitialStates.begin())) {
                auto initialStateSuccessor = trans1.getColumn();
                if (phiStates.get(initialStateSuccessor)) {
                    if (psiStates.get(initialStateSuccessor)) {
                        numerator += trans1.getValue();
                        denominator += trans1.getValue();
                    } else {
                        ValueType additiveTerm = storm::utility::zero<ValueType>();
                        for (auto const& trans2 : flexibleMatrix.getRow(initialStateSuccessor)) {
                            if (psiStates.get(trans2.getColumn())) {
                                additiveTerm += trans2.getValue();
                            }
                        }
                        additiveTerm *= trans1.getValue();
                        numerator += additiveTerm;
                        denominator += additiveTerm;
                    }
                } else {
                    STORM_LOG_ASSERT(psiStates.get(initialStateSuccessor), "Expected psi state.");
                    denominator += trans1.getValue();
                    ValueType additiveTerm = storm::utility::zero<ValueType>();
                    for (auto const& trans2 : flexibleMatrix.getRow(initialStateSuccessor)) {
                        if (phiStates.get(trans2.getColumn())) {
                            additiveTerm += trans2.getValue();
                        }
                    }
                    numerator += trans1.getValue() * additiveTerm;
                }
            }
            std::chrono::high_resolution_clock::time_point modelCheckingEnd = std::chrono::high_resolution_clock::now();
            std::chrono::high_resolution_clock::time_point totalTimeEnd = std::chrono::high_resolution_clock::now();
            
            if (storm::settings::generalSettings().isShowStatisticsSet()) {
                std::chrono::high_resolution_clock::duration conversionTime = conversionEnd - conversionStart;
                std::chrono::milliseconds conversionTimeInMilliseconds = std::chrono::duration_cast<std::chrono::milliseconds>(conversionTime);
                std::chrono::high_resolution_clock::duration modelCheckingTime = modelCheckingEnd - modelCheckingStart;
                std::chrono::milliseconds modelCheckingTimeInMilliseconds = std::chrono::duration_cast<std::chrono::milliseconds>(modelCheckingTime);
                std::chrono::high_resolution_clock::duration totalTime = totalTimeEnd - totalTimeStart;
                std::chrono::milliseconds totalTimeInMilliseconds = std::chrono::duration_cast<std::chrono::milliseconds>(totalTime);
                
                STORM_PRINT_AND_LOG(std::endl);
                STORM_PRINT_AND_LOG("Time breakdown:" << std::endl);
                STORM_PRINT_AND_LOG("    * time for conversion: " << conversionTimeInMilliseconds.count() << "ms" << std::endl);
                STORM_PRINT_AND_LOG("    * time for checking: " << modelCheckingTimeInMilliseconds.count() << "ms" << std::endl);
                STORM_PRINT_AND_LOG("------------------------------------------" << std::endl);
                STORM_PRINT_AND_LOG("    * total time: " << totalTimeInMilliseconds.count() << "ms" << std::endl);
                STORM_PRINT_AND_LOG(std::endl);
            }
            
            return std::unique_ptr<CheckResult>(new ExplicitQuantitativeCheckResult<ValueType>(initialState, numerator / denominator));
        }
        
        template<typename SparseDtmcModelType>
        typename SparseDtmcEliminationModelChecker<SparseDtmcModelType>::ValueType SparseDtmcEliminationModelChecker<SparseDtmcModelType>::computeReachabilityValue(storm::storage::SparseMatrix<ValueType> const& transitionMatrix, std::vector<ValueType>& oneStepProbabilities, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, storm::storage::BitVector const& initialStates, storm::storage::BitVector const& phiStates, storm::storage::BitVector const& psiStates, boost::optional<std::vector<ValueType>>& stateRewards, boost::optional<std::vector<std::size_t>> const& statePriorities) {
            std::chrono::high_resolution_clock::time_point totalTimeStart = std::chrono::high_resolution_clock::now();
            
            // Create a bit vector that represents the subsystem of states we still have to eliminate.
            storm::storage::BitVector subsystem = storm::storage::BitVector(transitionMatrix.getRowCount(), true);
            
            std::chrono::high_resolution_clock::time_point conversionStart = std::chrono::high_resolution_clock::now();
            // Then, we convert the reduced matrix to a more flexible format to be able to perform state elimination more easily.
            storm::storage::FlexibleSparseMatrix<ValueType> flexibleMatrix(transitionMatrix);
            storm::storage::FlexibleSparseMatrix<ValueType> flexibleBackwardTransitions(backwardTransitions, true);
            auto conversionEnd = std::chrono::high_resolution_clock::now();
            
            std::chrono::high_resolution_clock::time_point modelCheckingStart = std::chrono::high_resolution_clock::now();
            uint_fast64_t maximalDepth = 0;
            if (storm::settings::sparseDtmcEliminationModelCheckerSettings().getEliminationMethod() == storm::settings::modules::SparseDtmcEliminationModelCheckerSettings::EliminationMethod::State) {
                // If we are required to do pure state elimination, we simply create a vector of all states to
                // eliminate and sort it according to the given priorities.
                
                // Remove the initial state from the states which we need to eliminate.
                subsystem &= ~initialStates;
                std::vector<storm::storage::sparse::state_type> states(subsystem.begin(), subsystem.end());
                
                if (statePriorities) {
                    std::sort(states.begin(), states.end(), [&statePriorities] (storm::storage::sparse::state_type const& a, storm::storage::sparse::state_type const& b) { return statePriorities.get()[a] < statePriorities.get()[b]; });
                }
                
                STORM_LOG_DEBUG("Eliminating " << states.size() << " states using the state elimination technique." << std::endl);
                for (auto const& state : states) {
                    storm::storage::FlexibleSparseMatrix<ValueType>::eliminateState(flexibleMatrix, oneStepProbabilities, state, flexibleBackwardTransitions, stateRewards);
                }
                STORM_LOG_DEBUG("Eliminated " << states.size() << " states." << std::endl);
            } else if (storm::settings::sparseDtmcEliminationModelCheckerSettings().getEliminationMethod() == storm::settings::modules::SparseDtmcEliminationModelCheckerSettings::EliminationMethod::Hybrid) {
                // When using the hybrid technique, we recursively treat the SCCs up to some size.
                std::vector<storm::storage::sparse::state_type> entryStateQueue;
                STORM_LOG_DEBUG("Eliminating " << subsystem.size() << " states using the hybrid elimination technique." << std::endl);
                maximalDepth = treatScc(flexibleMatrix, oneStepProbabilities, initialStates, subsystem, transitionMatrix, flexibleBackwardTransitions, false, 0, storm::settings::sparseDtmcEliminationModelCheckerSettings().getMaximalSccSize(), entryStateQueue, stateRewards, statePriorities);
                
                // If the entry states were to be eliminated last, we need to do so now.
                STORM_LOG_DEBUG("Eliminating " << entryStateQueue.size() << " entry states as a last step.");
                if (storm::settings::sparseDtmcEliminationModelCheckerSettings().isEliminateEntryStatesLastSet()) {
                    for (auto const& state : entryStateQueue) {
                        storm::storage::FlexibleSparseMatrix<ValueType>::eliminateState(flexibleMatrix, oneStepProbabilities, state, flexibleBackwardTransitions, stateRewards);
                    }
                }
                STORM_LOG_DEBUG("Eliminated " << subsystem.size() << " states." << std::endl);
            }
            
            // Finally eliminate initial state.
            if (!stateRewards) {
                // If we are computing probabilities, then we can simply call the state elimination procedure. It
                // will scale the transition row of the initial state with 1/(1-loopProbability).
                STORM_LOG_INFO("Eliminating initial state " << *initialStates.begin() << "." << std::endl);
                storm::storage::FlexibleSparseMatrix<ValueType>::eliminateState(flexibleMatrix, oneStepProbabilities, *initialStates.begin(), flexibleBackwardTransitions, stateRewards);
            } else {
                // If we are computing rewards, we cannot call the state elimination procedure for technical reasons.
                // Instead, we need to get rid of a potential loop in this state explicitly.
                
                // Start by finding the self-loop element. Since it can only be the only remaining outgoing transition
                // of the initial state, this amounts to checking whether the outgoing transitions of the initial
                // state are non-empty.
                if (!flexibleMatrix.getRow(*initialStates.begin()).empty()) {
                    STORM_LOG_ASSERT(flexibleMatrix.getRow(*initialStates.begin()).size() == 1, "At most one outgoing transition expected at this point, but found more.");
                    STORM_LOG_ASSERT(flexibleMatrix.getRow(*initialStates.begin()).front().getColumn() == *initialStates.begin(), "Remaining entry should be a self-loop, but it is not.");
                    ValueType loopProbability = flexibleMatrix.getRow(*initialStates.begin()).front().getValue();
                    loopProbability = storm::utility::one<ValueType>() / (storm::utility::one<ValueType>() - loopProbability);
                    STORM_LOG_DEBUG("Scaling the reward of the initial state " << stateRewards.get()[(*initialStates.begin())] << " with " << loopProbability);
                    stateRewards.get()[(*initialStates.begin())] *= loopProbability;
                    flexibleMatrix.getRow(*initialStates.begin()).clear();
                }
            }
            
            // Make sure that we have eliminated all transitions from the initial state.
            STORM_LOG_ASSERT(flexibleMatrix.getRow(*initialStates.begin()).empty(), "The transitions of the initial states are non-empty.");
            
            std::chrono::high_resolution_clock::time_point modelCheckingEnd = std::chrono::high_resolution_clock::now();
            std::chrono::high_resolution_clock::time_point totalTimeEnd = std::chrono::high_resolution_clock::now();
            
            if (storm::settings::generalSettings().isShowStatisticsSet()) {
                std::chrono::high_resolution_clock::duration conversionTime = conversionEnd - conversionStart;
                std::chrono::milliseconds conversionTimeInMilliseconds = std::chrono::duration_cast<std::chrono::milliseconds>(conversionTime);
                std::chrono::high_resolution_clock::duration modelCheckingTime = modelCheckingEnd - modelCheckingStart;
                std::chrono::milliseconds modelCheckingTimeInMilliseconds = std::chrono::duration_cast<std::chrono::milliseconds>(modelCheckingTime);
                std::chrono::high_resolution_clock::duration totalTime = totalTimeEnd - totalTimeStart;
                std::chrono::milliseconds totalTimeInMilliseconds = std::chrono::duration_cast<std::chrono::milliseconds>(totalTime);
                
                STORM_PRINT_AND_LOG(std::endl);
                STORM_PRINT_AND_LOG("Time breakdown:" << std::endl);
                STORM_PRINT_AND_LOG("    * time for conversion: " << conversionTimeInMilliseconds.count() << "ms" << std::endl);
                STORM_PRINT_AND_LOG("    * time for checking: " << modelCheckingTimeInMilliseconds.count() << "ms" << std::endl);
                STORM_PRINT_AND_LOG("------------------------------------------" << std::endl);
                STORM_PRINT_AND_LOG("    * total time: " << totalTimeInMilliseconds.count() << "ms" << std::endl);
                STORM_PRINT_AND_LOG(std::endl);
                STORM_PRINT_AND_LOG("Other:" << std::endl);
                STORM_PRINT_AND_LOG("    * number of states eliminated: " << transitionMatrix.getRowCount() << std::endl);
                if (storm::settings::sparseDtmcEliminationModelCheckerSettings().getEliminationMethod() == storm::settings::modules::SparseDtmcEliminationModelCheckerSettings::EliminationMethod::Hybrid) {
                    STORM_PRINT_AND_LOG("    * maximal depth of SCC decomposition: " << maximalDepth << std::endl);
                }
            }

            // Now, we return the value for the only initial state.
            STORM_LOG_DEBUG("Simplifying and returning result.");
            if (stateRewards) {
                return storm::utility::simplify(stateRewards.get()[*initialStates.begin()]);
            } else {
                return oneStepProbabilities[*initialStates.begin()];
            }
        }
        
        template<typename SparseDtmcModelType>
        std::vector<std::size_t> SparseDtmcEliminationModelChecker<SparseDtmcModelType>::getStatePriorities(storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& transitionMatrixTransposed, storm::storage::BitVector const& initialStates, std::vector<ValueType> const& oneStepProbabilities) {
            std::vector<std::size_t> statePriorities(transitionMatrix.getRowCount());
            std::vector<std::size_t> states(transitionMatrix.getRowCount());
            for (std::size_t index = 0; index < states.size(); ++index) {
                states[index] = index;
            }
            if (storm::settings::sparseDtmcEliminationModelCheckerSettings().getEliminationOrder() == storm::settings::modules::SparseDtmcEliminationModelCheckerSettings::EliminationOrder::Random) {
                std::random_shuffle(states.begin(), states.end());
            } else {
                std::vector<std::size_t> distances;
                if (storm::settings::sparseDtmcEliminationModelCheckerSettings().getEliminationOrder() == storm::settings::modules::SparseDtmcEliminationModelCheckerSettings::EliminationOrder::Forward || storm::settings::sparseDtmcEliminationModelCheckerSettings().getEliminationOrder() == storm::settings::modules::SparseDtmcEliminationModelCheckerSettings::EliminationOrder::ForwardReversed) {
                    distances = storm::utility::graph::getDistances(transitionMatrix, initialStates);
                } else if (storm::settings::sparseDtmcEliminationModelCheckerSettings().getEliminationOrder() == storm::settings::modules::SparseDtmcEliminationModelCheckerSettings::EliminationOrder::Backward || storm::settings::sparseDtmcEliminationModelCheckerSettings().getEliminationOrder() == storm::settings::modules::SparseDtmcEliminationModelCheckerSettings::EliminationOrder::BackwardReversed) {
                    // Since the target states were eliminated from the matrix already, we construct a replacement by
                    // treating all states that have some non-zero probability to go to a target state in one step.
                    storm::storage::BitVector pseudoTargetStates(transitionMatrix.getRowCount());
                    for (std::size_t index = 0; index < oneStepProbabilities.size(); ++index) {
                        if (oneStepProbabilities[index] != storm::utility::zero<ValueType>()) {
                            pseudoTargetStates.set(index);
                        }
                    }
                    
                    distances = storm::utility::graph::getDistances(transitionMatrixTransposed, pseudoTargetStates);
                } else {
                    STORM_LOG_ASSERT(false, "Illegal sorting order selected.");
                }
                
                // In case of the forward or backward ordering, we can sort the states according to the distances.
                if (storm::settings::sparseDtmcEliminationModelCheckerSettings().getEliminationOrder() == storm::settings::modules::SparseDtmcEliminationModelCheckerSettings::EliminationOrder::Forward || storm::settings::sparseDtmcEliminationModelCheckerSettings().getEliminationOrder() == storm::settings::modules::SparseDtmcEliminationModelCheckerSettings::EliminationOrder::Backward) {
                    std::sort(states.begin(), states.end(), [&distances] (storm::storage::sparse::state_type const& state1, storm::storage::sparse::state_type const& state2) { return distances[state1] < distances[state2]; } );
                } else {
                    // Otherwise, we sort them according to descending distances.
                    std::sort(states.begin(), states.end(), [&distances] (storm::storage::sparse::state_type const& state1, storm::storage::sparse::state_type const& state2) { return distances[state1] > distances[state2]; } );
                }
            }
            
            // Now convert the ordering of the states to priorities.
            for (std::size_t index = 0; index < states.size(); ++index) {
                statePriorities[states[index]] = index;
            }
            
            return statePriorities;
        }
        
        template<typename SparseDtmcModelType>
        uint_fast64_t SparseDtmcEliminationModelChecker<SparseDtmcModelType>::treatScc(storm::storage::FlexibleSparseMatrix<ValueType>& matrix, std::vector<ValueType>& oneStepProbabilities, storm::storage::BitVector const& entryStates, storm::storage::BitVector const& scc, storm::storage::SparseMatrix<ValueType> const& forwardTransitions, storm::storage::FlexibleSparseMatrix<ValueType>& backwardTransitions, bool eliminateEntryStates, uint_fast64_t level, uint_fast64_t maximalSccSize, std::vector<storm::storage::sparse::state_type>& entryStateQueue, boost::optional<std::vector<ValueType>>& stateRewards, boost::optional<std::vector<std::size_t>> const& statePriorities) {
            uint_fast64_t maximalDepth = level;
            
            // If the SCCs are large enough, we try to split them further.
            if (scc.getNumberOfSetBits() > maximalSccSize) {
                STORM_LOG_TRACE("SCC is large enough (" << scc.getNumberOfSetBits() << " states) to be decomposed further.");
                
                // Here, we further decompose the SCC into sub-SCCs.
                storm::storage::StronglyConnectedComponentDecomposition<ValueType> decomposition(forwardTransitions, scc & ~entryStates, false, false);
                STORM_LOG_TRACE("Decomposed SCC into " << decomposition.size() << " sub-SCCs.");
                
                // Store a bit vector of remaining SCCs so we can be flexible when it comes to the order in which
                // we eliminate the SCCs.
                storm::storage::BitVector remainingSccs(decomposition.size(), true);
                
                // First, get rid of the trivial SCCs.
                std::vector<std::pair<storm::storage::sparse::state_type, uint_fast64_t>> trivialSccs;
                for (uint_fast64_t sccIndex = 0; sccIndex < decomposition.size(); ++sccIndex) {
                    storm::storage::StronglyConnectedComponent const& scc = decomposition.getBlock(sccIndex);
                    if (scc.isTrivial()) {
                        storm::storage::sparse::state_type onlyState = *scc.begin();
                        trivialSccs.emplace_back(onlyState, sccIndex);
                    }
                }
                
                // If we are given priorities, sort the trivial SCCs accordingly.
                if (statePriorities) {
                    std::sort(trivialSccs.begin(), trivialSccs.end(), [&statePriorities] (std::pair<storm::storage::sparse::state_type, uint_fast64_t> const& a, std::pair<storm::storage::sparse::state_type, uint_fast64_t> const& b) { return statePriorities.get()[a.first] < statePriorities.get()[b.first]; });
                }
                
                STORM_LOG_TRACE("Eliminating " << trivialSccs.size() << " trivial SCCs.");
                for (auto const& stateIndexPair : trivialSccs) {
                    storm::storage::FlexibleSparseMatrix<ValueType>::eliminateState(matrix, oneStepProbabilities, stateIndexPair.first, backwardTransitions, stateRewards);
                    remainingSccs.set(stateIndexPair.second, false);
                }
                STORM_LOG_TRACE("Eliminated all trivial SCCs.");
                
                // And then recursively treat the remaining sub-SCCs.
                STORM_LOG_TRACE("Eliminating " << remainingSccs.getNumberOfSetBits() << " remaining SCCs on level " << level << ".");
                for (auto sccIndex : remainingSccs) {
                    storm::storage::StronglyConnectedComponent const& newScc = decomposition.getBlock(sccIndex);
                    
                    // Rewrite SCC into bit vector and subtract it from the remaining states.
                    storm::storage::BitVector newSccAsBitVector(forwardTransitions.getRowCount(), newScc.begin(), newScc.end());
                    
                    // Determine the set of entry states of the SCC.
                    storm::storage::BitVector entryStates(forwardTransitions.getRowCount());
                    for (auto const& state : newScc) {
                        for (auto const& predecessor : backwardTransitions.getRow(state)) {
                            if (predecessor.getValue() != storm::utility::zero<ValueType>() && !newSccAsBitVector.get(predecessor.getColumn())) {
                                entryStates.set(state);
                            }
                        }
                    }
                    
                    // Recursively descend in SCC-hierarchy.
                    uint_fast64_t depth = treatScc(matrix, oneStepProbabilities, entryStates, newSccAsBitVector, forwardTransitions, backwardTransitions, !storm::settings::sparseDtmcEliminationModelCheckerSettings().isEliminateEntryStatesLastSet(), level + 1, maximalSccSize, entryStateQueue, stateRewards, statePriorities);
                    maximalDepth = std::max(maximalDepth, depth);
                }
                
            } else {
                // In this case, we perform simple state elimination in the current SCC.
                STORM_LOG_TRACE("SCC of size " << scc.getNumberOfSetBits() << " is small enough to be eliminated directly.");
                storm::storage::BitVector remainingStates = scc & ~entryStates;
                
                std::vector<uint_fast64_t> states(remainingStates.begin(), remainingStates.end());
                
                // If we are given priorities, sort the trivial SCCs accordingly.
                if (statePriorities) {
                    std::sort(states.begin(), states.end(), [&statePriorities] (storm::storage::sparse::state_type const& a, storm::storage::sparse::state_type const& b) { return statePriorities.get()[a] < statePriorities.get()[b]; });
                }
                
                // Eliminate the remaining states that do not have a self-loop (in the current, i.e. modified)
                // transition probability matrix.
                for (auto const& state : states) {
                    storm::storage::FlexibleSparseMatrix<ValueType>::eliminateState(matrix, oneStepProbabilities, state, backwardTransitions, stateRewards);
                }
                
                STORM_LOG_TRACE("Eliminated all states of SCC.");
            }
            
            // Finally, eliminate the entry states (if we are required to do so).
            if (eliminateEntryStates) {
                STORM_LOG_TRACE("Finally, eliminating/adding entry states.");
                for (auto state : entryStates) {
                    storm::storage::FlexibleSparseMatrix<ValueType>::eliminateState(matrix, oneStepProbabilities, state, backwardTransitions, stateRewards);
                }
                STORM_LOG_TRACE("Eliminated/added entry states.");
            } else {
                for (auto state : entryStates) {
                    entryStateQueue.push_back(state);
                }
            }
            
            return maximalDepth;
        }
        
        template class SparseDtmcEliminationModelChecker<storm::models::sparse::Dtmc<double>>;
        
#ifdef STORM_HAVE_CARL
        template class SparseDtmcEliminationModelChecker<storm::models::sparse::Dtmc<storm::RationalFunction>>;
#endif
    } // namespace modelchecker
} // namespace storm