637 lines
44 KiB

#include "SparseLTLHelper.h"
#include "storm/automata/LTL2DeterministicAutomaton.h"
#include "storm/modelchecker/prctl/helper/SparseDtmcPrctlHelper.h"
#include "storm/modelchecker/prctl/helper/SparseMdpPrctlHelper.h"
#include "storm/storage/StronglyConnectedComponentDecomposition.h"
#include "storm/storage/MaximalEndComponentDecomposition.h"
#include "storm/storage/memorystructure/MemoryStructure.h"
#include "storm/storage/memorystructure/MemoryStructureBuilder.h"
#include "storm/settings/SettingsManager.h"
#include "storm/settings/modules/DebugSettings.h"
#include "storm/exceptions/InvalidPropertyException.h"
#include "storm/environment/modelchecker/ModelCheckerEnvironment.h"
#include "storm/utility/graph.h"
namespace storm {
namespace modelchecker {
namespace helper {
template <typename ValueType, bool Nondeterministic>
SparseLTLHelper<ValueType, Nondeterministic>::SparseLTLHelper(storm::storage::SparseMatrix<ValueType> const& transitionMatrix) : _transitionMatrix(transitionMatrix){
// Intentionally left empty.
}
template <typename ValueType, bool Nondeterministic>
storm::storage::Scheduler<ValueType> SparseLTLHelper<ValueType, Nondeterministic>::SparseLTLHelper::extractScheduler(storm::models::sparse::Model<ValueType> const& model) {
STORM_LOG_ASSERT(this->isProduceSchedulerSet(), "Trying to get the produced optimal choices although no scheduler was requested.");
// If Pmax(phi) = 0 or Pmin(phi) = 1, we return a memoryless scheduler with arbitrary choices
if (_randomScheduler) {
storm::storage::Scheduler<ValueType> scheduler(this->_transitionMatrix.getRowGroupCount());
for (storm::storage::sparse::state_type state = 0; state < this->_transitionMatrix.getRowGroupCount(); ++state) {
scheduler.setChoice(0, state);
}
return scheduler;
}
// Otherwise, we compute a scheduler with memory.
STORM_LOG_ASSERT(this->_producedChoices.is_initialized(), "Trying to extract the produced scheduler but none is available. Was there a computation call before?");
STORM_LOG_ASSERT(this->_memoryTransitions.is_initialized(), "Trying to extract the DA transition structure but none is available. Was there a computation call before?");
STORM_LOG_ASSERT(this->_memoryInitialStates.is_initialized(), "Trying to extract the initial states of the DA but there are none available. Was there a computation call before?");
STORM_LOG_ASSERT(this->_dontCareStates.is_initialized(), "Trying to extract the Scheduler-dontCare states but there are none available. Was there a computation call before?");
// Create a memory structure for the MDP scheduler with memory. If hasRelevantStates is set, we only consider initial model states relevant.
auto memoryBuilder = storm::storage::MemoryStructureBuilder<ValueType>(this->_memoryTransitions.get().size(), model, this->hasRelevantStates());
// Build the transitions between the memory states: startState--- modelStates (transitionVector) --->goalState
for (storm::storage::sparse::state_type startState = 0; startState < this->_memoryTransitions.get().size(); ++startState) {
for (storm::storage::sparse::state_type goalState = 0; goalState < this->_memoryTransitions.get().size(); ++goalState) {
// Bitvector that represents modelStates the model states that trigger this transition.
memoryBuilder.setTransition(startState, goalState, this->_memoryTransitions.get()[startState][goalState]);
}
}
// initialMemoryStates: Assign an initial memory state model states
if (this->hasRelevantStates()) {
// Only consider initial model states
for (uint_fast64_t modelState : model.getInitialStates()) {
memoryBuilder.setInitialMemoryState(modelState, this->_memoryInitialStates.get()[modelState]);
}
} else {
// All model states are relevant
for (uint_fast64_t modelState = 0; modelState < model.getNumberOfStates(); ++modelState) {
memoryBuilder.setInitialMemoryState(modelState, this->_memoryInitialStates.get()[modelState]);
}
}
// Build the memoryStructure.
storm::storage::MemoryStructure memoryStructure = memoryBuilder.build();
// Create a scheduler (with memory) for the model from the REACH and MEC scheduler of the MDP-DA-product model.
storm::storage::Scheduler<ValueType> scheduler(this->_transitionMatrix.getRowGroupCount(), memoryStructure);
// Use choices in the product model to create a choice based on model state and memory state
for (const auto &choice : this->_producedChoices.get()) {
// <s, q, InfSet> -> choice
storm::storage::sparse::state_type modelState = std::get<0>(choice.first);
storm::storage::sparse::state_type automatonState = std::get<1>(choice.first);
uint_fast64_t infSet = std::get<2>(choice.first);
STORM_LOG_ASSERT(!this->_dontCareStates.get()[(automatonState*(_infSets.get().size()+1))+ infSet].get(modelState), "Tried to set choice for dontCare state.");
scheduler.setChoice(choice.second, modelState, (automatonState*(_infSets.get().size()+1))+ infSet);
}
// Set "don't care" states
for (uint_fast64_t memoryState = 0; memoryState < this->_dontCareStates.get().size(); ++memoryState) {
for (auto state : this->_dontCareStates.get()[memoryState]) {
scheduler.setDontCare(state, memoryState);
}
}
// Sanity check for created scheduler.
STORM_LOG_ASSERT(scheduler.isDeterministicScheduler(), "Expected a deterministic scheduler");
STORM_LOG_ASSERT(!scheduler.isPartialScheduler(), "Expected a fully defined scheduler");
return scheduler;
}
template<typename ValueType, bool Nondeterministic>
std::map<std::string, storm::storage::BitVector> SparseLTLHelper<ValueType, Nondeterministic>::computeApSets(std::map<std::string, std::shared_ptr<storm::logic::Formula const>> const& extracted, std::function<std::unique_ptr<CheckResult>(std::shared_ptr<storm::logic::Formula const> const& formula)> formulaChecker){
std::map<std::string, storm::storage::BitVector> apSets;
for (auto& p: extracted) {
STORM_LOG_INFO(" Computing satisfaction set for atomic proposition \"" << p.first << "\" <=> " << *p.second << "...");
std::unique_ptr<CheckResult> subResultPointer = formulaChecker(p.second);
ExplicitQualitativeCheckResult const& subResult = subResultPointer->asExplicitQualitativeCheckResult();
auto sat = subResult.getTruthValuesVector();
apSets[p.first] = std::move(sat);
STORM_LOG_INFO(" Atomic proposition \"" << p.first << "\" is satisfied by " << apSets[p.first].getNumberOfSetBits() << " states.");
}
return apSets;
}
template <typename ValueType, bool Nondeterministic>
storm::storage::BitVector SparseLTLHelper<ValueType, Nondeterministic>::computeAcceptingECs(automata::AcceptanceCondition const& acceptance, storm::storage::SparseMatrix<ValueType> const& transitionMatrix, storm::storage::SparseMatrix<ValueType> const& backwardTransitions, typename transformer::DAProduct<productModelType>::ptr product) {
STORM_LOG_INFO("Computing accepting states for acceptance condition " << *acceptance.getAcceptanceExpression());
if (acceptance.getAcceptanceExpression()->isTRUE()) {
STORM_LOG_INFO(" TRUE -> all states accepting (assumes no deadlock in the model)");
return storm::storage::BitVector(transitionMatrix.getRowGroupCount(), true);
} else if (acceptance.getAcceptanceExpression()->isFALSE()) {
STORM_LOG_INFO(" FALSE -> all states rejecting");
return storm::storage::BitVector(transitionMatrix.getRowGroupCount(), false);
}
std::vector<std::vector<automata::AcceptanceCondition::acceptance_expr::ptr>> dnf = acceptance.extractFromDNF();
storm::storage::BitVector acceptingStates(transitionMatrix.getRowGroupCount(), false);
std::size_t accMECs = 0;
std::size_t allMECs = 0;
std::size_t i = 0;
if (this->isProduceSchedulerSet()) {
_infSets.emplace();
_accInfSets.emplace(product->getProductModel().getNumberOfStates(), boost::none);
_producedChoices.emplace();
}
for (auto const& conjunction : dnf) {
// Determine the set of states of the subMDP that can satisfy the condition, remove all states that would violate Fins in the conjunction.
storm::storage::BitVector allowed(transitionMatrix.getRowGroupCount(), true);
STORM_LOG_INFO("Handle conjunction " << i);
for (auto const& literal : conjunction) {
STORM_LOG_INFO(" " << *literal);
if (literal->isTRUE()) {
// skip
} else if (literal->isFALSE()) {
allowed.clear();
break;
} else if (literal->isAtom()) {
const cpphoafparser::AtomAcceptance& atom = literal->getAtom();
if (atom.getType() == cpphoafparser::AtomAcceptance::TEMPORAL_FIN) {
// only deal with FIN, ignore INF here
const storm::storage::BitVector& accSet = acceptance.getAcceptanceSet(atom.getAcceptanceSet());
if (atom.isNegated()) {
// allowed = allowed \ ~accSet = allowed & accSet
allowed &= accSet;
} else {
// allowed = allowed \ accSet = allowed & ~accSet
allowed &= ~accSet;
}
}
}
}
if (allowed.empty()) {
// skip
continue;
}
STORM_LOG_DEBUG(" Allowed states: " << allowed);
// Compute MECs in the allowed fragment
storm::storage::MaximalEndComponentDecomposition<ValueType> mecs(transitionMatrix, backwardTransitions, allowed);
allMECs += mecs.size();
for (const auto& mec : mecs) {
STORM_LOG_DEBUG("Inspect MEC: " << mec);
bool accepting = true;
for (auto const& literal : conjunction) {
if (literal->isTRUE()) {
// skip
} else if (literal->isFALSE()) {
accepting = false;
break;
} else if (literal->isAtom()) {
const cpphoafparser::AtomAcceptance& atom = literal->getAtom();
const storm::storage::BitVector& accSet = acceptance.getAcceptanceSet(atom.getAcceptanceSet());
if (atom.getType() == cpphoafparser::AtomAcceptance::TEMPORAL_INF) {
if (atom.isNegated()) {
STORM_LOG_DEBUG("Checking against " << ~accSet);
if (!mec.containsAnyState(~accSet)) {
STORM_LOG_DEBUG(" -> not satisfied");
accepting = false;
break;
}
} else {
STORM_LOG_DEBUG("Checking against " << accSet);
if (!mec.containsAnyState(accSet)) {
STORM_LOG_DEBUG(" -> not satisfied");
accepting = false;
break;
}
}
} else if (atom.getType() == cpphoafparser::AtomAcceptance::TEMPORAL_FIN) {
// do only sanity checks here
STORM_LOG_ASSERT(atom.isNegated() ? !mec.containsAnyState(~accSet) : !mec.containsAnyState(accSet), "MEC contains Fin-states, which should have been removed");
}
}
}
if (accepting) {
accMECs++;
STORM_LOG_DEBUG("MEC is accepting");
for (auto const &stateChoicePair : mec) {
acceptingStates.set(stateChoicePair.first);
}
if (this->isProduceSchedulerSet()) {
// Save all states contained in this MEC
storm::storage::BitVector mecStates(transitionMatrix.getRowGroupCount(), false);
for (auto const &stateChoicePair : mec) {
mecStates.set(stateChoicePair.first);
}
// We know the MEC satisfied the conjunction: Save InfSets
std::set<uint_fast64_t> infSetIds;
for (auto const& literal : conjunction) {
storm::storage::BitVector infSet;
if (literal->isTRUE()) {
// All states
infSet = storm::storage::BitVector(transitionMatrix.getRowGroupCount(), true);
} else if (literal->isAtom()) {
const cpphoafparser::AtomAcceptance &atom = literal->getAtom();
if (atom.getType() == cpphoafparser::AtomAcceptance::TEMPORAL_INF) {
if (atom.isNegated()) {
infSet = ~acceptance.getAcceptanceSet(atom.getAcceptanceSet());
} else {
infSet = acceptance.getAcceptanceSet(atom.getAcceptanceSet());
}
}
else if (atom.getType() == cpphoafparser::AtomAcceptance::TEMPORAL_FIN) {
// If there are FinSets in the conjunction we use the InfSet containing all states in this MEC
infSet = mecStates;
}
}
// Save new InfSets
if (infSet.size() > 0) {
auto it = std::find(_infSets.get().begin(), _infSets.get().end(), infSet);
if (it == _infSets.get().end()) {
infSetIds.insert(_infSets.get().size());
_infSets.get().emplace_back(infSet);
} else {
// save ID for accCond of the MEC states
infSetIds.insert(distance(_infSets.get().begin(), it));
}
}
}
// Save the InfSets into the _accInfSets for states in this MEC, but only if there weren't assigned to any other MEC yet.
storm::storage::BitVector newMecStates(transitionMatrix.getRowGroupCount(), false);
for (auto const &stateChoicePair : mec) {
if (_accInfSets.get()[stateChoicePair.first] == boost::none) {
// state wasn't assigned to any other MEC yet.
_accInfSets.get()[stateChoicePair.first].emplace(infSetIds);
newMecStates.set(stateChoicePair.first);
}
}
// Define scheduler choices for the states in this MEC (that are not in any other MEC)
for (uint_fast64_t id : infSetIds) {
// Scheduler that satisfies the MEC acceptance condition (visit each InfSet inf often, or switch to scheduler of another MEC)
storm::storage::Scheduler<ValueType> mecScheduler(transitionMatrix.getRowGroupCount());
// States not in InfSet: Compute a scheduler that, with prob=1, reaches the infSet via mecStates starting from states that are not yet in other MEC
storm::utility::graph::computeSchedulerProb1E<ValueType>(newMecStates, transitionMatrix, backwardTransitions, mecStates, _infSets.get()[id] & mecStates, mecScheduler);
// States that already reached the InfSet
for (auto pState : (newMecStates & _infSets.get()[id])) {
// Prob1E sets an arbitrary choice for the psi states, but we want to stay in this accepting MEC.
mecScheduler.setChoice(*mec.getChoicesForState(pState).begin() - transitionMatrix.getRowGroupIndices()[pState], pState);
}
// Extract scheduler choices (only for states that are already assigned a scheduler, i.e are in another MEC)
for (auto pState : newMecStates) {
// We want to reach the InfSet, save choice: <s, q, InfSetID> ---> choice
this->_producedChoices.get().insert({std::make_tuple(product->getModelState(pState), product->getAutomatonState(pState), id), mecScheduler.getChoice(pState)});
}
}
}
}
}
}
STORM_LOG_DEBUG("Accepting states: " << acceptingStates);
STORM_LOG_INFO("Found " << acceptingStates.getNumberOfSetBits() << " states in " << accMECs << " accepting MECs (considered " << allMECs << " MECs).");
return acceptingStates;
}
template <typename ValueType, bool Nondeterministic>
storm::storage::BitVector SparseLTLHelper<ValueType, Nondeterministic>::computeAcceptingBCCs(automata::AcceptanceCondition const& acceptance, storm::storage::SparseMatrix<ValueType> const& transitionMatrix) {
storm::storage::StronglyConnectedComponentDecomposition<ValueType> bottomSccs(transitionMatrix, storage::StronglyConnectedComponentDecompositionOptions().onlyBottomSccs().dropNaiveSccs());
storm::storage::BitVector acceptingStates(transitionMatrix.getRowGroupCount(), false);
std::size_t checkedBSCCs = 0, acceptingBSCCs = 0, acceptingBSCCStates = 0;
for (auto& scc : bottomSccs) {
checkedBSCCs++;
if (acceptance.isAccepting(scc)) {
acceptingBSCCs++;
for (auto& state : scc) {
acceptingStates.set(state);
acceptingBSCCStates++;
}
}
}
STORM_LOG_INFO("BSCC analysis: " << acceptingBSCCs << " of " << checkedBSCCs << " BSCCs were acceptingStates (" << acceptingBSCCStates << " states in acceptingStates BSCCs).");
return acceptingStates;
}
template <typename ValueType, bool Nondeterministic>
void SparseLTLHelper<ValueType, Nondeterministic>::prepareScheduler(uint_fast64_t numDaStates, storm::storage::BitVector const& acceptingProductStates, std::unique_ptr<storm::storage::Scheduler<ValueType>> reachScheduler, transformer::DAProductBuilder const& productBuilder, typename transformer::DAProduct<productModelType>::ptr product, storm::storage::BitVector const& modelStatesOfInterest) {
STORM_LOG_ASSERT(this->_producedChoices.is_initialized(), "Trying to extract the produced scheduler but none is available. Was there a computation call before?");
STORM_LOG_ASSERT(this->_infSets.is_initialized(), "Was there a computation call before?");
STORM_LOG_ASSERT(this->_accInfSets.is_initialized(), "Was there a computation call before?");
// Compute size of the resulting memory structure: A state <q, infSet> is encoded as (q* (|infSets|+1))+ |infSet|
uint64 numMemoryStates = (numDaStates) * (_infSets.get().size()+1); //+1 for states outside accECs
_dontCareStates.emplace(numMemoryStates, storm::storage::BitVector(this->_transitionMatrix.getRowGroupCount(), false));
// Set choices for states or consider them "dontCare"
for (storm::storage::sparse::state_type automatonState= 0; automatonState < numDaStates; ++automatonState) {
for (storm::storage::sparse::state_type modelState = 0; modelState < this->_transitionMatrix.getRowGroupCount(); ++modelState) {
if (!product->isValidProductState(modelState, automatonState)) {
// If the state <s,q> does not occur in the product model, all the infSet combinations are irrelevant for the scheduler.
for (uint_fast64_t infSet = 0; infSet < _infSets.get().size()+1; ++infSet) {
_dontCareStates.get()[automatonState * (_infSets.get().size() + 1) + infSet].set(modelState, true);
}
} else {
auto pState = product->getProductStateIndex(modelState, automatonState);
if (acceptingProductStates.get(pState)) {
// For states in accepting ECs set the missing MEC-scheduler combinations are "dontCare", they are not reachable using the scheduler choices. //TODO is this correct?
for (uint_fast64_t infSet = 0; infSet < _infSets.get().size()+1; ++infSet) {
if (_producedChoices.get().find(std::make_tuple(product->getModelState(pState), product->getAutomatonState(pState), infSet)) == _producedChoices.get().end() ) {
_dontCareStates.get()[(product->getAutomatonState(pState)) * (_infSets.get().size()+1) + infSet].set(product->getModelState(pState), true);
}
}
} else {
// Extract the choices of the REACH-scheduler (choices to reach an acc. MEC) for the MDP-DA product: <s,q> -> choice. The memory structure corresponds to the "last" copy of the DA (_infSets.get().size()).
this->_accInfSets.get()[pState] = {_infSets.get().size()};
if (reachScheduler->isDontCare(pState)) {
// Mark the maybe States of the untilProbability scheduler as "dontCare"
_dontCareStates.get()[(product->getAutomatonState(pState)) * (_infSets.get().size()+1) + _infSets.get().size()].set(product->getModelState(pState), true);
} else {
// Set choice For non-accepting states that are not in any accepting EC
this->_producedChoices.get().insert({std::make_tuple(product->getModelState(pState),product->getAutomatonState(pState),_infSets.get().size()),reachScheduler->getChoice(pState)});
};
// All other InfSet combinations are unreachable (dontCare)
for (uint_fast64_t infSet = 0; infSet < _infSets.get().size(); ++infSet) {
_dontCareStates.get()[(product->getAutomatonState(pState)) * (_infSets.get().size()+1) + infSet].set(product->getModelState(pState), true);
}
}
}
}
}
// Prepare the memory structure. For that, we need: transitions, initialMemoryStates (and memoryStateLabeling)
// The next move function of the memory, will be build based on the transitions of the DA and jumps between InfSets.
_memoryTransitions.emplace(numMemoryStates, std::vector<storm::storage::BitVector>(numMemoryStates, storm::storage::BitVector(_transitionMatrix.getRowGroupCount(), false)));
for (storm::storage::sparse::state_type automatonFrom = 0; automatonFrom < numDaStates; ++automatonFrom) {
for (storm::storage::sparse::state_type modelState = 0; modelState < _transitionMatrix.getRowGroupCount(); ++modelState) {
uint_fast64_t automatonTo = productBuilder.getSuccessor(automatonFrom, modelState);
if (product->isValidProductState(modelState, automatonTo)) {
// Add the modelState to one outgoing transition of all states of the form <automatonFrom, InfSet> (Inf=lenInfSet equals not in MEC)
// For non-accepting states that are not in any accepting EC we use the 'last' copy of the DA
// and for the accepting states we jump through copies of the DA wrt. the infinity sets.
for (uint_fast64_t infSet = 0; infSet < _infSets.get().size()+1; ++infSet) {
// Check if we need to switch the acceptance condition
STORM_LOG_ASSERT(_accInfSets.get()[product->getProductStateIndex(modelState, automatonTo)] != boost::none, "The list of InfSets for the product state <" <<modelState<< ", " << automatonTo<<"> is undefined.");
if (_accInfSets.get()[product->getProductStateIndex(modelState, automatonTo)].get().count(infSet) == 0) {
// the state is is in a different accepting MEC with a different accepting conjunction of InfSets.
auto newInfSet = _accInfSets.get()[product->getProductStateIndex(modelState, automatonTo)].get().begin();
_memoryTransitions.get()[(automatonFrom * (_infSets.get().size()+1)) + infSet][(automatonTo * (_infSets.get().size()+1)) + *newInfSet].set(modelState);
} else {
// Continue looking for any accepting EC (if we haven't reached one yet) or stay in the corresponding accepting EC, test whether we have reached the next infSet.
if (infSet == _infSets.get().size() || !(_infSets.get()[infSet].get(product->getProductStateIndex(modelState, automatonTo)))) {
// <modelState, automatonTo> is not in any accepting EC or does not satisfy the InfSet, we stay there.
// Add modelState to the transition from <automatonFrom, InfSet> to <automatonTo, InfSet>
_memoryTransitions.get()[(automatonFrom * (_infSets.get().size()+1)) + infSet][(automatonTo * (_infSets.get().size()+1)) + infSet].set(modelState);
} else {
STORM_LOG_ASSERT(_accInfSets.get()[product->getProductStateIndex(modelState, automatonTo)] != boost::none, "The list of InfSets for the product state <" <<modelState<< ", " << automatonTo<<"> is undefined.");
// <modelState, automatonTo> satisfies the InfSet, find the next one.
auto nextInfSet = std::find(_accInfSets.get()[product->getProductStateIndex(modelState, automatonTo)].get().begin(), _accInfSets.get()[product->getProductStateIndex(modelState, automatonTo)].get().end(), infSet);
STORM_LOG_ASSERT(nextInfSet != _accInfSets.get()[product->getProductStateIndex(modelState, automatonTo)].get().end(), "The list of InfSets for the product state <" <<modelState<< ", " << automatonTo<<"> does not contain the infSet " << infSet);
nextInfSet++;
if (nextInfSet == _accInfSets.get()[product->getProductStateIndex(modelState, automatonTo)].get().end()) {
// Start again.
nextInfSet = _accInfSets.get()[product->getProductStateIndex(modelState, automatonTo)].get().begin();
}
// Add modelState to the transition from <automatonFrom <mec, InfSet>> to <automatonTo, <mec, NextInfSet>>.
_memoryTransitions.get()[(automatonFrom * (_infSets.get().size()+1)) + infSet][(automatonTo * (_infSets.get().size()+1)) + *nextInfSet].set(modelState);
}
}
}
}
}
}
// Finished creation of transitions.
// Find initial memory states
this->_memoryInitialStates.emplace();
this->_memoryInitialStates->resize(this->_transitionMatrix.getRowGroupCount());
// Save for each relevant model state its initial memory state (get the s-successor q of q0)
for (storm::storage::sparse::state_type modelState : modelStatesOfInterest) {
storm::storage::sparse::state_type automatonState = productBuilder.getInitialState(modelState);
STORM_LOG_ASSERT(product->isValidProductState(modelState, automatonState), "The memory successor state for the model state "<< modelState << "does not exist in the DA-Model Product.");
if (acceptingProductStates[product->getProductStateIndex(modelState, automatonState)]) {
STORM_LOG_ASSERT(_accInfSets.get()[product->getProductStateIndex(modelState, automatonState)] != boost::none, "The list of InfSets for the product state <" <<modelState<< ", " << automatonState<<"> is undefined.");
// If <s, q> is an accepting state start in the first InfSet of <s, q>.
auto infSet = _accInfSets.get()[product->getProductStateIndex(modelState, automatonState)].get().begin();
_memoryInitialStates.get()[modelState] = (automatonState * (_infSets.get().size()+1)) + *infSet;
} else {
_memoryInitialStates.get()[modelState] = (automatonState * (_infSets.get().size()+1)) + _infSets.get().size();
}
}
// Finished creation of initial states.
}
template<typename ValueType, bool Nondeterministic>
std::vector<ValueType> SparseLTLHelper<ValueType, Nondeterministic>::computeDAProductProbabilities(Environment const& env, storm::automata::DeterministicAutomaton const& da, std::map<std::string, storm::storage::BitVector>& apSatSets) {
const storm::automata::APSet& apSet = da.getAPSet();
std::vector<storm::storage::BitVector> statesForAP;
for (const std::string& ap : apSet.getAPs()) {
auto it = apSatSets.find(ap);
STORM_LOG_THROW(it != apSatSets.end(), storm::exceptions::InvalidOperationException, "Deterministic automaton has AP " << ap << ", does not appear in formula");
statesForAP.push_back(std::move(it->second));
}
storm::storage::BitVector statesOfInterest;
if (this->hasRelevantStates()) {
statesOfInterest = this->getRelevantStates();
} else {
// Product from all model states
statesOfInterest = storm::storage::BitVector(this->_transitionMatrix.getRowGroupCount(), true);
}
STORM_LOG_INFO("Building "+ (Nondeterministic ? std::string("MDP-DA") : std::string("DTMC-DA")) +" product with deterministic automaton, starting from " << statesOfInterest.getNumberOfSetBits() << " model states...");
transformer::DAProductBuilder productBuilder(da, statesForAP);
auto product = productBuilder.build<productModelType>(this->_transitionMatrix, statesOfInterest);
STORM_LOG_INFO("Product "+ (Nondeterministic ? std::string("MDP-DA") : std::string("DTMC-DA")) +" has " << product->getProductModel().getNumberOfStates() << " states and "
<< product->getProductModel().getNumberOfTransitions() << " transitions.");
if (storm::settings::getModule<storm::settings::modules::DebugSettings>().isTraceSet()) {
STORM_LOG_TRACE("Writing product model to product.dot");
std::ofstream productDot("product.dot");
product->getProductModel().writeDotToStream(productDot);
productDot.close();
STORM_LOG_TRACE("Product model mapping:");
std::stringstream str;
product->printMapping(str);
STORM_LOG_TRACE(str.str());
}
// Compute accepting states
storm::storage::BitVector acceptingStates;
if (Nondeterministic) {
STORM_LOG_INFO("Computing MECs and checking for acceptance...");
acceptingStates = computeAcceptingECs(*product->getAcceptance(), product->getProductModel().getTransitionMatrix(), product->getProductModel().getBackwardTransitions(), product); //TODO product is only needed for ->getModelState(pState) (remove arg)
} else {
STORM_LOG_INFO("Computing BSCCs and checking for acceptance...");
acceptingStates = computeAcceptingBCCs(*product->getAcceptance(), product->getProductModel().getTransitionMatrix());
}
if (acceptingStates.empty()) {
STORM_LOG_INFO("No accepting states, skipping probability computation.");
std::vector<ValueType> numericResult(this->_transitionMatrix.getRowGroupCount(), storm::utility::zero<ValueType>());
this->_randomScheduler = true;
return numericResult;
}
STORM_LOG_INFO("Computing probabilities for reaching accepting components...");
storm::storage::BitVector bvTrue(product->getProductModel().getNumberOfStates(), true);
storm::storage::BitVector soiProduct(product->getStatesOfInterest());
// Create goal for computeUntilProbabilities, always compute maximizing probabilities
storm::solver::SolveGoal<ValueType> solveGoalProduct;
if (this->isValueThresholdSet()) {
solveGoalProduct = storm::solver::SolveGoal<ValueType>(OptimizationDirection::Maximize, this->getValueThresholdComparisonType(), this->getValueThresholdValue(), std::move(soiProduct));
} else {
solveGoalProduct = storm::solver::SolveGoal<ValueType>(OptimizationDirection::Maximize);
solveGoalProduct.setRelevantValues(std::move(soiProduct));
}
std::vector<ValueType> prodNumericResult;
if (Nondeterministic) {
MDPSparseModelCheckingHelperReturnType<ValueType> prodCheckResult = storm::modelchecker::helper::SparseMdpPrctlHelper<ValueType>::computeUntilProbabilities(env,
std::move(solveGoalProduct),
product->getProductModel().getTransitionMatrix(),
product->getProductModel().getBackwardTransitions(),
bvTrue,
acceptingStates,
this->isQualitativeSet(),
this->isProduceSchedulerSet() // Whether to create memoryless scheduler for the Model-DA Product.
);
prodNumericResult = std::move(prodCheckResult.values);
if (this->isProduceSchedulerSet()) {
prepareScheduler(da.getNumberOfStates(), acceptingStates, std::move(prodCheckResult.scheduler), productBuilder, product, statesOfInterest);
}
} else {
prodNumericResult = storm::modelchecker::helper::SparseDtmcPrctlHelper<ValueType>::computeUntilProbabilities(env,
std::move(solveGoalProduct),
product->getProductModel().getTransitionMatrix(),
product->getProductModel().getBackwardTransitions(),
bvTrue,
acceptingStates,
this->isQualitativeSet());
}
std::vector<ValueType> numericResult = product->projectToOriginalModel(this->_transitionMatrix.getRowGroupCount(), prodNumericResult);
return numericResult;
}
template<typename ValueType, bool Nondeterministic>
std::vector <ValueType> SparseLTLHelper<ValueType, Nondeterministic>::computeLTLProbabilities(Environment const& env, storm::logic::Formula const& formula, std::map<std::string, storm::storage::BitVector>& apSatSets) {
std::shared_ptr<storm::logic::Formula const> ltlFormula;
STORM_LOG_THROW((!Nondeterministic) || this->isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
if (Nondeterministic && this->getOptimizationDirection() == OptimizationDirection::Minimize) {
// negate formula in order to compute 1-Pmax[!formula]
ltlFormula = std::make_shared<storm::logic::UnaryBooleanPathFormula>(storm::logic::UnaryBooleanOperatorType::Not, formula.asSharedPointer());
STORM_LOG_INFO("Computing Pmin, proceeding with negated LTL formula.");
} else {
ltlFormula = formula.asSharedPointer();
}
STORM_LOG_INFO("Resulting LTL path formula: " << ltlFormula->toString());
STORM_LOG_INFO(" in prefix format: " << ltlFormula->toPrefixString());
// Convert LTL formula to a deterministic automaton
std::shared_ptr<storm::automata::DeterministicAutomaton> da;
if (env.modelchecker().isLtl2daSet()) {
// Use the external tool given via ltl2da
std::string ltl2da = env.modelchecker().getLtl2da().get();
da = storm::automata::LTL2DeterministicAutomaton::ltl2daExternalTool(*ltlFormula, ltl2da);
}
else {
// Use the internal tool (Spot)
// For nondeterministic models the acceptance condition is transformed into DNF
da = storm::automata::LTL2DeterministicAutomaton::ltl2daSpot(*ltlFormula, Nondeterministic);
}
STORM_LOG_INFO("Deterministic automaton for LTL formula has "
<< da->getNumberOfStates() << " states, "
<< da->getAPSet().size() << " atomic propositions and "
<< *da->getAcceptance()->getAcceptanceExpression() << " as acceptance condition." << std::endl);
std::vector<ValueType> numericResult = computeDAProductProbabilities(env, *da, apSatSets);
if(Nondeterministic && this->getOptimizationDirection()==OptimizationDirection::Minimize) {
// compute 1-Pmax[!fomula]
for (auto& value : numericResult) {
value = storm::utility::one<ValueType>() - value;
}
}
return numericResult;
}
template class SparseLTLHelper<double, false>;
template class SparseLTLHelper<double, true>;
#ifdef STORM_HAVE_CARL
template class SparseLTLHelper<storm::RationalNumber, false>;
template class SparseLTLHelper<storm::RationalNumber, true>;
template class SparseLTLHelper<storm::RationalFunction, false>;
#endif
}
}
}