19class DeterministicAutomaton;
22namespace modelchecker {
30template<
typename ValueType,
bool Nondeterministic>
68 static std::map<std::string, storm::storage::BitVector>
computeApSets(std::map<std::string, std::shared_ptr<storm::logic::Formula const>>
const& extracted,
78 std::map<std::string, storm::storage::BitVector>& apSatSets);
87 std::map<std::string, storm::storage::BitVector>& apSatSets);
117 boost::optional<storm::modelchecker::helper::internal::SparseLTLSchedulerHelper<ValueType, Nondeterministic>> _schedulerHelper;
Helper for model checking queries where we are interested in (optimizing) a single value per state.
Helper class for LTL model checking.
std::function< storm::storage::BitVector(storm::logic::Formula const &)> CheckFormulaCallback
std::vector< ValueType > computeLTLProbabilities(Environment const &env, storm::logic::PathFormula const &formula, CheckFormulaCallback const &formulaChecker)
Computes the LTL probabilities.
storm::storage::Scheduler< ValueType > extractScheduler(storm::models::sparse::Model< ValueType > const &model)
static std::map< std::string, storm::storage::BitVector > computeApSets(std::map< std::string, std::shared_ptr< storm::logic::Formula const > > const &extracted, CheckFormulaCallback const &formulaChecker)
Computes the states that are satisfying the AP.
std::vector< ValueType > computeDAProductProbabilities(Environment const &env, storm::automata::DeterministicAutomaton const &da, std::map< std::string, storm::storage::BitVector > &apSatSets)
Computes the (maximizing) probabilities for the constructed DA product.
typename std::conditional< Nondeterministic, storm::models::sparse::Mdp< ValueType >, storm::models::sparse::Dtmc< ValueType > >::type productModelType
The type of the product model (DTMC or MDP) that is used during the computation.
This class represents a discrete-time Markov chain.
Base class for all sparse models.
A bit vector that is internally represented as a vector of 64-bit values.
This class defines which action is chosen in a particular state of a non-deterministic model.
A class that holds a possibly non-square matrix in the compressed row storage format.