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468 lines
26 KiB
468 lines
26 KiB
#include "DFTModelChecker.h"
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#include "storm/builder/ParallelCompositionBuilder.h"
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#include "storm/utility/bitoperations.h"
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#include "storm/utility/DirectEncodingExporter.h"
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#include "storm-dft/builder/ExplicitDFTModelBuilder.h"
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#include "storm-dft/builder/ExplicitDFTModelBuilderApprox.h"
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#include "storm-dft/storage/dft/DFTIsomorphism.h"
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#include "storm-dft/settings/modules/DFTSettings.h"
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namespace storm {
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namespace modelchecker {
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template<typename ValueType>
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void DFTModelChecker<ValueType>::check(storm::storage::DFT<ValueType> const& origDft, std::vector<std::shared_ptr<const storm::logic::Formula>> const& properties, bool symred, bool allowModularisation, bool enableDC, double approximationError) {
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// Initialize
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this->approximationError = approximationError;
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totalTimer.start();
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// Optimizing DFT
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storm::storage::DFT<ValueType> dft = origDft.optimize();
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// TODO Matthias: check that all paths reach the target state for approximation
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// Checking DFT
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if (properties[0]->isTimeOperatorFormula() && allowModularisation) {
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// Use parallel composition as modularisation approach for expected time
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std::shared_ptr<storm::models::sparse::Model<ValueType>> model = buildModelViaComposition(dft, properties, symred, true, enableDC, approximationError);
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// Model checking
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std::vector<ValueType> resultsValue = checkModel(model, properties);
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for (ValueType result : resultsValue) {
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checkResults.push_back(result);
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}
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} else {
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checkResults = checkHelper(dft, properties, symred, allowModularisation, enableDC, approximationError);
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}
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totalTimer.stop();
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}
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template<typename ValueType>
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typename DFTModelChecker<ValueType>::dft_results DFTModelChecker<ValueType>::checkHelper(storm::storage::DFT<ValueType> const& dft, property_vector const& properties, bool symred, bool allowModularisation, bool enableDC, double approximationError) {
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STORM_LOG_TRACE("Check helper called");
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std::vector<storm::storage::DFT<ValueType>> dfts;
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bool invResults = false;
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size_t nrK = 0; // K out of M
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size_t nrM = 0; // K out of M
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// Try modularisation
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if(allowModularisation) {
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switch (dft.topLevelType()) {
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case storm::storage::DFTElementType::AND:
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STORM_LOG_TRACE("top modularisation called AND");
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dfts = dft.topModularisation();
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STORM_LOG_TRACE("Modularsation into " << dfts.size() << " submodules.");
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nrK = dfts.size();
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nrM = dfts.size();
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break;
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case storm::storage::DFTElementType::OR:
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STORM_LOG_TRACE("top modularisation called OR");
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dfts = dft.topModularisation();
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STORM_LOG_TRACE("Modularsation into " << dfts.size() << " submodules.");
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nrK = 0;
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nrM = dfts.size();
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invResults = true;
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break;
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case storm::storage::DFTElementType::VOT:
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STORM_LOG_TRACE("top modularisation called VOT");
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dfts = dft.topModularisation();
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STORM_LOG_TRACE("Modularsation into " << dfts.size() << " submodules.");
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nrK = std::static_pointer_cast<storm::storage::DFTVot<ValueType> const>(dft.getTopLevelGate())->threshold();
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nrM = dfts.size();
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if(nrK <= nrM/2) {
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nrK -= 1;
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invResults = true;
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}
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break;
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default:
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// No static gate -> no modularisation applicable
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break;
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}
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}
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// Perform modularisation
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if(dfts.size() > 1) {
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STORM_LOG_TRACE("Recursive CHECK Call");
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// TODO Matthias: compute simultaneously
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dft_results results;
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for (auto property : properties) {
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if (!property->isProbabilityOperatorFormula()) {
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STORM_LOG_WARN("Could not check property: " << *property);
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} else {
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// Recursively call model checking
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std::vector<ValueType> res;
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for(auto const ft : dfts) {
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// TODO Matthias: allow approximation in modularisation
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dft_results ftResults = checkHelper(ft, {property}, symred, true, enableDC, 0.0);
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STORM_LOG_ASSERT(ftResults.size() == 1, "Wrong number of results");
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res.push_back(boost::get<ValueType>(ftResults[0]));
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}
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// Combine modularisation results
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STORM_LOG_TRACE("Combining all results... K=" << nrK << "; M=" << nrM << "; invResults=" << (invResults?"On":"Off"));
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ValueType result = storm::utility::zero<ValueType>();
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int limK = invResults ? -1 : nrM+1;
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int chK = invResults ? -1 : 1;
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// WARNING: there is a bug for computing permutations with more than 32 elements
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STORM_LOG_ASSERT(res.size() < 32, "Permutations work only for < 32 elements");
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for(int cK = nrK; cK != limK; cK += chK ) {
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STORM_LOG_ASSERT(cK >= 0, "ck negative.");
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size_t permutation = smallestIntWithNBitsSet(static_cast<size_t>(cK));
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do {
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STORM_LOG_TRACE("Permutation="<<permutation);
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ValueType permResult = storm::utility::one<ValueType>();
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for(size_t i = 0; i < res.size(); ++i) {
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if(permutation & (1 << i)) {
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permResult *= res[i];
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} else {
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permResult *= storm::utility::one<ValueType>() - res[i];
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}
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}
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STORM_LOG_TRACE("Result for permutation:"<<permResult);
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permutation = nextBitPermutation(permutation);
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result += permResult;
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} while(permutation < (1 << nrM) && permutation != 0);
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}
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if(invResults) {
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result = storm::utility::one<ValueType>() - result;
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}
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results.push_back(result);
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}
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}
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return results;
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} else {
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// No modularisation was possible
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return checkDFT(dft, properties, symred, enableDC, approximationError);
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}
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}
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template<typename ValueType>
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std::shared_ptr<storm::models::sparse::Ctmc<ValueType>> DFTModelChecker<ValueType>::buildModelViaComposition(storm::storage::DFT<ValueType> const& dft, property_vector const& properties, bool symred, bool allowModularisation, bool enableDC, double approximationError) {
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// TODO Matthias: use approximation?
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STORM_LOG_TRACE("Build model via composition");
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std::vector<storm::storage::DFT<ValueType>> dfts;
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bool isAnd = true;
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// Try modularisation
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if(allowModularisation) {
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switch (dft.topLevelType()) {
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case storm::storage::DFTElementType::AND:
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STORM_LOG_TRACE("top modularisation called AND");
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dfts = dft.topModularisation();
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STORM_LOG_TRACE("Modularisation into " << dfts.size() << " submodules.");
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isAnd = true;
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break;
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case storm::storage::DFTElementType::OR:
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STORM_LOG_TRACE("top modularisation called OR");
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dfts = dft.topModularisation();
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STORM_LOG_TRACE("Modularsation into " << dfts.size() << " submodules.");
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isAnd = false;
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break;
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case storm::storage::DFTElementType::VOT:
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// TODO enable modularisation for voting gate
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break;
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default:
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// No static gate -> no modularisation applicable
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break;
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}
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}
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// Perform modularisation via parallel composition
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if(dfts.size() > 1) {
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STORM_LOG_TRACE("Recursive CHECK Call");
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bool firstTime = true;
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std::shared_ptr<storm::models::sparse::Ctmc<ValueType>> composedModel;
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for (auto const ft : dfts) {
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STORM_LOG_INFO("Building Model via parallel composition...");
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explorationTimer.start();
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// Find symmetries
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std::map<size_t, std::vector<std::vector<size_t>>> emptySymmetry;
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storm::storage::DFTIndependentSymmetries symmetries(emptySymmetry);
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if(symred) {
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auto colouring = ft.colourDFT();
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symmetries = ft.findSymmetries(colouring);
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STORM_LOG_INFO("Found " << symmetries.groups.size() << " symmetries.");
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STORM_LOG_TRACE("Symmetries: " << std::endl << symmetries);
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}
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// Build a single CTMC
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STORM_LOG_INFO("Building Model...");
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storm::builder::ExplicitDFTModelBuilderApprox<ValueType> builder(ft, symmetries, enableDC);
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typename storm::builder::ExplicitDFTModelBuilderApprox<ValueType>::LabelOptions labeloptions(properties);
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builder.buildModel(labeloptions, 0, 0.0);
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std::shared_ptr<storm::models::sparse::Model<ValueType>> model = builder.getModel();
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explorationTimer.stop();
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STORM_LOG_THROW(model->isOfType(storm::models::ModelType::Ctmc), storm::exceptions::NotSupportedException, "Parallel composition only applicable for CTMCs");
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std::shared_ptr<storm::models::sparse::Ctmc<ValueType>> ctmc = model->template as<storm::models::sparse::Ctmc<ValueType>>();
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// Apply bisimulation to new CTMC
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bisimulationTimer.start();
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ctmc = storm::performDeterministicSparseBisimulationMinimization<storm::models::sparse::Ctmc<ValueType>>(ctmc, properties, storm::storage::BisimulationType::Weak)->template as<storm::models::sparse::Ctmc<ValueType>>();
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bisimulationTimer.stop();
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if (firstTime) {
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composedModel = ctmc;
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firstTime = false;
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} else {
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composedModel = storm::builder::ParallelCompositionBuilder<ValueType>::compose(composedModel, ctmc, isAnd);
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}
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// Apply bisimulation to parallel composition
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bisimulationTimer.start();
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composedModel = storm::performDeterministicSparseBisimulationMinimization<storm::models::sparse::Ctmc<ValueType>>(composedModel, properties, storm::storage::BisimulationType::Weak)->template as<storm::models::sparse::Ctmc<ValueType>>();
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bisimulationTimer.stop();
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STORM_LOG_DEBUG("No. states (Composed): " << composedModel->getNumberOfStates());
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STORM_LOG_DEBUG("No. transitions (Composed): " << composedModel->getNumberOfTransitions());
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if (composedModel->getNumberOfStates() <= 15) {
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STORM_LOG_TRACE("Transition matrix: " << std::endl << composedModel->getTransitionMatrix());
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} else {
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STORM_LOG_TRACE("Transition matrix: too big to print");
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}
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}
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composedModel->printModelInformationToStream(std::cout);
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return composedModel;
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} else {
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// No composition was possible
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explorationTimer.start();
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// Find symmetries
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std::map<size_t, std::vector<std::vector<size_t>>> emptySymmetry;
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storm::storage::DFTIndependentSymmetries symmetries(emptySymmetry);
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if(symred) {
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auto colouring = dft.colourDFT();
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symmetries = dft.findSymmetries(colouring);
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STORM_LOG_INFO("Found " << symmetries.groups.size() << " symmetries.");
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STORM_LOG_TRACE("Symmetries: " << std::endl << symmetries);
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}
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// Build a single CTMC
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STORM_LOG_INFO("Building Model...");
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storm::builder::ExplicitDFTModelBuilderApprox<ValueType> builder(dft, symmetries, enableDC);
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typename storm::builder::ExplicitDFTModelBuilderApprox<ValueType>::LabelOptions labeloptions(properties);
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builder.buildModel(labeloptions, 0, 0.0);
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std::shared_ptr<storm::models::sparse::Model<ValueType>> model = builder.getModel();
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model->printModelInformationToStream(std::cout);
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explorationTimer.stop();
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STORM_LOG_THROW(model->isOfType(storm::models::ModelType::Ctmc), storm::exceptions::NotSupportedException, "Parallel composition only applicable for CTMCs");
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return model->template as<storm::models::sparse::Ctmc<ValueType>>();
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}
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}
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template<typename ValueType>
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typename DFTModelChecker<ValueType>::dft_results DFTModelChecker<ValueType>::checkDFT(storm::storage::DFT<ValueType> const& dft, property_vector const& properties, bool symred, bool enableDC, double approximationError) {
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explorationTimer.start();
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// Find symmetries
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std::map<size_t, std::vector<std::vector<size_t>>> emptySymmetry;
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storm::storage::DFTIndependentSymmetries symmetries(emptySymmetry);
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if(symred) {
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auto colouring = dft.colourDFT();
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symmetries = dft.findSymmetries(colouring);
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STORM_LOG_INFO("Found " << symmetries.groups.size() << " symmetries.");
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STORM_LOG_TRACE("Symmetries: " << std::endl << symmetries);
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}
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if (approximationError > 0.0) {
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// Comparator for checking the error of the approximation
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storm::utility::ConstantsComparator<ValueType> comparator;
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// Build approximate Markov Automata for lower and upper bound
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approximation_result approxResult = std::make_pair(storm::utility::zero<ValueType>(), storm::utility::zero<ValueType>());
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std::shared_ptr<storm::models::sparse::Model<ValueType>> model;
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std::vector<ValueType> newResult;
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storm::builder::ExplicitDFTModelBuilderApprox<ValueType> builder(dft, symmetries, enableDC);
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typename storm::builder::ExplicitDFTModelBuilderApprox<ValueType>::LabelOptions labeloptions(properties);
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// TODO Matthias: compute approximation for all properties simultaneously?
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std::shared_ptr<const storm::logic::Formula> property = properties[0];
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if (properties.size() > 1) {
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STORM_LOG_WARN("Computing approximation only for first property: " << *property);
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}
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bool probabilityFormula = property->isProbabilityOperatorFormula();
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STORM_LOG_ASSERT((property->isTimeOperatorFormula() && !probabilityFormula) || (!property->isTimeOperatorFormula() && probabilityFormula), "Probability formula not initialized correctly");
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size_t iteration = 0;
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do {
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// Iteratively build finer models
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if (iteration > 0) {
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explorationTimer.start();
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}
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STORM_LOG_INFO("Building model...");
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// TODO Matthias refine model using existing model and MC results
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builder.buildModel(labeloptions, iteration, approximationError);
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explorationTimer.stop();
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buildingTimer.start();
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// TODO Matthias: possible to do bisimulation on approximated model and not on concrete one?
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// Build model for lower bound
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STORM_LOG_INFO("Getting model for lower bound...");
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model = builder.getModelApproximation(probabilityFormula ? false : true);
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// We only output the info from the lower bound as the info for the upper bound is the same
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model->printModelInformationToStream(std::cout);
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buildingTimer.stop();
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// Check lower bounds
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newResult = checkModel(model, {property});
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STORM_LOG_ASSERT(newResult.size() == 1, "Wrong size for result vector.");
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STORM_LOG_ASSERT(iteration == 0 || !comparator.isLess(newResult[0], approxResult.first), "New under-approximation " << newResult[0] << " is smaller than old result " << approxResult.first);
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approxResult.first = newResult[0];
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// Build model for upper bound
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STORM_LOG_INFO("Getting model for upper bound...");
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buildingTimer.start();
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model = builder.getModelApproximation(probabilityFormula ? true : false);
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buildingTimer.stop();
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// Check upper bound
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newResult = checkModel(model, {properties});
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STORM_LOG_ASSERT(newResult.size() == 1, "Wrong size for result vector.");
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STORM_LOG_ASSERT(iteration == 0 || !comparator.isLess(approxResult.second, newResult[0]), "New over-approximation " << newResult[0] << " is greater than old result " << approxResult.second);
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approxResult.second = newResult[0];
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++iteration;
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STORM_LOG_INFO("Result after iteration " << iteration << ": (" << std::setprecision(10) << approxResult.first << ", " << approxResult.second << ")");
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totalTimer.stop();
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printTimings();
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totalTimer.start();
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STORM_LOG_THROW(!storm::utility::isInfinity<ValueType>(approxResult.first) && !storm::utility::isInfinity<ValueType>(approxResult.second), storm::exceptions::NotSupportedException, "Approximation does not work if result might be infinity.");
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} while (!isApproximationSufficient(approxResult.first, approxResult.second, approximationError, probabilityFormula));
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STORM_LOG_INFO("Finished approximation after " << iteration << " iteration" << (iteration > 1 ? "s." : "."));
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dft_results results;
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results.push_back(approxResult);
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return results;
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} else {
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// Build a single Markov Automaton
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STORM_LOG_INFO("Building Model...");
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std::shared_ptr<storm::models::sparse::Model<ValueType>> model;
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// TODO Matthias: use only one builder if everything works again
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if (storm::settings::getModule<storm::settings::modules::DFTSettings>().isApproximationErrorSet()) {
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storm::builder::ExplicitDFTModelBuilderApprox<ValueType> builder(dft, symmetries, enableDC);
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typename storm::builder::ExplicitDFTModelBuilderApprox<ValueType>::LabelOptions labeloptions(properties, storm::settings::getModule<storm::settings::modules::IOSettings>().isExportExplicitSet());
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builder.buildModel(labeloptions, 0, 0.0);
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model = builder.getModel();
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} else {
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storm::builder::ExplicitDFTModelBuilder<ValueType> builder(dft, symmetries, enableDC);
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typename storm::builder::ExplicitDFTModelBuilder<ValueType>::LabelOptions labeloptions;
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model = builder.buildModel(labeloptions);
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}
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model->printModelInformationToStream(std::cout);
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explorationTimer.stop();
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// Export the model if required
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if (storm::settings::getModule<storm::settings::modules::IOSettings>().isExportExplicitSet()) {
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std::ofstream stream;
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storm::utility::openFile(storm::settings::getModule<storm::settings::modules::IOSettings>().getExportExplicitFilename(), stream);
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std::vector<std::string> parameterNames;
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// TODO fill parameter names
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storm::exporter::explicitExportSparseModel(stream, model, parameterNames);
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storm::utility::closeFile(stream);
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}
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// Model checking
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std::vector<ValueType> resultsValue = checkModel(model, properties);
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dft_results results;
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for (ValueType result : resultsValue) {
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results.push_back(result);
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}
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return results;
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}
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}
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template<typename ValueType>
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std::vector<ValueType> DFTModelChecker<ValueType>::checkModel(std::shared_ptr<storm::models::sparse::Model<ValueType>>& model, property_vector const& properties) {
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// Bisimulation
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if (model->isOfType(storm::models::ModelType::Ctmc) && storm::settings::getModule<storm::settings::modules::GeneralSettings>().isBisimulationSet()) {
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bisimulationTimer.start();
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STORM_LOG_INFO("Bisimulation...");
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model = storm::performDeterministicSparseBisimulationMinimization<storm::models::sparse::Ctmc<ValueType>>(model->template as<storm::models::sparse::Ctmc<ValueType>>(), properties, storm::storage::BisimulationType::Weak)->template as<storm::models::sparse::Ctmc<ValueType>>();
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STORM_LOG_INFO("No. states (Bisimulation): " << model->getNumberOfStates());
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STORM_LOG_INFO("No. transitions (Bisimulation): " << model->getNumberOfTransitions());
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bisimulationTimer.stop();
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}
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// Check the model
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STORM_LOG_INFO("Model checking...");
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modelCheckingTimer.start();
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std::vector<ValueType> results;
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// Check each property
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storm::utility::Stopwatch singleModelCheckingTimer;
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for (auto property : properties) {
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singleModelCheckingTimer.reset();
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singleModelCheckingTimer.start();
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STORM_PRINT_AND_LOG("Model checking property " << *property << " ..." << std::endl);
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std::unique_ptr<storm::modelchecker::CheckResult> result(storm::verifySparseModel(model, property, true));
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STORM_LOG_ASSERT(result, "Result does not exist.");
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result->filter(storm::modelchecker::ExplicitQualitativeCheckResult(model->getInitialStates()));
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ValueType resultValue = result->asExplicitQuantitativeCheckResult<ValueType>().getValueMap().begin()->second;
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STORM_PRINT_AND_LOG("Result (initial states): " << resultValue << std::endl);
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results.push_back(resultValue);
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singleModelCheckingTimer.stop();
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STORM_PRINT_AND_LOG("Time for model checking: " << singleModelCheckingTimer << "." << std::endl);
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}
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modelCheckingTimer.stop();
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STORM_LOG_INFO("Model checking done.");
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return results;
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}
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|
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template<typename ValueType>
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bool DFTModelChecker<ValueType>::isApproximationSufficient(ValueType , ValueType , double , bool ) {
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|
STORM_LOG_THROW(false, storm::exceptions::NotImplementedException, "Approximation works only for double.");
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|
}
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|
|
|
template<>
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|
bool DFTModelChecker<double>::isApproximationSufficient(double lowerBound, double upperBound, double approximationError, bool relative) {
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|
STORM_LOG_THROW(!std::isnan(lowerBound) && !std::isnan(upperBound), storm::exceptions::NotSupportedException, "Approximation does not work if result is NaN.");
|
|
if (relative) {
|
|
return upperBound - lowerBound <= approximationError;
|
|
} else {
|
|
return upperBound - lowerBound <= approximationError * (lowerBound + upperBound) / 2;
|
|
}
|
|
}
|
|
|
|
template<typename ValueType>
|
|
void DFTModelChecker<ValueType>::printTimings(std::ostream& os) {
|
|
os << "Times:" << std::endl;
|
|
os << "Exploration:\t" << explorationTimer << "s" << std::endl;
|
|
os << "Building:\t" << buildingTimer << "s" << std::endl;
|
|
os << "Bisimulation:\t" << bisimulationTimer<< "s" << std::endl;
|
|
os << "Modelchecking:\t" << modelCheckingTimer << "s" << std::endl;
|
|
os << "Total:\t\t" << totalTimer << "s" << std::endl;
|
|
}
|
|
|
|
template<typename ValueType>
|
|
void DFTModelChecker<ValueType>::printResults(std::ostream& os) {
|
|
bool first = true;
|
|
os << "Result: [";
|
|
for (auto result : checkResults) {
|
|
if (!first) {
|
|
os << ", ";
|
|
}
|
|
if (this->approximationError > 0.0) {
|
|
approximation_result resultApprox = boost::get<approximation_result>(result);
|
|
os << "(" << resultApprox.first << ", " << resultApprox.second << ")";
|
|
} else {
|
|
os << boost::get<ValueType>(result);
|
|
}
|
|
if (first) {
|
|
first = false;
|
|
}
|
|
}
|
|
os << "]" << std::endl;
|
|
}
|
|
|
|
|
|
template class DFTModelChecker<double>;
|
|
|
|
#ifdef STORM_HAVE_CARL
|
|
template class DFTModelChecker<storm::RationalFunction>;
|
|
#endif
|
|
}
|
|
}
|