fixed fragment specification: total reward formulas should not be supported for hybrid/dd right now

src/storm/logic/FragmentSpecification.cpp

@@ -59,7 +59,6 @@ namespace storm {
             prctl.setCumulativeRewardFormulasAllowed(true);
             prctl.setInstantaneousFormulasAllowed(true);
             prctl.setReachabilityRewardFormulasAllowed(true);
-            prctl.setTotalRewardFormulasAllowed(true);
             prctl.setLongRunAverageOperatorsAllowed(true);
             prctl.setStepBoundedCumulativeRewardFormulasAllowed(true);
             prctl.setTimeBoundedCumulativeRewardFormulasAllowed(true);
@@ -82,7 +81,6 @@ namespace storm {
             csrl.setCumulativeRewardFormulasAllowed(true);
             csrl.setInstantaneousFormulasAllowed(true);
             csrl.setReachabilityRewardFormulasAllowed(true);
-            csrl.setTotalRewardFormulasAllowed(true);
             csrl.setLongRunAverageOperatorsAllowed(true);
             csrl.setTimeBoundedCumulativeRewardFormulasAllowed(true);
             

src/storm/modelchecker/prctl/SparseDtmcPrctlModelChecker.cpp

@@ -31,7 +31,7 @@ namespace storm {
         template<typename SparseDtmcModelType>
         bool SparseDtmcPrctlModelChecker<SparseDtmcModelType>::canHandle(CheckTask<storm::logic::Formula, ValueType> const& checkTask) const {
             storm::logic::Formula const& formula = checkTask.getFormula();
-            return formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setConditionalProbabilityFormulasAllowed(true).setConditionalRewardFormulasAllowed(true).setOnlyEventuallyFormuluasInConditionalFormulasAllowed(true).setRewardBoundedUntilFormulasAllowed(true).setRewardBoundedCumulativeRewardFormulasAllowed(true).setMultiDimensionalBoundedUntilFormulasAllowed(true).setMultiDimensionalCumulativeRewardFormulasAllowed(true));
+            return formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setConditionalProbabilityFormulasAllowed(true).setConditionalRewardFormulasAllowed(true).setTotalRewardFormulasAllowed(true).setOnlyEventuallyFormuluasInConditionalFormulasAllowed(true).setRewardBoundedUntilFormulasAllowed(true).setRewardBoundedCumulativeRewardFormulasAllowed(true).setMultiDimensionalBoundedUntilFormulasAllowed(true).setMultiDimensionalCumulativeRewardFormulasAllowed(true));
         }
         
         template<typename SparseDtmcModelType>

src/storm/modelchecker/prctl/SparseMdpPrctlModelChecker.cpp

@@ -38,7 +38,7 @@ namespace storm {
         template<typename SparseMdpModelType>
         bool SparseMdpPrctlModelChecker<SparseMdpModelType>::canHandle(CheckTask<storm::logic::Formula, ValueType> const& checkTask) const {
             storm::logic::Formula const& formula = checkTask.getFormula();
-            if (formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setConditionalProbabilityFormulasAllowed(true).setOnlyEventuallyFormuluasInConditionalFormulasAllowed(true).setRewardBoundedUntilFormulasAllowed(true).setRewardBoundedCumulativeRewardFormulasAllowed(true).setMultiDimensionalBoundedUntilFormulasAllowed(true).setMultiDimensionalCumulativeRewardFormulasAllowed(true))) {
+            if (formula.isInFragment(storm::logic::prctl().setLongRunAverageRewardFormulasAllowed(true).setLongRunAverageProbabilitiesAllowed(true).setConditionalProbabilityFormulasAllowed(true).setOnlyEventuallyFormuluasInConditionalFormulasAllowed(true).setTotalRewardFormulasAllowed(true).setRewardBoundedUntilFormulasAllowed(true).setRewardBoundedCumulativeRewardFormulasAllowed(true).setMultiDimensionalBoundedUntilFormulasAllowed(true).setMultiDimensionalCumulativeRewardFormulasAllowed(true))) {
                 return true;
             } else {
                 // Check whether we consider a multi-objective formula
@@ -172,6 +172,17 @@ namespace storm {
             }
             return result;
         }
+        
+        template<typename SparseMdpModelType>
+        std::unique_ptr<CheckResult> SparseMdpPrctlModelChecker<SparseMdpModelType>::computeTotalRewards(Environment const& env, storm::logic::RewardMeasureType, CheckTask<storm::logic::TotalRewardFormula, ValueType> const& checkTask) {
+            STORM_LOG_THROW(checkTask.isOptimizationDirectionSet(), storm::exceptions::InvalidPropertyException, "Formula needs to specify whether minimal or maximal values are to be computed on nondeterministic model.");
+            auto ret = storm::modelchecker::helper::SparseMdpPrctlHelper<ValueType>::computeTotalRewards(env, storm::solver::SolveGoal<ValueType>(this->getModel(), checkTask), this->getModel().getTransitionMatrix(), this->getModel().getBackwardTransitions(), checkTask.isRewardModelSet() ? this->getModel().getRewardModel(checkTask.getRewardModel()) : this->getModel().getRewardModel(""), checkTask.isQualitativeSet(), checkTask.isProduceSchedulersSet(), checkTask.getHint());
+            std::unique_ptr<CheckResult> result(new ExplicitQuantitativeCheckResult<ValueType>(std::move(ret.values)));
+            if (checkTask.isProduceSchedulersSet() && ret.scheduler) {
+                result->asExplicitQuantitativeCheckResult<ValueType>().setScheduler(std::move(ret.scheduler));
+            }
+            return result;
+        }
 
 		template<typename SparseMdpModelType>
 		std::unique_ptr<CheckResult> SparseMdpPrctlModelChecker<SparseMdpModelType>::computeLongRunAverageProbabilities(Environment const& env, CheckTask<storm::logic::StateFormula, ValueType> const& checkTask) {