diff --git a/include/rosa/agent/SignalState.hpp b/include/rosa/agent/SignalState.hpp
index a65ca9c..4b001a5 100644
--- a/include/rosa/agent/SignalState.hpp
+++ b/include/rosa/agent/SignalState.hpp
@@ -1,609 +1,606 @@
 //===-- rosa/agent/SignalState.hpp ------------------------------*- C++ -*-===//
 //
 //                                 The RoSA Framework
 //
 //===----------------------------------------------------------------------===//
 ///
 /// \file rosa/agent/SignalState.hpp
 ///
 /// \author Maximilian Götzinger (maximilian.goetzinger@tuwien.ac.at)
 ///
 /// \date 2019
 ///
 /// \brief Definition of *signal state* *functionality*.
 ///
 //===----------------------------------------------------------------------===//
 
 #ifndef ROSA_AGENT_SIGNALSTATE_HPP
 #define ROSA_AGENT_SIGNALSTATE_HPP
 
 #include "rosa/agent/DistanceMetrics.hpp"
 #include "rosa/agent/FunctionAbstractions.hpp"
 #include "rosa/agent/Functionality.h"
 #include "rosa/agent/History.hpp"
 #include "rosa/agent/State.hpp"
 
 #include "rosa/support/math.hpp"
 
 namespace rosa {
 namespace agent {
 
 /// Signal properties defining the properties of the signal which is monitored
 /// by \c rosa::agent::SignalStateDetector and is saved in \c
 /// rosa::agent::SignalStateInformation.
 enum SignalProperties : uint8_t {
   INPUT = 0, ///< The signal is an input signal
   OUTPUT = 1 ///< The signal is an output signal
 };
 
 /// TODO: write description
 template <typename CONFDATATYPE>
 struct SignalStateInformation : StateInformation<CONFDATATYPE> {
   // Make sure the actual type arguments are matching our expectations.
   STATIC_ASSERT((std::is_arithmetic<CONFDATATYPE>::value),
                 "confidence type is not to arithmetic");
 
   /// ConfidenceOfMatchingState is the confidence how good the new sample
   /// matches the state.
   CONFDATATYPE ConfidenceOfMatchingState;
 
   /// ConfidenceOfMatchingState is the confidence how bad the new sample
   /// matches the state.
   CONFDATATYPE ConfidenceOfMismatchingState;
 
   /// The SignalProperty saves whether the monitored signal is an input our
   /// output signal.
   SignalProperties SignalProperty;
 
   /// The SignalStateIsValid saves the number of samples which have been
   /// inserted into the state after entering it.
   uint32_t NumberOfInsertedSamplesAfterEntrance;
 
 public:
   SignalStateInformation(unsigned int SignalStateID,
                          SignalProperties _SignalProperty) {
     this->StateID = SignalStateID;
     this->SignalProperty = _SignalProperty;
     this->StateCondition = StateConditions::UNKNOWN;
     this->NumberOfInsertedSamplesAfterEntrance = 0;
     this->StateIsValid = false;
     this->StateJustGotValid = false;
     this->StateIsValidAfterReentrance = false;
     this->ConfidenceStateIsValid = 0;
     this->ConfidenceStateIsInvalid = 0;
     this->ConfidenceStateIsStable = 0;
     this->ConfidenceStateIsDrifting = 0;
   }
 
   SignalStateInformation() = default;
 };
 
 /// \tparam INDATATYPE type of input data, \tparam CONFDATATYPE type of
 /// data in that the confidence values are given, \tparam PROCDATATYPE type of
 /// the relative distance and the type of data in which DABs are saved.
 template <typename INDATATYPE, typename CONFDATATYPE, typename PROCDATATYPE>
 class SignalState : public Functionality {
 
   // Make sure the actual type arguments are matching our expectations.
   STATIC_ASSERT((std::is_arithmetic<INDATATYPE>::value),
                 "input data type not arithmetic");
   STATIC_ASSERT((std::is_arithmetic<CONFDATATYPE>::value),
                 "confidence data type is not to arithmetic");
   STATIC_ASSERT(
       (std::is_arithmetic<PROCDATATYPE>::value),
       "process data type (DAB and Relative Distance) is not to arithmetic");
 
 public:
   // The metric to calculate the distance between two points
   using DistanceMetricAbstraction =
       Abstraction<std::pair<INDATATYPE, INDATATYPE>, PROCDATATYPE> &;
   // For the convinience to write a shorter data type name
   using PartFuncReference = PartialFunction<INDATATYPE, CONFDATATYPE> &;
   // using PartFuncReference2 = ;
   using StepFuncReference = StepFunction<INDATATYPE, CONFDATATYPE> &;
 
 private:
   /// SignalStateInfo is a struct of SignalStateInformation that contains
   /// information about the current signal state.
   SignalStateInformation<CONFDATATYPE> SignalStateInfo;
 
   /// The metric to calculate the distance between two points
   DistanceMetricAbstraction DistanceMetric;
 
   /// The FuzzyFunctionSampleMatches is the fuzzy function that gives the
   /// confidence how good the new sample matches another sample in the sample
   /// history.
   PartFuncReference FuzzyFunctionSampleMatches;
 
   /// The FuzzyFunctionSampleMismatches is the fuzzy function that gives the
   /// confidence how bad the new sample matches another sample in the sample
   /// history.
   PartFuncReference FuzzyFunctionSampleMismatches;
 
   /// The FuzzyFunctionNumOfSamplesMatches is the fuzzy function that gives the
   /// confidence how many samples from the sampe history match the new sample.
   StepFuncReference FuzzyFunctionNumOfSamplesMatches;
 
   /// The FuzzyFunctionNumOfSamplesMismatches is the fuzzy function that gives
   /// the confidence how many samples from the sampe history mismatch the new
   /// sample.
   StepFuncReference FuzzyFunctionNumOfSamplesMismatches;
 
   /// The FuzzyFunctionSampleValid is the fuzzy function that gives the
   /// confidence how good one matches another sample in the sample
   /// history. This is done to evaluate whether a state is valid.
   PartFuncReference FuzzyFunctionSampleValid;
 
   /// The FuzzyFunctionSampleInvalid is the fuzzy function that gives the
   /// confidence how bad one sample matches another sample in the sample
   /// history. This is done to evaluate whether a state is invalid.
   PartFuncReference FuzzyFunctionSampleInvalid;
 
   /// The FuzzyFunctionNumOfSamplesValid is the fuzzy function that gives the
   /// confidence how many samples from the sample history match another sample.
   /// This is done to evaluate whether a state is valid.
   StepFuncReference FuzzyFunctionNumOfSamplesValid;
 
   /// The FuzzyFunctionNumOfSamplesInvalid is the fuzzy function that gives
   /// the confidence how many samples from the sample history mismatch another
   /// sample. This is done to evaluate whether a state is invalid.
   StepFuncReference FuzzyFunctionNumOfSamplesInvalid;
 
   /// The FuzzyFunctionSignalIsDrifting is the fuzzy function that gives the
   /// confidence how likely it is that the signal (resp. the state of a signal)
   /// is drifting.
   PartFuncReference FuzzyFunctionSignalIsDrifting;
 
   /// The FuzzyFunctionSignalIsStable is the fuzzy function that gives the
   /// confidence how likely it is that the signal (resp. the state of a signal)
   /// is stable (not drifting).
   PartFuncReference FuzzyFunctionSignalIsStable;
 
   /// TODO: description
   PartialFunction<uint32_t, float> &FuzzyFunctionSignalConditionLookBack;
   /// TODO: description
   PartialFunction<uint32_t, float> &FuzzyFunctionSignalConditionHistoryDesicion;
   /// TODO: description
   uint32_t DriftLookbackRange;
 
   /// SampleHistory is a history in that the last sample values are stored.
   DynamicLengthHistory<INDATATYPE, HistoryPolicy::FIFO> SampleHistory;
   /// DAB is a (usually) small history of the last sample values of which a
   /// average is calculated if the DAB is full.
   std::vector<DynamicLengthHistory<INDATATYPE, HistoryPolicy::SRWF>> DABs;
   /// DABHistory is a history in that the last DABs (to be exact, the averages
   /// of the last DABs) are stored.
   std::vector<DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::LIFO>> DABHistories;
 
   /// LowestConfidenceMatchingHistory is a history in that the lowest confidence
   /// for the current sample matches all history samples are saved.
   DynamicLengthHistory<INDATATYPE, HistoryPolicy::FIFO>
       LowestConfidenceMatchingHistory;
   /// HighestConfidenceMatchingHistory is a history in that the highest
   /// confidence for the current sample matches all history samples are saved.
   DynamicLengthHistory<INDATATYPE, HistoryPolicy::FIFO>
       HighestConfidenceMismatchingHistory;
 
   /// TempConfidenceMatching is the confidence how good a sample matches the
   /// state. However, the value of this variable is only needed temporarly.
   CONFDATATYPE TempConfidenceMatching = 0;
 
   /// TempConfidenceMatching is the confidence how bad a sample matches the
   /// state. However, the value of this variable is only needed temporarly.
   CONFDATATYPE TempConfidenceMismatching = 0;
 
 #pragma GCC diagnostic ignored "-Wunused-parameter"
 
 public:
   /// Creates an instance by setting all parameters
   /// \param SignalStateID The Id of the SignalStateinfo \c
   /// SignalStateInformation.
   ///
   /// \param DistanceMetric the distance metric to calculate the distance
   /// between two points
   ///
   /// \param FuzzyFunctionSampleMatches The FuzzyFunctionSampleMatches is the
   /// fuzzy function that gives the confidence how good the new sample matches
   /// another sample in the sample history.
   ///
   /// \param FuzzyFunctionSampleMismatches The FuzzyFunctionSampleMismatches is
   /// the fuzzy function that gives the confidence how bad the new sample
   /// matches another sample in the sample history.
   ///
   /// \param FuzzyFunctionNumOfSamplesMatches The
   /// FuzzyFunctionNumOfSamplesMatches is the fuzzy function that gives the
   /// confidence how many samples from the sampe history match the new sample.
   ///
   /// \param FuzzyFunctionNumOfSamplesMismatches The
   /// FuzzyFunctionNumOfSamplesMismatches is the fuzzy function that gives the
   /// confidence how many samples from the sampe history mismatch the new
   /// sample.
   ///
   /// \param FuzzyFunctionSignalIsDrifting The FuzzyFunctionSignalIsDrifting is
   /// the fuzzy function that gives the confidence how likely it is that the
   /// signal (resp. the state of a signal) is drifting.
   ///
   /// \param FuzzyFunctionSignalIsStable The FuzzyFunctionSignalIsStable is the
   /// fuzzy function that gives the confidence how likely it is that the signal
   /// (resp. the state of a signal) is stable (not drifting).
   ///
   /// \param SampleHistorySize Size of the Sample History \c
   /// DynamicLengthHistory . SampleHistory is a history in that the last sample
   /// values are stored.
   ///
   /// \param DABSize Size of DAB \c DynamicLengthHistory . DAB is a (usually)
   /// small history of the last sample values of which a average is calculated
   /// if the DAB is full.
   ///
   /// \param DABHistorySize Size of the DABHistory \c DynamicLengthHistory .
   /// DABHistory is a history in that the last DABs (to be exact, the averages
   /// of the last DABs) are stored.
   ///
   SignalState(
       uint32_t SignalStateID, SignalProperties SignalProperty,
       uint32_t SampleHistorySize, uint32_t DABSize, uint32_t DABHistorySize,
       DistanceMetricAbstraction DistanceMetric,
       PartFuncReference FuzzyFunctionSampleMatches,
       PartFuncReference FuzzyFunctionSampleMismatches,
       StepFuncReference FuzzyFunctionNumOfSamplesMatches,
       StepFuncReference FuzzyFunctionNumOfSamplesMismatches,
       PartFuncReference FuzzyFunctionSampleValid,
       PartFuncReference FuzzyFunctionSampleInvalid,
       StepFuncReference FuzzyFunctionNumOfSamplesValid,
       StepFuncReference FuzzyFunctionNumOfSamplesInvalid,
       // SAVE CHANGES
       PartFuncReference FuzzyFunctionSignalIsDrifting,
       PartFuncReference FuzzyFunctionSignalIsStable,
       PartialFunction<uint32_t, float> &FuzzyFunctionSignalConditionLookBack,
       // - SAVE CHANGES
       PartialFunction<uint32_t, float>
           &FuzzyFunctionSignalConditionHistoryDesicion,
       uint32_t DriftLookbackRange) noexcept
       : SignalStateInfo{SignalStateID, SignalProperty},
         DistanceMetric(DistanceMetric),
         FuzzyFunctionSampleMatches(FuzzyFunctionSampleMatches),
         FuzzyFunctionSampleMismatches(FuzzyFunctionSampleMismatches),
         FuzzyFunctionNumOfSamplesMatches(FuzzyFunctionNumOfSamplesMatches),
         FuzzyFunctionNumOfSamplesMismatches(
             FuzzyFunctionNumOfSamplesMismatches),
         FuzzyFunctionSampleValid(FuzzyFunctionSampleValid),
         FuzzyFunctionSampleInvalid(FuzzyFunctionSampleInvalid),
         FuzzyFunctionNumOfSamplesValid(FuzzyFunctionNumOfSamplesValid),
         FuzzyFunctionNumOfSamplesInvalid(FuzzyFunctionNumOfSamplesInvalid),
         FuzzyFunctionSignalIsDrifting(FuzzyFunctionSignalIsDrifting),
         FuzzyFunctionSignalIsStable(FuzzyFunctionSignalIsStable),
         // SAVE CHANGES
         FuzzyFunctionSignalConditionLookBack(
             FuzzyFunctionSignalConditionLookBack),
         FuzzyFunctionSignalConditionHistoryDesicion(
             FuzzyFunctionSignalConditionHistoryDesicion),
         DriftLookbackRange(DriftLookbackRange),
         // - SAVE CHANGES
         SampleHistory(SampleHistorySize), 
         LowestConfidenceMatchingHistory(SampleHistorySize),
         HighestConfidenceMismatchingHistory(SampleHistorySize) {
           //DAB(DABSize);
 
           DABs.push_back(3);
           DABHistories.push_back(DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::LIFO>(DABHistorySize));
           
           DABs.push_back(DynamicLengthHistory<INDATATYPE, HistoryPolicy::SRWF>(5));
           DABHistories.push_back(DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::LIFO>(DABHistorySize));
           
           DABs.push_back(DynamicLengthHistory<INDATATYPE, HistoryPolicy::SRWF>(10));
           DABHistories.push_back(DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::LIFO>(DABHistorySize));
           
           DABs.push_back(DynamicLengthHistory<INDATATYPE, HistoryPolicy::SRWF>(20));
           DABHistories.push_back(DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::LIFO>(DABHistorySize));
 
         }
 
   /// Destroys \p this object.
   ~SignalState(void) = default;
 
   void leaveSignalState(void) noexcept {
     for(auto& dab: DABs) {
       dab.clear();
     }
     SignalStateInfo.NumberOfInsertedSamplesAfterEntrance = 0;
     SignalStateInfo.StateIsValidAfterReentrance = false;
   }
 
   SignalStateInformation<CONFDATATYPE>
   insertSample(INDATATYPE Sample) noexcept {
 
     SignalStateInfo.NumberOfInsertedSamplesAfterEntrance++;
 
     validateSignalState(Sample);
 
     SampleHistory.addEntry(Sample);
 
     unsigned int index = 0;
     for(auto& DAB: DABs) {
       DAB.addEntry(Sample);
       if (DAB.full()) {
 
         PROCDATATYPE AvgOfDAB = DAB.template median<PROCDATATYPE>();
 
         DABHistories[index].addEntry(AvgOfDAB);
         DAB.clear();
       }
       index++;
     }
 
     FuzzyFunctionNumOfSamplesMatches.setRightLimit(
         static_cast<INDATATYPE>(SampleHistory.numberOfEntries()));
     FuzzyFunctionNumOfSamplesMismatches.setRightLimit(
         static_cast<INDATATYPE>(SampleHistory.numberOfEntries()));
 
     checkSignalStability();
 
     SignalStateInfo.ConfidenceOfMatchingState = TempConfidenceMatching;
     SignalStateInfo.ConfidenceOfMismatchingState = TempConfidenceMismatching;
 
     return SignalStateInfo;
   }
 
   /// Gives the confidence how likely the new sample matches the signal state.
   ///
   /// \param Sample is the actual sample of the observed signal.
   ///
   /// \return the confidence of the new sample is matching the signal state.
   CONFDATATYPE
   confidenceSampleMatchesSignalState(INDATATYPE Sample) noexcept {
 
     CONFDATATYPE ConfidenceOfBestCase = 0;
 
     DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::FIFO>
         RelativeDistanceHistory(SampleHistory.maxLength());
 
     // Calculate distances to all history samples.
     for (auto &HistorySample : SampleHistory) {
       PROCDATATYPE RelativeDistance =
           DistanceMetric(std::make_pair(Sample, HistorySample));
       RelativeDistanceHistory.addEntry(RelativeDistance);
     }
 
     // Sort all calculated distances so that the lowest distance (will get the
     // highest confidence) is at the beginning.
     RelativeDistanceHistory.sortAscending();
 
     CONFDATATYPE ConfidenceOfWorstFittingSample = 1;
 
     // Case 1 means that one (the best fitting) sample of the history is
     // compared with the new sample. Case 2 means the two best history samples
     // are compared with the new sample. And so on.
     // TODO (future): to accelerate . don't start with 1 start with some higher
     // number because a low number (i guess lower than 5) will definetely lead
     // to a low confidence. except the history is not full.
 
     // Case 1 means that one (the best fitting) sample of the history is
     // compared with the new sample. Case 2 means the two best history samples
     // are compared with the new sample. And so on.
     for (uint32_t Case = 0; Case < RelativeDistanceHistory.numberOfEntries();
          Case++) {
 
       CONFDATATYPE ConfidenceFromRelativeDistance;
 
       if (std::isinf(RelativeDistanceHistory[Case])) {
         // TODO (future): if fuzzy is defined in a way that infinity is not 0 it
         // would be a problem.
         ConfidenceFromRelativeDistance = 0;
       } else {
         ConfidenceFromRelativeDistance =
             FuzzyFunctionSampleMatches(RelativeDistanceHistory[Case]);
       }
       ConfidenceOfWorstFittingSample = fuzzyAND(ConfidenceOfWorstFittingSample,
                                                 ConfidenceFromRelativeDistance);
 
       ConfidenceOfBestCase =
           fuzzyOR(ConfidenceOfBestCase,
                   fuzzyAND(ConfidenceOfWorstFittingSample,
                            FuzzyFunctionNumOfSamplesMatches(
                                static_cast<CONFDATATYPE>(Case) + 1)));
     }
 
     TempConfidenceMatching = ConfidenceOfBestCase;
 
     return ConfidenceOfBestCase;
   }
 
   /// Gives the confidence how likely the new sample mismatches the signal
   /// state.
   ///
   /// \param Sample is the actual sample of the observed signal.
   ///
   /// \return the confidence of the new sample is mismatching the signal state.
   CONFDATATYPE
   confidenceSampleMismatchesSignalState(INDATATYPE Sample) noexcept {
 
     float ConfidenceOfWorstCase = 1;
 
     DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::FIFO>
         RelativeDistanceHistory(SampleHistory.maxLength());
 
     // Calculate distances to all history samples.
     for (auto &HistorySample : SampleHistory) {
       RelativeDistanceHistory.addEntry(
           DistanceMetric(std::make_pair(Sample, HistorySample)));
     }
 
     // Sort all calculated distances so that the highest distance (will get the
     // lowest confidence) is at the beginning.
     RelativeDistanceHistory.sortDescending();
 
     CONFDATATYPE ConfidenceOfBestFittingSample = 0;
 
     // TODO (future): to accelerate -> don't go until end. Confidences will only
     // get higher. See comment in "CONFDATATYPE
     // confidenceSampleMatchesSignalState(INDATATYPE Sample)".
 
     // Case 1 means that one (the worst fitting) sample of the history is
     // compared with the new sample. Case 2 means the two worst history samples
     // are compared with the new sample. And so on.
     for (uint32_t Case = 0; Case < RelativeDistanceHistory.numberOfEntries();
          Case++) {
 
       CONFDATATYPE ConfidenceFromRelativeDistance;
 
       if (std::isinf(RelativeDistanceHistory[Case])) {
         ConfidenceFromRelativeDistance = 1;
       } else {
         ConfidenceFromRelativeDistance =
             FuzzyFunctionSampleMismatches(RelativeDistanceHistory[Case]);
       }
 
       ConfidenceOfBestFittingSample = fuzzyOR(ConfidenceOfBestFittingSample,
                                               ConfidenceFromRelativeDistance);
 
       ConfidenceOfWorstCase =
           fuzzyAND(ConfidenceOfWorstCase,
                    fuzzyOR(ConfidenceOfBestFittingSample,
                            FuzzyFunctionNumOfSamplesMismatches(
                                static_cast<CONFDATATYPE>(Case) + 1)));
     }
 
     TempConfidenceMismatching = ConfidenceOfWorstCase;
 
     return ConfidenceOfWorstCase;
   }
 
   /// Gives information about the current signal state.
   ///
   /// \return a struct SignalStateInformation that contains information about
   /// the current signal state.
   SignalStateInformation<CONFDATATYPE> signalStateInformation(void) noexcept {
     return SignalStateInfo;
   }
 
 private:
   void validateSignalState(INDATATYPE Sample) {
     // TODO (future): WorstConfidenceDistance and BestConfidenceDistance could
     // be set already in "CONFDATATYPE
     // confidenceSampleMatchesSignalState(INDATATYPE Sample)" and "CONFDATATYPE
     // confidenceSampleMismatchesSignalState(INDATATYPE Sample)" when the new
     // sample is compared to all history samples. This would save a lot time
     // because the comparisons are done only once. However, it has to be asured
     // that the these two functions are called before the insertation, and the
     // FuzzyFunctions for validation and matching have to be the same!
     CONFDATATYPE LowestConfidenceMatching = 1;
     CONFDATATYPE HighestConfidenceMismatching = 0;
 
     for (auto &HistorySample : SampleHistory) {
       // TODO (future): think about using different fuzzy functions for
       // validation and matching.
       LowestConfidenceMatching =
           fuzzyAND(LowestConfidenceMatching,
                    FuzzyFunctionSampleMatches(
                        DistanceMetric(std::make_pair(Sample, HistorySample))));
 
       HighestConfidenceMismatching =
           fuzzyOR(HighestConfidenceMismatching,
                   FuzzyFunctionSampleMismatches(
                       DistanceMetric(std::make_pair(Sample, HistorySample))));
     }
     LowestConfidenceMatchingHistory.addEntry(LowestConfidenceMatching);
     HighestConfidenceMismatchingHistory.addEntry(HighestConfidenceMismatching);
 
     LowestConfidenceMatching = LowestConfidenceMatchingHistory.lowestEntry();
     HighestConfidenceMismatching =
         HighestConfidenceMismatchingHistory.highestEntry();
 
     SignalStateInfo.ConfidenceStateIsValid =
         fuzzyAND(LowestConfidenceMatching,
                  FuzzyFunctionNumOfSamplesValid(static_cast<INDATATYPE>(
                      SignalStateInfo.NumberOfInsertedSamplesAfterEntrance)));
 
     SignalStateInfo.ConfidenceStateIsInvalid =
         fuzzyOR(HighestConfidenceMismatching,
                 FuzzyFunctionNumOfSamplesInvalid(static_cast<INDATATYPE>(
                     SignalStateInfo.NumberOfInsertedSamplesAfterEntrance)));
 
     if (SignalStateInfo.ConfidenceStateIsValid >
         SignalStateInfo.ConfidenceStateIsInvalid) {
 
       if (SignalStateInfo.StateIsValid) {
         SignalStateInfo.StateJustGotValid = false;
       } else {
         SignalStateInfo.StateJustGotValid = true;
       }
 
       SignalStateInfo.StateIsValid = true;
       SignalStateInfo.StateIsValidAfterReentrance = true;
     }
   }
 
   void checkSignalStability(void) {
 
     SignalStateInfo.ConfidenceStateIsStable = 0;
-    SignalStateInfo.ConfidenceStateIsDrifting = 0;
+    SignalStateInfo.ConfidenceStateIsDriftingDown = 0;
+    SignalStateInfo.ConfidenceStateIsDriftingUp = 0;
 
-    bool DriftDirectionIsUp = true;
+    unsigned int Divider = 0; 
 
     for(auto& DABHistory: DABHistories) {
 
       if (DABHistory.numberOfEntries() >= 2) {
-
         // SAVE CHANGES
         INDATATYPE CurrentDAB = DABHistory[DABHistory.numberOfEntries() - 1];
         INDATATYPE DAB2Compare;
 
-        // ########### TODO HERE: calculating up_down
-
-        uint32_t DriftDnCounter = 0;
-        uint32_t DriftUpCounter = 0;
-
-        // EXPERIMENTING
         for (unsigned int t = 1;
             t <= DriftLookbackRange && t < DABHistory.numberOfEntries(); t++) {
 
           DAB2Compare = DABHistory[DABHistory.numberOfEntries() - (t + 1)];
           INDATATYPE dist = DistanceMetric(std::make_pair(CurrentDAB, DAB2Compare));
 
           // AVG
           SignalStateInfo.ConfidenceStateIsStable +=
               FuzzyFunctionSignalIsStable(dist);
-          SignalStateInfo.ConfidenceStateIsDrifting +=
-              FuzzyFunctionSignalIsDrifting(dist);
-
           if (CurrentDAB > DAB2Compare)
-            DriftUpCounter++;
+            SignalStateInfo.ConfidenceStateIsDriftingUp +=
+            FuzzyFunctionSignalIsDrifting(dist);
           else if (CurrentDAB < DAB2Compare)
-            DriftDnCounter++;
+            SignalStateInfo.ConfidenceStateIsDriftingDown +=
+            FuzzyFunctionSignalIsDrifting(dist);
         }
 
-        CONFDATATYPE Divider;         
+                
         if(DriftLookbackRange<=DABHistory.numberOfEntries())
-          Divider = DriftLookbackRange;
+          Divider += DriftLookbackRange;
         else
-          Divider = DABHistory.numberOfEntries();
-                
-        SignalStateInfo.ConfidenceStateIsStable /= Divider;
-        SignalStateInfo.ConfidenceStateIsDrifting /= Divider;
-
-        // TODO: change something because it is biased if the are equal
-        DriftDirectionIsUp = DriftUpCounter > DriftDnCounter;
+          Divider += DABHistory.numberOfEntries();
       }
     }
 
+    SignalStateInfo.ConfidenceStateIsStable /= Divider;
+    SignalStateInfo.ConfidenceStateIsDriftingDown /= Divider;
+    SignalStateInfo.ConfidenceStateIsDriftingUp /= Divider; 
+
+    if (SignalStateInfo.ConfidenceStateIsDriftingDown >
+      SignalStateInfo.ConfidenceStateIsDriftingUp) {
+      SignalStateInfo.ConfidenceStateIsDrifting = SignalStateInfo.ConfidenceStateIsDriftingDown;
+      SignalStateInfo.StateCondition = StateConditions::DRIFTING_DN;
+      }
+    else if (SignalStateInfo.ConfidenceStateIsDriftingUp >
+      SignalStateInfo.ConfidenceStateIsDriftingDown) {
+      SignalStateInfo.ConfidenceStateIsDrifting = SignalStateInfo.ConfidenceStateIsDriftingUp;
+      SignalStateInfo.StateCondition = StateConditions::DRIFTING_UP;
+      }
+    else
+      SignalStateInfo.StateCondition = StateConditions::STABLE;
+
     if (SignalStateInfo.ConfidenceStateIsStable >
         SignalStateInfo.ConfidenceStateIsDrifting) {
       SignalStateInfo.StateCondition = StateConditions::STABLE;
-    } else if (SignalStateInfo.ConfidenceStateIsStable <
-               SignalStateInfo.ConfidenceStateIsDrifting) {
-
-      if (DriftDirectionIsUp) {
-        SignalStateInfo.StateCondition = StateConditions::DRIFTING_UP;
-      } else {
-        SignalStateInfo.StateCondition = StateConditions::DRIFTING_DN;
-      }
-    } else {
+    } 
+    else if (SignalStateInfo.ConfidenceStateIsStable ==
+        SignalStateInfo.ConfidenceStateIsDrifting)
       SignalStateInfo.StateCondition = StateConditions::UNKNOWN;
-    }
   }
 }; // namespace agent
 
 } // namespace agent
 } // End namespace rosa
 
 #endif // ROSA_AGENT_SIGNALSTATE_HPP
diff --git a/include/rosa/agent/State.hpp b/include/rosa/agent/State.hpp
index ca267b5..6dc2481 100644
--- a/include/rosa/agent/State.hpp
+++ b/include/rosa/agent/State.hpp
@@ -1,97 +1,99 @@
 //===-- rosa/agent/State.hpp ------------------------------------*- C++ -*-===//
 //
 //                                 The RoSA Framework
 //
 // Distributed under the terms and conditions of the Boost Software License 1.0.
 // See accompanying file LICENSE.
 //
 // If you did not receive a copy of the license file, see
 // http://www.boost.org/LICENSE_1_0.txt.
 //
 //===----------------------------------------------------------------------===//
 ///
 /// \file rosa/agent/State.hpp
 ///
 /// \author Maximilian Götzinger (maximilian.goetzinger@tuwien.ac.at)
 ///
 /// \date 2019
 ///
 /// \brief Definition of *state* *functionality*.
 ///
 //===----------------------------------------------------------------------===//
 
 #ifndef ROSA_AGENT_STATE_HPP
 #define ROSA_AGENT_STATE_HPP
 
 #include "rosa/agent/Functionality.h"
 //#include "rosa/agent/FunctionAbstractions.hpp"
 //#include "rosa/agent/History.hpp"
 
 #include "rosa/support/debug.hpp"
 
 #include <stdint.h>
 
 //#include <vector>
 
 namespace rosa {
 namespace agent {
 
 /// State conditions defining how the condition of a \c rosa::agent::State is
 /// saved in \c rosa::agent::StateInformation.
 enum StateConditions : uint8_t {
 
   UNKNOWN = '0',       ///< The state is unknown
   STABLE = '1',        ///< The state is stable
   DRIFTING_DN = '2',   ///< The state is drifting down
   DRIFTING = '3',      ///< The state is drifting down or up
   DRIFTING_UP = '4',   ///< The state is drifting up
   MALFUNCTIONING = '5' ///< Malfunction
 
 };
 
 template <typename CONFDATATYPE> struct StateInformation {
   // Make sure the actual type arguments are matching our expectations.
   STATIC_ASSERT((std::is_arithmetic<CONFDATATYPE>::value),
                 "confidence type is not to arithmetic");
   /// The StateID stores the ID of the state.
   unsigned int StateID;
   /// The StateCondition shows the condition of a state (stable, drifting, or
   /// unknown)
   StateConditions StateCondition;
   /// The StateIsValid shows whether a state is valid or invalid. In this
   /// context, valid means that enough samples which are in close proximitry
   /// have been inserted into the state.
   bool StateIsValid;
   /// The StateJustGotValid shows whether a state got valid (toggled from
   /// invalid to valid) during the current inserted sample.
   bool StateJustGotValid;
   /// The StateIsValidAfterReentrance shows whether a state is valid after the
   /// variable changed back to it again.
   bool StateIsValidAfterReentrance;
 
   /// TODO: describe
   CONFDATATYPE ConfidenceStateIsValid;
   CONFDATATYPE ConfidenceStateIsInvalid;
 
   CONFDATATYPE ConfidenceStateIsStable;
   CONFDATATYPE ConfidenceStateIsDrifting;
+  CONFDATATYPE ConfidenceStateIsDriftingUp;
+  CONFDATATYPE ConfidenceStateIsDriftingDown;
 };
 
 template <typename INDATATYPE, typename CONFDATATYPE, typename PROCDATATYPE>
 class State : public Functionality {
 
   // Make sure the actual type arguments are matching our expectations.
   STATIC_ASSERT((std::is_arithmetic<INDATATYPE>::value),
                 "input data type not arithmetic");
   STATIC_ASSERT((std::is_arithmetic<CONFDATATYPE>::value),
                 "confidence abstraction type is not to arithmetic");
   STATIC_ASSERT((std::is_arithmetic<PROCDATATYPE>::value),
                 "process type is not to arithmetic");
 
 protected:
 };
 
 } // End namespace agent
 } // End namespace rosa
 
 #endif // ROSA_AGENT_SIGNALSTATEDETECTOR_HPP