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	diff --git a/apps/ccam/ccam.cpp b/apps/ccam/ccam.cpp
	index 7ae44de..76fc676 100644
	--- a/apps/ccam/ccam.cpp
	+++ b/apps/ccam/ccam.cpp
	@@ -1,58 +1,116 @@
	//===-- apps/ccam/ccam.cpp --------------------------------------- C++ --===//
	//
	// The RoSA Framework -- Application CCAM
	//
	//===----------------------------------------------------------------------===//
	///
	/// \file apps/ccam/ccam.cpp
	///
	/// \author Maximilian Goetzinger (maximilian.goetzinger@tuwien.ac.at)
	///
	/// \date 2019
	///
	/// \brief The application CCAM implements the case study from the paper:
	/// M. Goetzinger, N. TaheriNejad, H. A. Kholerdi, A. Jantsch, E. Willegger,
	/// T. Glatzl, A.M. Rahmani, T.Sauter, P. Liljeberg: Model - Free Condition
	/// Monitoring with Confidence
	//===----------------------------------------------------------------------===//

	#include "rosa/agent/FunctionAbstractions.hpp"
	#include "rosa/agent/SignalStateDetector.hpp"

	#include <iostream>

	+using namespace rosa::agent;
	+
	int main(void) {

	// Just some tests :D
	std::vector vec = {7, 3, 5, 1, 9};

	std::sort(vec.rbegin(), vec.rend());
	// std::reverse(vec.begin(), vec.end());

	for (auto it = vec.cbegin(); it != vec.cend(); ++it) {
	std::cout << *it << ' ';
	}

	- std::shared_ptr<rosa::agent::PartialFunction<float, float>> PartFunc(
	- new rosa::agent::PartialFunction<float, float>(
	+ std::shared_ptr<PartialFunction<float, float>> PartFunc(
	+ new PartialFunction<float, float>(
	{
	{{0.f, 3.f},
	- std::make_shared<rosa::agent::LinearFunction<float, float>>(
	- 0.f, 1.f / 3)},
	+ std::make_shared<LinearFunction<float, float>>(0.f, 1.f / 3)},
	{{3.f, 6.f},
	- std::make_shared<rosa::agent::LinearFunction<float, float>>(
	- 1.f, 0.f)},
	+ std::make_shared<LinearFunction<float, float>>(1.f, 0.f)},
	{{6.f, 9.f},
	- std::make_shared<rosa::agent::LinearFunction<float, float>>(
	- 3.f, -1.f / 3)},
	+ std::make_shared<LinearFunction<float, float>>(3.f, -1.f / 3)},
	},
	0));

	- std::shared_ptr<rosa::agent::StepFunction<float, float>> StepFunc(
	- new rosa::agent::StepFunction<float, float>(1 / 10));
	+ std::shared_ptr<StepFunction<float, float>> StepFunc(
	+ new StepFunction<float, float>(1 / 10));
	+
	+ SignalStateDetector<float, float, float, HistoryPolicy::SRWF> TestSigSD(
	+ 10000, PartFunc, PartFunc, StepFunc, StepFunc, PartFunc, PartFunc, 10, 5,
	+ 1000);

	- rosa::agent::SignalStateDetector<float, float> TestSigSD(
	- PartFunc, PartFunc, StepFunc, StepFunc, PartFunc, PartFunc, 10, 5, 1000);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(50.3f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);
	+ TestSigSD.detectSignalState(100.6f);

	return 0;
	}
	diff --git a/include/rosa/agent/FunctionAbstractions.hpp b/include/rosa/agent/FunctionAbstractions.hpp
	index bebfd77..a0f8585 100644
	--- a/include/rosa/agent/FunctionAbstractions.hpp
	+++ b/include/rosa/agent/FunctionAbstractions.hpp
	@@ -1,351 +1,354 @@
	//===-- rosa/agent/FunctionAbstractions.hpp ---------------------- C++ --===//
	//
	// The RoSA Framework
	//
	//===----------------------------------------------------------------------===//
	///
	/// \file rosa/agent/FunctionAbstractions.hpp
	///
	/// \author Benedikt Tutzer (benedikt.tutzer@tuwien.ac.at)
	///
	/// \date 2019
	///
	/// \brief Definition of FunctionAbstractions functionality.
	///
	//===----------------------------------------------------------------------===//

	#ifndef ROSA_AGENT_FUNCTIONABSTRACTIONS_HPP
	#define ROSA_AGENT_FUNCTIONABSTRACTIONS_HPP

	#include "rosa/agent/Abstraction.hpp"
	#include "rosa/agent/Functionality.h"

	#include "rosa/support/debug.hpp"

	#include <algorithm>
	#include <cmath>
	#include <memory>
	#include <vector>

	namespace rosa {
	namespace agent {

	/// Implements \c rosa::agent::Abstraction as a linear function,
	/// y = Coefficient * X + Intercept.
	///
	/// \note This implementation is supposed to be used to represent a linear
	/// function from an arithmetic domain to an arithmetic range. This is enforced
	/// statically.
	///
	/// \tparam D type of the functions domain
	/// \tparam R type of the functions range
	template <typename D, typename R>
	class LinearFunction : public Abstraction<D, R> {
	// Make sure the actual type arguments are matching our expectations.
	STATIC_ASSERT((std::is_arithmetic<D>::value),
	"LinearFunction not arithmetic T");
	STATIC_ASSERT((std::is_arithmetic<R>::value),
	"LinearFunction not to arithmetic");

	protected:
	/// The Intercept of the linear function
	const D Intercept;
	/// The Coefficient of the linear function
	const D Coefficient;

	public:
	/// Creates an instance given the intercept and the coefficient of a linear
	/// function.
	///
	/// \param Intercept the intercept of the linear function
	/// \param Coefficient the coefficient of the linear function
	LinearFunction(D Intercept, D Coefficient) noexcept
	: Abstraction<D, R>(Intercept), Intercept(Intercept),
	Coefficient(Coefficient) {}

	/// Creates an instance given the two points on a linear function.
	///
	/// \param x1 The x-value of the first point
	/// \param y1 The x-value of the first point
	/// \param x2 The y-value of the second point
	/// \param y2 The y-value of the second point
	LinearFunction(D x1, R y1, D x2, R y2) noexcept
	: Abstraction<D, R>(y1 - x1 * (y1 - y2) / (x1 - x2),
	(y1 - y2) / (x1 - x2)) {}

	/// Creates an instance given the two points on a linear function.
	///
	/// \param p1 The coordinates of the first point
	/// \param p2 The coordinates of the second point
	LinearFunction(std::pair<D, R> p1, std::pair<D, R> p2) noexcept
	: LinearFunction<D, R>(p1.first, p1.second, p2.first, p2.second) {}

	/// Destroys \p this object.
	~LinearFunction(void) = default;

	/// Checks wether the Abstraction evaluates to default at the given position
	/// As LinearFunctions can be evaluated everythwere, this is always false
	///
	/// \param V the value at which to check if the function falls back to it's
	/// default value.
	///
	/// \return false
	bool isDefaultAt(const D &V) const noexcept override {
	(void)V;
	return false;
	}

	/// Getter for member variable Intercept
	///
	/// \return Intercept
	D getIntercept() const { return Intercept; }

	/// Setter for member variable Intercept
	///
	/// \param Intercept the new Intercept
	void setIntercept(const D &Intercept) { this->Intercept = Intercept; }

	/// Getter for member variable Coefficient
	///
	/// \return Coefficient
	D getCoefficient() const { return Coefficient; }

	/// Setter for member variable Coefficient
	///
	/// \param Coefficient the new Intercept
	void setCoefficient(const D &Coefficient) { this->Coefficient = Coefficient; }

	/// Set Intercept and Coefficient from two points on the linear function
	///
	/// \param x1 The x-value of the first point
	/// \param y1 The x-value of the first point
	/// \param x2 The y-value of the second point
	/// \param y2 The y-value of the second point
	void setFromPoints(D x1, R y1, D x2, R y2) {
	Coefficient = (y1 - y2) / (x1 - x2);
	Intercept = y1 - Coefficient * x1;
	}

	/// Set Intercept and Coefficient from two points on the linear function
	///
	/// \param p1 The coordinates of the first point
	/// \param p2 The coordinates of the second point
	inline void setFromPoints(std::pair<D, R> p1, std::pair<D, R> p2) {
	setFromPoints(p1.first, p1.second, p2.first, p2.second);
	}

	/// Evaluates the linear function
	///
	/// \param X the value at which to evaluate the function
	///
	/// \return Coefficient*X + Intercept
	virtual R operator()(const D &X) const noexcept override {
	return Intercept + X * Coefficient;
	}
	};

	/// Implements \c rosa::agent::Abstraction as a sine function,
	/// y = Amplitude * sin(Frequency * X + Phase) + Average.
	///
	/// \note This implementation is supposed to be used to represent a sine
	/// function from an arithmetic domain to an arithmetic range. This is enforced
	/// statically.
	///
	/// \tparam D type of the functions domain
	/// \tparam R type of the functions range
	template <typename D, typename R>
	class SineFunction : public Abstraction<D, R> {
	// Make sure the actual type arguments are matching our expectations.
	STATIC_ASSERT((std::is_arithmetic<D>::value),
	"SineFunction not arithmetic T");
	STATIC_ASSERT((std::is_arithmetic<R>::value),
	"SineFunction not to arithmetic");

	protected:
	/// The frequency of the sine wave
	const D Frequency;
	/// The Ampiltude of the sine wave
	const D Amplitude;
	/// The Phase-shift of the sine wave
	const D Phase;
	/// The y-shift of the sine wave
	const D Average;

	public:
	/// Creates an instance.
	///
	/// \param Frequency the frequency of the sine wave
	/// \param Amplitude the amplitude of the sine wave
	/// \param Phase the phase of the sine wave
	/// \param Average the average of the sine wave
	SineFunction(D Frequency, D Amplitude, D Phase, D Average) noexcept
	: Abstraction<D, R>(Average), Frequency(Frequency), Amplitude(Amplitude),
	Phase(Phase), Average(Average) {}

	/// Destroys \p this object.
	~SineFunction(void) = default;

	/// Checks wether the Abstraction evaluates to default at the given position
	/// As SineFunctions can be evaluated everythwere, this is always false
	///
	/// \param V the value at which to check if the function falls back to it's
	/// default value.
	///
	/// \return false
	bool isDefaultAt(const D &V) const noexcept override {
	(void)V;
	return false;
	}

	/// Evaluates the sine function
	///
	/// \param X the value at which to evaluate the function
	/// \return the value of the sine-function at X
	virtual R operator()(const D &X) const noexcept override {
	return Amplitude * sin(Frequency * X + Phase) + Average;
	}
	};

	/// Implements \c rosa::agent::PartialFunction as a step function from 0 to 1
	/// with a ramp in between
	///
	/// \tparam D type of the functions domain
	/// \tparam R type of the functions range
	template <typename D, typename R>
	class StepFunction : public Abstraction<D, R> {
	// Make sure the actual type arguments are matching our expectations.
	STATIC_ASSERT((std::is_arithmetic<D>::value), "abstracting not arithmetic");
	STATIC_ASSERT((std::is_arithmetic<R>::value),
	"abstracting not to arithmetic");

	private:
	D Coefficient;
	D RightLimit;

	public:
	/// Creates an instance by Initializing the underlying \c Abstraction.
	///
	/// \param Coefficient Coefficient of the ramp
	///
	/// \pre Coefficient > 0
	StepFunction(D Coefficient)
	: Abstraction<D, R>(0), Coefficient(Coefficient),
	RightLimit(1.0f / Coefficient) {
	ASSERT(Coefficient > 0);
	}

	/// Destroys \p this object.
	~StepFunction(void) = default;

	/// Setter for Coefficient
	///
	/// \param Coefficient the new Coefficient
	void setCoefficient(const D &Coefficient) {
	ASSERT(Coefficient > 0);
	this->Coefficient = Coefficient;
	this->RightLimit = 1 / Coefficient;
	}

	/// Setter for RightLimit
	///
	/// \param RightLimit the new RightLimit
	- void setRightLimit(const D &RightLimit) {
	- ASSERT(RightLimit > 0);
	- this->RightLimit = RightLimit;
	- this->Coefficient = 1 / RightLimit;
	+ //@Benedikt: I had to change the name of the parameter from RightLimit to
	+ // RightLimit_, because otherwise there was a "warning treaded as error:
	+ // warning: C4458: declaration of 'RightLimit' hides class member"
	+ void setRightLimit(const D &RightLimit_) {
	+ ASSERT(RightLimit_ > 0);
	+ this->RightLimit = RightLimit_;
	+ this->Coefficient = 1 / RightLimit_;
	}

	/// Checks wether the Abstraction evaluates to default at the given position
	///
	/// \param V the value at which to check if the function falls back to it's
	/// default value.
	///
	/// \return false if the is negative, true otherwise
	bool isDefaultAt(const D &V) const noexcept override { return V > 0; }

	/// Executes the Abstraction
	///
	/// \param V value to abstract
	///
	/// \return the abstracted value
	R operator()(const D &V) const noexcept override {
	if (V <= 0)
	return 0;
	if (V >= RightLimit)
	return 1;
	return V * Coefficient;
	}
	};

	/// Implements \c rosa::agent::Abstraction as a partial function from a domain
	/// to a range.
	///
	/// \note This implementation is supposed to be used to represent a partial
	/// function from an arithmetic domain to an arithmetic range. This is enforced
	/// statically.
	///
	/// A partial function is defined as a list of abstractions, where each
	/// abstraction is associated a range in which it is defined. These ranges must
	/// be mutually exclusive.
	///
	/// \tparam D type of the functions domain
	/// \tparam R type of the functions range
	template <typename D, typename R>
	class PartialFunction : public Abstraction<D, R> {
	// Make sure the actual type arguments are matching our expectations.
	STATIC_ASSERT((std::is_arithmetic<D>::value), "abstracting not arithmetic");
	STATIC_ASSERT((std::is_arithmetic<R>::value),
	"abstracting not to arithmetic");

	private:
	/// A \c rosa::agent::RangeAbstraction RA is used to represent the association
	/// from ranges to Abstractions.
	/// This returns the Abstraction that is defined for any given value, or
	/// a default Abstraction if no Abstraction is defined for that value.
	RangeAbstraction<D, std::shared_ptr<Abstraction<D, R>>> RA;

	public:
	/// Creates an instance by Initializing the underlying \c Abstraction.
	///
	/// \param Map the mapping to do abstraction according to
	/// \param Default abstraction to abstract to by default
	///
	/// \pre Each key defines a valid range such that `first <= second` and
	/// there are no overlapping ranges defined by the keys.
	PartialFunction(
	const std::map<std::pair<D, D>, std::shared_ptr<Abstraction<D, R>>> &Map,
	const R Default)
	: Abstraction<D, R>(Default),
	RA(Map,
	std::shared_ptr<Abstraction<D, R>>(new Abstraction<D, R>(Default))) {
	}

	/// Destroys \p this object.
	~PartialFunction(void) = default;

	/// Checks wether the Abstraction evaluates to default at the given position
	///
	/// \param V the value at which to check if the function falls back to it's
	/// default value.
	///
	/// \return false if the value falls into a defined range and the Abstraction
	/// defined for that range does not fall back to it's default value.
	bool isDefaultAt(const D &V) const noexcept override {
	return RA.isDefaultAt(V) ? true : RA(V)->isDefaultAt(V);
	}

	/// Searches for an Abstraction for the given value and executes it for that
	/// value, if such an Abstraction is found. The default Abstraction is
	/// evaluated otherwise.
	///
	/// \param V value to abstract
	///
	/// \return the abstracted value based on the set mapping
	R operator()(const D &V) const noexcept override {
	return RA(V)->operator()(V);
	}
	};
	} // End namespace agent
	} // End namespace rosa

	#endif // ROSA_AGENT_FUNCTIONABSTRACTIONS_HPP
	diff --git a/include/rosa/agent/History.hpp b/include/rosa/agent/History.hpp
	index 2426f9b..f8d66d1 100644
	--- a/include/rosa/agent/History.hpp
	+++ b/include/rosa/agent/History.hpp
	@@ -1,536 +1,548 @@
	//===-- rosa/agent/History.hpp ----------------------------------- C++ --===//
	//
	// The RoSA Framework
	//
	//===----------------------------------------------------------------------===//
	///
	/// \file rosa/agent/History.hpp
	///
	/// \author David Juhasz (david.juhasz@tuwien.ac.at)
	///
	/// \date 2017
	///
	/// \brief Definition of history functionality.
	///
	//===----------------------------------------------------------------------===//

	#ifndef ROSA_AGENT_HISTORY_HPP
	#define ROSA_AGENT_HISTORY_HPP

	#include "rosa/agent/Functionality.h"

	#include "rosa/config/config.h"

	#include "rosa/support/debug.hpp"
	#include "rosa/support/type_helper.hpp"

	#include <array>
	#include <vector>

	namespace rosa {
	namespace agent {

	/// Retention policies defining what a \c rosa::agent::History instance should
	/// do when the number of recorded entries reached its capacity.
	enum class HistoryPolicy {
	SRWF, ///< Stop Recording When Full -- no new entry is recorded when full
	FIFO, ///< First In First Out -- overwrite the earliest entry with a new one
	LIFO ///< Last In First Out -- overwrite the latest entry with a new one
	};

	template <typename T, HistoryPolicy P> class History : public Functionality {

	public:
	History(void) noexcept {}

	/// Destroys \p this object.
	virtual ~History(void) = default;

	/// Tells the retention policy applied to \p this object.
	///
	/// \return \c rosa::agent::History::P
	static constexpr HistoryPolicy policy(void) noexcept { return P; }

	/// Tells how many entries may be recorded by \c this object.
	///
	/// \note The number of entries that are actually recorded may be smaller.
	///
	/// \return The max number of entries that may be recorded
	virtual size_t maxLength(void) const noexcept = 0;

	/// Tells how many entries are currently recorded by \p this object.
	///
	/// \return number of entries currently recorded by \p this object.
	///
	/// \post The returned value cannot be larger than the capacity of \p this
	/// object:\code
	/// 0 <= numberOfEntries() && numberOfEntries <= lengthOfHistory()
	/// \endcode
	virtual size_t numberOfEntries(void) const noexcept = 0;

	/// Tells if \p this object has not recorded anything yet.
	///
	/// \return if \p this object has no entries recorded
	bool empty(void) const noexcept { return numberOfEntries() == 0; }

	/// Tells if the history reached it's maximum length
	///
	/// \return if the history reached it's maximum length.
	bool full(void) const noexcept { return numberOfEntries() == maxLength(); }

	/// Gives a constant lvalue reference to an entry stored in \p this object.
	///
	/// \note The recorded entries are indexed starting from the latest one.
	///
	/// \param I the index at which the stored entry to take from
	///
	/// \pre \p I is a valid index:\code
	/// 0 <= I && I < numberOfEntries()
	/// \endcode
	virtual const T &entry(const size_t I = 0) const noexcept = 0;

	/// Removes all entries recorded in \p this object.
	virtual void clear() noexcept = 0;

	private:
	/// Pushes a new entry into the history.
	///
	/// \note The earliest entry gets overwritten if the history is full.
	///
	/// \param V value to push into the history
	virtual void pushBack(const T &V) noexcept = 0;

	/// Replaces the most recent entry in the history.
	///
	/// \param V value to replace the most current value with
	virtual void replaceFront(const T &V) noexcept = 0;

	public:
	/// Adds a new entry to \p this object and tells if the operation was
	/// successful.
	///
	/// \note Success of the operation depends on the actual policy.
	///
	/// \param V value to store
	///
	/// \return if \p V was successfully stored
	bool addEntry(const T &V) noexcept {
	switch (P) {
	default:
	ROSA_CRITICAL("unkown HistoryPolicy");
	case HistoryPolicy::LIFO:
	if (full()) {
	replaceFront(V);
	return true;
	}
	case HistoryPolicy::SRWF:
	if (full()) {
	return false;
	}
	// \note Fall through to FIFO which unconditionally pushes the new entry.
	case HistoryPolicy::FIFO:
	// FIFO and SRWF not full.
	pushBack(V);
	return true;
	}
	}

	/// Tells the trend set by the entries recorded by \p this object.
	///
	/// The number of steps to go back when calculating the trend is defined as
	/// argument to the function.
	///
	/// \note The number of steps that can be made is limited by the number of
	/// entries recorded by \p this object.
	///
	/// \note The function is made a template only to be able to use
	/// \c std::enable_if.
	///
	/// \tparam X always use the default!
	///
	/// \param D number of steps to go back in history
	///
	/// \return trend set by analyzed entries
	///
	/// \pre Statically, \p this object stores signed arithmetic values:\code
	/// std::is_arithmetic<T>::value && std::is_signed<T>::value
	/// \endcode Dynamically, \p D is a valid number of steps to take:\code
	/// 0 <= D && D < lengthOfHistory()
	/// \endcode
	template <typename X = T>
	typename std::enable_if<
	std::is_arithmetic<X>::value && std::is_signed<X>::value, X>::type
	trend(const size_t D) const noexcept {
	STATIC_ASSERT((std::is_same<X, T>::value), "not default template arg");
	ASSERT(0 <= D && D < maxLength()); // Boundary check.
	if (numberOfEntries() < 2 \|\| D < 1) {
	// No entries for computing trend.
	return {}; // Zero element of \p T
	} else {
	// Here at least two entries.
	// \c S is the number of steps that can be done.
	const size_t S = std::min(numberOfEntries() - 1, D);
	size_t I = S;

	// Compute trend with linear regression.
	size_t SumIndices = 0;
	T SumEntries = {};
	T SumSquareEntries = {};
	T SumProduct = {};
	while (I > 0) {
	// \note Indexing for the regression starts in the past.
	const size_t Index = S - I;
	const T Entry = entry(--I);
	SumIndices += Index;
	SumEntries += Entry;
	SumSquareEntries += Entry * Entry;
	SumProduct += Entry * Index;
	}

	return (SumProduct * S - SumEntries * SumIndices) /
	(SumSquareEntries * S - SumEntries * SumEntries);
	}
	}

	/// Tells the average absolute difference between consecutive entries recorded
	/// by \p this object
	/// The number of steps to go back when calculating the average is defined as
	/// argument to the function.
	///
	/// \note The number of steps that can be made is limited by the number of
	/// entries recorded by \p this object.
	///
	/// \note The function is made a template only to be able to use
	/// \c std::enable_if.
	///
	/// \tparam X always use the default!
	///
	/// \param D number of steps to go back in history
	///
	/// \pre Statically, \p this object stores arithmetic values:\code
	/// std::is_arithmetic<T>::value
	/// \endcode Dynamically, \p D is a valid number of steps to take:\code
	/// 0 <= D && D < lengthOfHistory()
	/// \endcode
	template <typename X = T>
	typename std::enable_if<std::is_arithmetic<X>::value, size_t>::type
	averageAbsDiff(const size_t D) const noexcept {
	STATIC_ASSERT((std::is_same<X, T>::value), "not default template arg");
	ASSERT(0 <= D && D < maxLength()); // Boundary check.
	if (numberOfEntries() < 2 \|\| D < 1) {
	// No difference to average.
	return {}; // Zero element of \p T
	} else {
	// Here at least two entries.
	// \c S is the number of steps that can be done.
	const size_t S = std::min(numberOfEntries() - 1, D);

	// Sum up differences as non-negative values only, hence using an
	// unsigned variable for that.
	size_t Diffs = {}; // Init to zero.
	// Count down entry indices and sum up all the absolute differences.
	size_t I = S;
	T Last = entry(I);
	while (I > 0) {
	T Next = entry(--I);
	Diffs += Last < Next ? Next - Last : Last - Next;
	Last = Next;
	}
	// Return the average of the summed differences.
	return Diffs / S;
	}
	}

	/// Tells the average of all entries recorded by \p this object
	///
	/// \tparam R type of the result
	template <typename R> R average() const noexcept {
	R Average = 0;
	for (size_t I = 0; I < numberOfEntries(); I++) {
	Average += entry(I);
	}
	Average /= numberOfEntries();
	return Average;
	}
	};

	/// Implements history by recording and storing values.
	/// The length of the underlying std::array is static and must be set at
	/// compile-time
	///
	/// \note Not thread-safe implementation, which should not be a problem as any
	/// instance of \c rosa::agent::Functionality is an internal component of a
	/// \c rosa::Agent, which is the basic unit of concurrency.
	///
	/// \tparam T type of values to store
	/// \tparam N number of values to store at most
	/// \tparam P retention policy to follow when capacity is reached
	///
	/// \invariant The size of the underlying \c std::array is `N + 1`:\code
	/// max_size() == N + 1 && N == max_size() - 1
	/// \endcode
	template <typename T, size_t N, HistoryPolicy P>
	class StaticLengthHistory : public History<T, P>, private std::array<T, N + 1> {

	// Bring into scope inherited functions that are used.
	using std::array<T, N + 1>::max_size;
	using std::array<T, N + 1>::operator[];

	/// The index of the first data element in the circular buffer.
	size_t Data;

	/// The index of the first empty slot in the circular buffer.
	size_t Space;

	public:
	using History<T, P>::policy;
	using History<T, P>::empty;
	using History<T, P>::full;
	using History<T, P>::addEntry;
	using History<T, P>::trend;
	using History<T, P>::averageAbsDiff;

	/// Creates an instances by initializing the indices for the circular buffer.
	StaticLengthHistory(void) noexcept : Data(0), Space(0) {}

	/// Destroys \p this object.
	~StaticLengthHistory(void) override = default;

	/// Tells how many entries may be recorded by \c this object.
	///
	/// \note The number of entries that are actually recorded may be smaller.
	///
	/// \return \c rosa::agent::History::N
	size_t maxLength(void) const noexcept override { return N; }

	/// Tells how many entries are currently recorded by \p this object.
	///
	/// \return number of entries currently recorded by \p this object.
	///
	/// \post The returned value cannot be larger than the capacity of \p this
	/// object:\code
	/// 0 <= numberOfEntries() && numberOfEntries <= lengthOfHistory()
	/// \endcode
	size_t numberOfEntries(void) const noexcept override {
	return Data <= Space ? Space - Data : max_size() - Data + Space;
	}

	/// Gives a constant lvalue reference to an entry stored in \p this object.
	///
	/// \note The recorded entries are indexed starting from the latest one.
	///
	/// \param I the index at which the stored entry to take from
	///
	/// \pre \p I is a valid index:\code
	/// 0 <= I && I < numberOfEntries()
	/// \endcode
	const T &entry(const size_t I = 0) const noexcept override {
	ASSERT(0 <= I && I < numberOfEntries()); // Boundary check.
	// Position counted back from the last recorded entry.
	typename std::make_signed<const size_t>::type Pos = Space - (1 + I);
	// Actual index wrapped around to the end of the buffer if negative.
	return (*this)[Pos >= 0 ? Pos : max_size() + Pos];
	}

	/// Removes all entries recorded in \p this object.
	void clear() noexcept override {
	Data = 0;
	Space = 0;
	}

	private:
	/// Pushes a new entry into the circular buffer.
	///
	/// \note The earliest entry gets overwritten if the buffer is full.
	///
	/// \param V value to push into the buffer
	void pushBack(const T &V) noexcept override {
	// Store value to the first empty slot and step Space index.
	(*this)[Space] = V;
	Space = (Space + 1) % max_size();
	if (Data == Space) {
	// Buffer was full, step Data index.
	Data = (Data + 1) % max_size();
	}
	}

	/// Replaces the most recent entry in the history.
	///
	/// \param V value to replace the most current value with
	void replaceFront(const T &V) noexcept override {
	(*this)[(Space - 1) % max_size()] = V;
	}
	};

	/// Adds a new entry to a \c rosa::agent::History instance.
	///
	/// \note The result of \c rosa::agent::History::addEntry is ignored.
	///
	/// \tparam T type of values stored in \p H
	/// \tparam N number of values \p H is able to store
	/// \tparam P retention policy followed by \p H when capacity is reached
	///
	/// \param H to add a new entry to
	/// \param V value to add to \p H
	///
	/// \return \p H after adding \p V to it
	template <typename T, size_t N, HistoryPolicy P>
	StaticLengthHistory<T, N, P> &operator<<(StaticLengthHistory<T, N, P> &H,
	const T &V) noexcept {
	H.addEntry(V);
	return H;
	}

	/// Implements DynamicLengthHistory by recording and storing values.
	///
	/// \note Not thread-safe implementation, which should not be a problem as any
	/// instance of \c rosa::agent::Functionality is an internal component of a
	/// \c rosa::Agent, which is the basic unit of concurrency.
	///
	/// \tparam T type of values to store
	/// \tparam P retention policy to follow when capacity is reached
	template <typename T, HistoryPolicy P>
	class DynamicLengthHistory : public History<T, P>, private std::vector<T> {

	+ //@benedikt: if i dont make these public, I cannot iterate from outside
	+ // through the history. E.g., "for (auto &SavedSignalState :
	+ // DetectedSignalStates)" at line ~297 in "SignalStateDetector.hpp". Do you
	+ // have an idea to make this in a better/more beautiful way?
	+public:
	// Bring into scope inherited functions that are used.
	using std::vector<T>::erase;
	using std::vector<T>::begin;
	using std::vector<T>::end;
	using std::vector<T>::rbegin;
	using std::vector<T>::rend;
	using std::vector<T>::size;
	using std::vector<T>::max_size;
	using std::vector<T>::resize;
	using std::vector<T>::push_back;
	using std::vector<T>::pop_back;
	using std::vector<T>::operator[];

	/// The current length of the DynamicLengthHistory.
	size_t Length;

	public:
	using History<T, P>::policy;
	using History<T, P>::empty;
	using History<T, P>::full;
	using History<T, P>::addEntry;
	using History<T, P>::trend;
	using History<T, P>::averageAbsDiff;

	/// Creates an instances by setting an initial length
	DynamicLengthHistory(size_t Length) noexcept : Length(Length) {
	this->resize(Length);
	}

	/// Destroys \p this object.
	~DynamicLengthHistory(void) override = default;

	/// Tells how many entries may be recorded by \c this object.
	///
	/// \note The number of entries that are actually recorded may be smaller.
	///
	/// \return \c rosa::agent::DynamicLengthHistory::N
	size_t maxLength(void) const noexcept override { return Length; }

	/// Tells how many entries are currently recorded by \p this object.
	///
	/// \return number of entries currently recorded by \p this object.
	///
	/// \post The returned value cannot be larger than the capacity of \p this
	/// object:\code
	/// 0 <= numberOfEntries() && numberOfEntries <=
	/// lengthOfHistory() \endcode
	size_t numberOfEntries(void) const noexcept { return size(); }

	/// Gives a constant lvalue reference to an entry stored in \p this object.
	///
	/// \note The recorded entries are indexed starting from the latest one.
	///
	/// \param I the index at which the stored entry to take from
	///
	/// \pre \p I is a valid index:\code
	/// 0 <= I && I < numberOfEntries()
	/// \endcode
	const T &entry(const size_t I = 0) const noexcept override {
	ASSERT(0 <= I && I < numberOfEntries()); // Boundary check.
	return this->operator[](size() - I - 1);
	}

	/// Removes all entries recorded in \p this object.
	void clear() noexcept override { erase(begin(), end()); }

	/// Sort all entries in ascending order.
	void sortAscending(void) noexcept { std::sort(begin(), end()); }

	/// Sort all entries in descending order.
	void sortDescending(void) noexcept { std::sort(rbegin(), rend()); }

	+ /// Delets one element of the history.
	+ ///
	+ /// \param the element which shall be deleted.
	+ // @benedikt: is this ok like that? should there be some "error handling"?
	+ // checking if V is not null, or if V is member of the vector?
	+ void deleteEntry(T &V) { erase(std::find(begin(), end(), V)); }
	+
	private:
	/// Pushes a new entry into the circular buffer.
	///
	/// \note The earliest entry gets overwritten if the buffer is full.
	///
	/// \param V value to push into the buffer
	void pushBack(const T &V) noexcept override {
	if (full()) {
	erase(begin());
	}
	push_back(V);
	}

	/// Replaces the most recent entry in the history.
	///
	/// \param V value to replace the most current value with
	void replaceFront(const T &V) noexcept override {
	(void)pop_back();
	push_back(V);
	}

	public:
	/// Resizes the History length. If the new length is smaller than the number
	/// of currently stored values, values are deleted according to the
	/// HistoryPolicy.
	///
	/// @param NewLength The new Length of the History.
	void setLength(size_t NewLength) noexcept {
	Length = NewLength;
	if (NewLength < numberOfEntries()) {
	switch (P) {
	default:
	ROSA_CRITICAL("unkown HistoryPolicy");
	case HistoryPolicy::LIFO:
	case HistoryPolicy::SRWF:
	// Delete last numberOfEntries() - NewLength items from the back
	erase(begin() + NewLength, end());
	break;
	case HistoryPolicy::FIFO:
	// Delete last numberOfEntries() - NewLength items from the front
	erase(begin(), begin() + (numberOfEntries() - NewLength));
	break;
	}
	}
	this->resize(Length);
	}
	};

	/// Adds a new entry to a \c rosa::agent::DynamicLengthHistory instance.
	///
	/// \note The result of \c rosa::agent::DynamicLengthHistory::addEntry is
	/// ignored.
	///
	/// \tparam T type of values stored in \p H
	/// \tparam P retention policy followed by \p H when capacity is reached
	///
	/// \param H to add a new entry to
	/// \param V value to add to \p H
	///
	/// \return \p H after adding \p V to it
	template <typename T, HistoryPolicy P>
	DynamicLengthHistory<T, P> &operator<<(DynamicLengthHistory<T, P> &H,
	const T &V) noexcept {
	H.addEntry(V);
	return H;
	}
	} // End namespace agent
	} // End namespace rosa

	#endif // ROSA_AGENT_HISTORY_HPP
	diff --git a/include/rosa/agent/SignalState.hpp b/include/rosa/agent/SignalState.hpp
	index dcbcba4..3a68820 100644
	--- a/include/rosa/agent/SignalState.hpp
	+++ b/include/rosa/agent/SignalState.hpp
	@@ -1,420 +1,380 @@
	//===-- 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/FunctionAbstractions.hpp"
	#include "rosa/agent/Functionality.h"
	#include "rosa/agent/History.hpp"
	+#include "rosa/support/math.hpp"

	#include <cstdarg>

	namespace rosa {
	namespace agent {

	/// Signal state conditions defining how the condition of a \c
	/// rosa::agent::SignalState is saved in \c rosa::agent::SignalStateInformation.
	enum class SignalStateCondition {
	STABLE, ///< The signal state is stable
	DRIFTING, ///< The signal state is drifting
	UNKNOWN ///< The signal state is unknown
	};

	template <typename CONFDATATYPE> struct SignalStateInformation {
	// Make sure the actual type arguments are matching our expectations.
	STATIC_ASSERT((std::is_arithmetic<CONFDATATYPE>::value),
	"confidence type is not to arithmetic");

	/// The signal state ID saved as an unsigned integer number
	unsigned int SignalStateID;
	/// The SignalStateConfidence shows the overall confidence value of the signal
	/// state.
	CONFDATATYPE SignalStateConfidence;
	/// The SignalStateCondition shows the condition of a signal state (stable or
	/// drifting)
	SignalStateCondition SignalStateCondition;
	/// The SignalStateIsValid shows whether a signal state is valid or invalid.
	/// In this context, valid means that enough samples which are in close
	/// proximitry have been inserted into the signal state.
	bool SignalStateIsValid;
	/// The SignalStateJustGotValid shows whether a signal state got valid
	/// (toggled from invalid to valid) during the current inserted sample.
	bool SignalStateJustGotValid;
	/// The SignalStateIsValidAfterReentrance shows whether a signal state is
	/// valid after the variable changed back to it again.
	bool SignalStateIsValidAfterReentrance;
	};

	-// @Benedikt: now there are 4 datatypes. Do you think we can merge PROCDATATYPE
	-// and PROCDATATYPE somehow?
	/// \tparam INDATATYPE type of input data, \tparam CONFDATATYPE type of
	/// data in that the confidence values are given, \param 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");

	private:
	// For the convinience to write a shorter data type name
	using PartFuncPointer =
	std::shared_ptr<PartialFunction<INDATATYPE, CONFDATATYPE>>;
	+ // @Benedikt: are INDATATYPE, CONFDATATYPE right here?
	using StepFuncPointer =
	std::shared_ptr<StepFunction<INDATATYPE, CONFDATATYPE>>;

	/// SignalStateInfo is a struct SignalStateInformation that contains
	/// information about the current state.
	SignalStateInformation<CONFDATATYPE> SignalStateInfo;

	/// The FuzzyFunctionSampleMatches is the fuzzy function that gives the
	/// confidence how good the new sample matches another sample in the sample
	/// history.
	PartFuncPointer FuzzyFunctionSampleMatches;

	/// The FuzzyFunctionSampleMismatches is the fuzzy function that gives the
	/// confidence how bad the new sample matches another sample in the sample
	/// history.
	PartFuncPointer FuzzyFunctionSampleMismatches;

	/// The FuzzyFunctionNumOfSamplesMatches is the fuzzy function that gives the
	/// confidence how many samples from the sampe history match the new sample.
	StepFuncPointer FuzzyFunctionNumOfSamplesMatches;

	/// The FuzzyFunctionNumOfSamplesMismatches is the fuzzy function that gives
	/// the confidence how many samples from the sampe history mismatch the new
	/// sample.
	StepFuncPointer FuzzyFunctionNumOfSamplesMismatches;

	/// 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.
	PartFuncPointer 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).
	PartFuncPointer FuzzyFunctionSignalIsStable;

	/// 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.
	DynamicLengthHistory<INDATATYPE, HistoryPolicy::SRWF> DAB;
	/// DABHistory is a history in that the last DABs (to be exact, the averages
	/// of the last DABs) are stored.
	DynamicLengthHistory<PROCDATATYPE, HistoryPolicy::LIFO> DABHistory;

	/// The SignalStateIsValid shows whether a signal state is valid or invalid.
	/// In this context, valid means that enough samples which are in close
	/// proximitry have been inserted into the signal state.
	bool SignalStateIsValid;
	/// The SignalStateIsValidAfterReentrance shows whether a signal state is
	/// valid after the variable changed back to it again.
	bool SignalStateIsValidAfterReentrance;

	public:
	// @Maxi doxygen per default doesn't display private attributes of a class. So
	// I copied them to the constructor. So the user has more information.
	/// Creates an instance by setting all parameters
	/// \param SignalStateID The Id of the SignalStateinfo \c
	/// SignalStateInformation.
	///
	/// \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(unsigned int SignalStateID,
	+ SignalState(unsigned int SignalStateID, unsigned int SampleHistorySize,
	+ unsigned int DABSize, unsigned int DABHistorySize,
	PartFuncPointer FuzzyFunctionSampleMatches,
	PartFuncPointer FuzzyFunctionSampleMismatches,
	StepFuncPointer FuzzyFunctionNumOfSamplesMatches,
	StepFuncPointer FuzzyFunctionNumOfSamplesMismatches,
	PartFuncPointer FuzzyFunctionSignalIsDrifting,
	- PartFuncPointer FuzzyFunctionSignalIsStable,
	- unsigned int SampleHistorySize, unsigned int DABSize,
	- unsigned int DABHistorySize) noexcept
	- : SignalStateInfo(SignalStateID, 0, SignalStateCondition::UNKNOWN, false,
	- false),
	+ PartFuncPointer FuzzyFunctionSignalIsStable) noexcept
	+ : SignalStateInfo{SignalStateID, 0, SignalStateCondition::UNKNOWN,
	+ false, false, false},
	SampleHistory(SampleHistorySize), DAB(DABSize),
	DABHistory(DABHistorySize),
	FuzzyFunctionSampleMatches(FuzzyFunctionSampleMatches),
	FuzzyFunctionSampleMismatches(FuzzyFunctionSampleMismatches),
	FuzzyFunctionNumOfSamplesMatches(FuzzyFunctionNumOfSamplesMatches),
	FuzzyFunctionNumOfSamplesMismatches(
	FuzzyFunctionNumOfSamplesMismatches),
	FuzzyFunctionSignalIsDrifting(FuzzyFunctionSignalIsDrifting),
	FuzzyFunctionSignalIsStable(FuzzyFunctionSignalIsStable) {}

	/// Destroys \p this object.
	~SignalState(void) = default;

	void leaveSignalState(void) noexcept {
	DAB.clear();
	SignalStateIsValidAfterReentrance = false;
	}

	SignalStateInformation<CONFDATATYPE>
	insertSample(INDATATYPE Sample) noexcept {
	SampleHistory.addEntry(Sample);

	DAB.addEntry(Sample);
	if (DAB.full()) {
	PROCDATATYPE AvgOfDAB = DAB.template average<PROCDATATYPE>();
	DABHistory.addEntry(AvgOfDAB);
	DAB.clear();
	}

	+ //@Benedikt: Do I really have to cast here?
	FuzzyFunctionNumOfSamplesMatches->setRightLimit(
	- SampleHistory->numberOfEntries());
	+ static_cast<INDATATYPE>(SampleHistory.numberOfEntries()));
	FuzzyFunctionNumOfSamplesMismatches->setRightLimit(
	- SampleHistory->numberOfEntries());
	+ static_cast<INDATATYPE>(SampleHistory.numberOfEntries()));

	// TODO: calculate whether signal state is valid and properly set
	// SignalStateIsValid, SignalStateJustGotValid,
	// SignalStateIsValidAfterReentrance

	// TODO: check current signal state whether it drifts

	// TODO: write in SignalStateInfo

	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;
	+ RelativeDistanceHistory(SampleHistory.maxLength());

	// calculate distances to all history samples
	for (auto &HistorySample : SampleHistory) {
	- PROCDATATYPE RelativeDistance = relativeDistance(Sample, HistorySample);
	+ PROCDATATYPE RelativeDistance =
	+ relativeDistance<INDATATYPE, PROCDATATYPE>(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.

	for (unsigned int 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
	//@benedikt: check if your partialfunctions can take infinity as
	// argument
	+ //@benedikt: same as before "->operator()"
	ConfidenceFromRelativeDistance = 0;
	} else {
	- ConfidenceFromRelativeDistance =
	- FuzzyFunctionSampleMatches(RelativeDistanceHistory[Case]);
	+ ConfidenceFromRelativeDistance = FuzzyFunctionSampleMatches->operator()(
	+ RelativeDistanceHistory[Case]);
	}

	- ConfidenceOfWorstFittingSample = fuzzyAND(ConfidenceOfWorstFittingSample,
	- ConfidenceFromRelativeDistance);
	-
	- // @benedikt: change old-style cast to one of these: reinterpret_cast,
	- // static_cast, dynamic_cast or const_cast. Which should I use? Or should
	- // the HistSampleCounter variable already be CONFDATATYPE type?
	- ConfidenceOfBestCase = fuzzyOR(
	- ConfidenceOfBestCase,
	- fuzzyAND(ConfidenceOfWorstFittingSample,
	- FuzzyFunctionNumOfSamplesMatches((CONFDATATYPE)Case + 1)));
	+ ConfidenceOfWorstFittingSample = fuzzyAND<CONFDATATYPE>(
	+ 2, ConfidenceOfWorstFittingSample, ConfidenceFromRelativeDistance);
	+ //@benedikt: do i have to pass the number 2 to tell the function how many
	+ // arguments are following?
	+ //@benedikt: same as before with "->operator()"
	+ ConfidenceOfBestCase = fuzzyOR<CONFDATATYPE>(
	+ 2, ConfidenceOfBestCase,
	+ fuzzyAND<CONFDATATYPE>(2, ConfidenceOfWorstFittingSample,
	+ FuzzyFunctionNumOfSamplesMatches->operator()(
	+ static_cast<CONFDATATYPE>(Case) + 1)));
	}

	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;
	+ RelativeDistanceHistory(SampleHistory.maxLength());

	// calculate distances to all history samples
	for (auto &HistorySample : SampleHistory) {
	- RelativeDistanceHistory.addEntry(relativeDistance(Sample, HistorySample));
	+ RelativeDistanceHistory.addEntry(
	+ relativeDistance<INDATATYPE, PROCDATATYPE>(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;
	- unsigned int Case = 1;

	// 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.
	// TODO (future): to accelerate -> don't go until end. Confidences will only
	// get higher. See comment in "CONFDATATYPE
	// confidenceSampleMatchesSignalState(INDATATYPE Sample)".
	for (unsigned int Case = 0;
	Case < RelativeDistanceHistory.numberOfEntries(); Case++) {

	CONFDATATYPE ConfidenceFromRelativeDistance;

	if (std::isinf(RelativeDistanceHistory[Case])) {
	ConfidenceFromRelativeDistance = 1;
	} else {
	+ //@benedikt: I had to change the following line. The outcommented line
	+ // was the original one. I think it is ugly like that (new line). Do you
	+ // have an idea how to make it better/more beautiful?
	ConfidenceFromRelativeDistance =
	- FuzzyFunctionSampleMismatches(RelativeDistanceHistory[Case]);
	+ FuzzyFunctionSampleMismatches->operator()(
	+ RelativeDistanceHistory[Case]);
	+ // FuzzyFunctionSampleMismatches(RelativeDistanceHistory[Case]);
	}

	- ConfidenceOfBestFittingSample = fuzzyOR(ConfidenceOfBestFittingSample,
	- ConfidenceFromRelativeDistance);
	-
	- // @benedikt: change old-style cast to one of these: reinterpret_cast,
	- // static_cast, dynamic_cast or const_cast. Which should I use? Or should
	- // the HistSampleCounter variable already be CONFDATATYPE type?
	- ConfidenceOfWorstCase = fuzzyAND(
	- ConfidenceOfWorstCase,
	- fuzzyOR(ConfidenceOfBestFittingSample,
	- FuzzyFunctionNumOfSamplesMismatches((CONFDATATYPE)Case + 1)));
	+ //@benedikt: do i have to pass the number 2 to tell the function how many
	+ // arguments are following?
	+ ConfidenceOfBestFittingSample = fuzzyOR<CONFDATATYPE>(
	+ 2, ConfidenceOfBestFittingSample, ConfidenceFromRelativeDistance);
	+
	+ //@benedikt: do i have to pass the number 2 to tell the function how many
	+ // arguments are following?
	+ //@benedikt: same as before with "->operator()"
	+ ConfidenceOfWorstCase = fuzzyAND<CONFDATATYPE>(
	+ 2, ConfidenceOfWorstCase,
	+ fuzzyOR<CONFDATATYPE>(2, ConfidenceOfBestFittingSample,
	+ FuzzyFunctionNumOfSamplesMismatches->operator()(
	+ static_cast<CONFDATATYPE>(Case) + 1)));
	}

	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:
	- // @David: Where should these next functions (fuzzyAND, fuzzyOR,
	- // relativeDistance) moved to (I guess we will use them also somewhere else)?
	-
	- // copied from the internet and adapted
	- // (https://stackoverflow.com/questions/1657883/variable-number-of-arguments-in-c)
	- CONFDATATYPE fuzzyAND(int n_args, ...) noexcept {
	- va_list ap;
	- va_start(ap, n_args);
	- CONFDATATYPE min = va_arg(ap, CONFDATATYPE);
	- for (int i = 2; i <= n_args; i++) {
	- CONFDATATYPE a = va_arg(ap, CONFDATATYPE);
	- min = std::min(a, min);
	- }
	- va_end(ap);
	- return min;
	- }
	-
	- // copied from the internet
	- // (https://stackoverflow.com/questions/1657883/variable-number-of-arguments-in-c)
	- CONFDATATYPE fuzzyOR(int n_args, ...) noexcept {
	- va_list ap;
	- va_start(ap, n_args);
	- CONFDATATYPE max = va_arg(ap, CONFDATATYPE);
	- for (int i = 2; i <= n_args; i++) {
	- CONFDATATYPE a = va_arg(ap, CONFDATATYPE);
	- std::max(a, max);
	- }
	- va_end(ap);
	- return max;
	- }
	-
	- PROCDATATYPE relativeDistance(INDATATYPE SampleValue,
	- INDATATYPE HistoryValue) noexcept {
	- PROCDATATYPE Dist = HistoryValue - SampleValue;
	-
	- if (Dist == 0) {
	- return 0;
	- } else {
	- Dist = Dist / SampleValue;
	- if (Dist < 0) {
	- //@benedikt: I guess this multiplication here should not be done because
	- // it could be that the distance fuzzy functions are not symetrical
	- //(negative and positive side)
	- Dist = Dist * (-1);
	- }
	- return (Dist);
	- }
	- }
	};

	} // End namespace agent
	} // End namespace rosa

	#endif // ROSA_AGENT_SIGNALSTATE_HPP
	diff --git a/include/rosa/agent/SignalStateDetector.hpp b/include/rosa/agent/SignalStateDetector.hpp
	index b306ede..d1ebec5 100644
	--- a/include/rosa/agent/SignalStateDetector.hpp
	+++ b/include/rosa/agent/SignalStateDetector.hpp
	@@ -1,367 +1,357 @@
	//===-- rosa/agent/SignalStateDetector.hpp ----------------------------*- C++
	//-*-===//
	//
	// The RoSA Framework
	//
	//===----------------------------------------------------------------------===//
	///
	/// \file rosa/agent/SignalStateDetector.hpp
	///
	/// \author Maximilian Götzinger (maximilian.goetzinger@tuwien.ac.at)
	///
	/// \date 2019
	///
	/// \brief Definition of signal state detector functionality.
	///
	//===----------------------------------------------------------------------===//

	#ifndef ROSA_AGENT_SIGNALSTATEDETECTOR_HPP
	#define ROSA_AGENT_SIGNALSTATEDETECTOR_HPP

	#include "rosa/agent/FunctionAbstractions.hpp"
	#include "rosa/agent/Functionality.h"
	#include "rosa/agent/SignalState.hpp"

	#include <vector>

	namespace rosa {
	namespace agent {

	/// Implements \c rosa::agent::SignalStateDetector as a functionality that
	/// detects signal states given on input samples.
	///
	/// \note This implementation is supposed to be used for samples of an
	/// arithmetic type.
	///
	-/// \tparam INDATATYPE is the type of input data, \tparam CONFDATATYPE is type
	-/// of
	-/// data in that the confidence values are given
	-template <typename INDATATYPE, typename CONFDATATYPE>
	+/// \tparam INDATATYPE type of input data, \tparam CONFDATATYPE type of
	+/// data in that the confidence values are given, \param PROCDATATYPE type of
	+/// the relative distance and the type of data in which DABs are saved.
	+template <typename INDATATYPE, typename CONFDATATYPE, typename PROCDATATYPE,
	+ HistoryPolicy HP>
	class SignalStateDetector : 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");

	private:
	// For the convinience to write a shorter data type name
	using PartFuncPointer =
	std::shared_ptr<PartialFunction<INDATATYPE, CONFDATATYPE>>;
	using StepFuncPointer =
	std::shared_ptr<StepFunction<INDATATYPE, CONFDATATYPE>>;
	- using SignalStatePtr = std::shared_ptr<SignalStateInformation<CONFDATATYPE>>;
	- using SignalStateInfoPtr =
	- std::shared_ptr<SignalStateInformation<CONFDATATYPE>>;
	+ using SignalStatePtr =
	+ std::shared_ptr<SignalState<INDATATYPE, CONFDATATYPE, PROCDATATYPE>>;

	/// The NextSignalStateID is a counter variable which stores the ID which the
	/// next signal state shall have.
	unsigned int NextSignalStateID;

	/// The SignalStateHasChanged is a flag that show whether a signal has changed
	/// its state.
	bool SignalStateHasChanged;

	/// The CurrentSignalState is a pointer to the (saved) signal state in which
	/// the actual variable (signal) of the observed system is.
	SignalStatePtr CurrentSignalState;

	/// The DetectedSignalStates is vector in that all detected signal states are
	/// saved.
	- // TODO: make it to history
	- DynamicLengthHistory<SignalStatePtr, HistoryPolicy::SRWF>
	- DetectedSignalStates;
	- // std::vector<SignalStatePtr> DetectedSignalStates;
	+ DynamicLengthHistory<SignalStatePtr, HP> DetectedSignalStates;

	/// The FuzzyFunctionSampleMatches is the fuzzy function that gives the
	/// confidence how good the new sample matches another sample in the sample
	/// history.
	PartFuncPointer FuzzyFunctionSampleMatches;

	/// The FuzzyFunctionSampleMismatches is the fuzzy function that gives the
	/// confidence how bad the new sample matches another sample in the sample
	/// history.
	PartFuncPointer FuzzyFunctionSampleMismatches;

	/// The FuzzyFunctionNumOfSamplesMatches is the fuzzy function that gives the
	/// confidence how many samples from the sampe history match the new sample.
	StepFuncPointer FuzzyFunctionNumOfSamplesMatches;

	/// The FuzzyFunctionNumOfSamplesMismatches is the fuzzy function that gives
	/// the confidence how many samples from the sampe history mismatch the new
	/// sample.
	StepFuncPointer FuzzyFunctionNumOfSamplesMismatches;

	/// The FuzzyFunctionSignalIsDrifting is the fuzzy function that gives the
	/// confidence how likely it is that the signal is drifting.
	PartFuncPointer FuzzyFunctionSignalIsDrifting;

	/// The FuzzyFunctionSignalIsStable is the fuzzy function that gives the
	/// confidence how likely it is that the signal is stable (not drifting).
	PartFuncPointer FuzzyFunctionSignalIsStable;

	/// SampleHistorySize is the (maximum) size of the sample history.
	unsigned int SampleHistorySize;
	/// DABSize the size of a DAB (Discrete Average Block).
	unsigned int DABSize;
	/// DABHistorySize is the (maximum) size of the DAB history.
	unsigned int DABHistorySize;

	public:
	/// Creates an instance by setting all parameters
	/// \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 Sets the History size which will be used by \c
	/// SignalState.
	///
	/// \param DABSize Sets the DAB size which will be used by \c SignalState.
	///
	/// \param DABHistorySize Sets the size which will be used by \c SignalState.
	///
	- SignalStateDetector(PartFuncPointer FuzzyFunctionSampleMatches,
	+ SignalStateDetector(unsigned int MaximumNumberOfSignalStates,
	+ PartFuncPointer FuzzyFunctionSampleMatches,
	PartFuncPointer FuzzyFunctionSampleMismatches,
	StepFuncPointer FuzzyFunctionNumOfSamplesMatches,
	StepFuncPointer FuzzyFunctionNumOfSamplesMismatches,
	PartFuncPointer FuzzyFunctionSignalIsDrifting,
	PartFuncPointer FuzzyFunctionSignalIsStable,
	unsigned int SampleHistorySize, unsigned int DABSize,
	unsigned int DABHistorySize) noexcept
	: NextSignalStateID(1), SignalStateHasChanged(false),
	CurrentSignalState(NULL),
	FuzzyFunctionSampleMatches(FuzzyFunctionSampleMatches),
	FuzzyFunctionSampleMismatches(FuzzyFunctionSampleMismatches),
	FuzzyFunctionNumOfSamplesMatches(FuzzyFunctionNumOfSamplesMatches),
	FuzzyFunctionNumOfSamplesMismatches(
	FuzzyFunctionNumOfSamplesMismatches),
	FuzzyFunctionSignalIsDrifting(FuzzyFunctionSignalIsDrifting),
	FuzzyFunctionSignalIsStable(FuzzyFunctionSignalIsStable),
	SampleHistorySize(SampleHistorySize), DABSize(DABSize),
	- DABHistorySize(DABHistorySize) {}
	+ DABHistorySize(DABHistorySize),
	+ DetectedSignalStates(MaximumNumberOfSignalStates) {}

	/// Destroys \p this object.
	~SignalStateDetector(void) = default;

	/// Detects a signal state to which the new sample belongs or create a new
	/// signal state if the new sample does not match to any of the saved signal
	/// states.
	///
	/// \param Sample is the actual sample of the observed signal.
	///
	/// \return the signal state ID as unsigend integer type. Signal state IDs
	/// start with number 1; that means if there is no current signal state, the
	/// return value is 0.
	unsigned int detectSignalState(INDATATYPE Sample) noexcept {
	- SignalStateInfoPtr SignalStateInfo = detectSignalState__debug(Sample);
	- return SignalStateInfo->SignalStateID;
	+ SignalStateInformation<CONFDATATYPE> SignalStateInfo =
	+ detectSignalState__debug(Sample);
	+ return SignalStateInfo.SignalStateID;
	}

	/// Gives information about the current signal state.
	///
	/// \return a the signal state ID (as unsigned integer type) of the current
	/// signal state. Signal state IDs start with number 1; that means if there is
	/// no current signal state, the return value is 0.
	unsigned int currentSignalStateInformation(void) noexcept {
	- SignalStateInfoPtr SignalStateInfo = currentSignalStateInformation__debug();
	+ SignalStateInformation<CONFDATATYPE> SignalStateInfo =
	+ currentSignalStateInformation__debug();
	if (SignalStateInfo) {
	- return SignalStateInfo->SignalStateID;
	+ return SignalStateInfo.SignalStateID;
	} else {
	return 0;
	}
	}

	/// Gives information whether a signal state change has happened or not.
	///
	/// \return true if a signal state change has happened, and false if not.
	bool signalStateHasChanged(void) noexcept { return SignalStateHasChanged; }

	private:
	- // TODO: change exlaination! it is not totally right
	- //@maxi \param is there to Document a specific parameter of a method/function
	- // this method doesn't have any parameters.
	/// Creates a new signal state and adds it to the signal state vector in which
	/// all known states are saved.
	///
	- /// \param SampleHistorySize the (maximum) size of the sample history.
	- /// \param DABSize the size of a DAB.
	- /// \param DABHistorySize the (maximum) size of the DAB history.
	- /// \param FuzzyFunctionSampleMatches the
	- /// \param FuzzyFunctionSampleMismatches
	- /// \param FuzzyFunctionNumOfSamplesMatches
	- /// \param FuzzyFunctionNumOfSamplesMismatches
	- ///
	/// \return a pointer to the newly created signal state or NULL if no state
	/// could be created.
	SignalStatePtr createNewSignalState(void) noexcept {
	- SignalStatePtr S = new (std::nothrow) SignalState(
	+ SignalStatePtr S(new SignalState<INDATATYPE, CONFDATATYPE, PROCDATATYPE>(
	NextSignalStateID, SampleHistorySize, DABSize, DABHistorySize,
	FuzzyFunctionSampleMatches, FuzzyFunctionSampleMismatches,
	- FuzzyFunctionNumOfSamplesMatches, FuzzyFunctionNumOfSamplesMismatches);
	+ FuzzyFunctionNumOfSamplesMatches, FuzzyFunctionNumOfSamplesMismatches,
	+ FuzzyFunctionSignalIsDrifting, FuzzyFunctionSignalIsStable));

	// @benedikt: todo: assert in history, which checks if push_back worked
	DetectedSignalStates.addEntry(S);

	return S;
	}

	#ifdef SIGNALSTATEDETECTORDEBUGMODE
	public:
	#else
	private:
	#endif // SIGNALSTATEDETECTORDEBUGMODE

	// @maxi is this a debug method or is it a method that will be used and
	// you simply want to have access to it in debug mode?
	// debug -> extend the preprocessor around the function
	// access -> remove the __debug from the name ( it is confusing)
	// if you want to have it marked as a debug method for auto
	// complete you can do something like this :
	//
	//#ifdef STATEDETECTORDEBUGMODE
	// public:
	// StateInfoPtr debug_detectState(INDATATYPE Sample) {
	// return detectState(Sample);
	// }
	//#endif // STATEDETECTORDEBUGMODE
	// private :
	// StateInfoPtr detectState(INDATATYPE Sample) { ...
	//
	/// Detects the signal state to which the new sample belongs or create a new
	/// signal state if the new sample does not match to any of the saved states.
	///
	/// \param Sample is the actual sample of the observed signal.
	///
	/// \return the information of the current signal state (signal state ID and
	/// other
	/// parameters).
	// TODO: return something const.. cannot remember exactly (ask benedikt)
	//
	// maybe: you are returning a pointer to the state info so who ever has that
	// pointer can actually change the information if you want to return only the
	// current info return a copy of the state info
	// like this:
	//
	// StateInfoPtr detectState__debug(INDATATYPE Sample) ->
	// StateInformation<CONFTYPE> detectState__debug(INDATATYPE Sample)
	//
	// return CurrentState->stateInformation(); ->
	// return *(CurrentState->stateInformation());
	- SignalStateInfoPtr detectSignalState__debug(INDATATYPE Sample) noexcept {
	+ SignalStateInformation<CONFDATATYPE>
	+ detectSignalState__debug(INDATATYPE Sample) noexcept {

	if (!CurrentSignalState) {
	ASSERT(DetectedSignalStates.empty());

	SignalStatePtr S = createNewSignalState();
	CurrentSignalState = S;
	} else {
	CONFDATATYPE ConfidenceSampleMatchesSignalState =
	- CurrentSignalState->confSampleMatchesSignalState(Sample);
	+ CurrentSignalState->confidenceSampleMatchesSignalState(Sample);
	CONFDATATYPE ConfidenceSampleMismatchesSignalState =
	- CurrentSignalState->confSampleMismatchesSignalState(Sample);
	+ CurrentSignalState->confidenceSampleMismatchesSignalState(Sample);

	if (ConfidenceSampleMatchesSignalState >
	ConfidenceSampleMismatchesSignalState) {
	SignalStateHasChanged = false;
	} else {
	SignalStateHasChanged = true;

	- if (CurrentSignalState->signalStateInformation()->SignalStateIsValid) {
	+ if (CurrentSignalState->signalStateInformation().SignalStateIsValid) {
	CurrentSignalState->leaveSignalState();
	} else {
	//@benedikt: changed from vector to history. can i still do the next
	// line?
	- DetectedSignalStates.erase(std::find(DetectedSignalStates.begin(),
	- DetectedSignalStates.end(),
	- CurrentSignalState));
	+ DetectedSignalStates.deleteEntry(CurrentSignalState);
	}

	// TODO (future): additionally save averages to enable fast iteration
	// through recorded signl state history (maybe sort vector based on
	// these
	// average values)
	CurrentSignalState = nullptr;

	//@benedikt: same question
	for (auto &SavedSignalState : DetectedSignalStates) {
	if (SavedSignalState != CurrentSignalState) {
	- CONFDATATYPE ConfidenceSampleMatchesSignalState =
	- SavedSignalState->confSampleMatchesSignalState(Sample);
	- CONFDATATYPE ConfidenceSampleMismatchesSignalState =
	- SavedSignalState->confSampleMismatchesSignalState(Sample);
	+ ConfidenceSampleMatchesSignalState =
	+ SavedSignalState->confidenceSampleMatchesSignalState(Sample);
	+ ConfidenceSampleMismatchesSignalState =
	+ SavedSignalState->confidenceSampleMismatchesSignalState(Sample);

	if (ConfidenceSampleMatchesSignalState >
	ConfidenceSampleMismatchesSignalState) {
	// TODO (future): maybe it would be better to compare
	// ConfidenceSampleMatchesSignalState of all signal states in the
	// vector in order to find the best matching signal state.
	CurrentSignalState = SavedSignalState;
	break;
	}
	}
	}

	if (!CurrentSignalState) {
	SignalStatePtr S = createNewSignalState();
	CurrentSignalState = S;
	}
	}
	}

	SignalStateInformation<CONFDATATYPE> SignalStateInfo =
	CurrentSignalState->insertSample(Sample);

	if (SignalStateInfo.SignalStateJustGotValid) {
	NextSignalStateID++;
	}

	return SignalStateInfo;
	}

	#ifdef SIGNALSTATEDETECTORDEBUGMODE
	public:
	#else
	private:
	#endif // SIGNALSTATEDETECTORDEBUGMODE

	/// Gives information about the current signal state.
	///
	/// \return a struct SignalStateInformation that contains information about
	/// the
	/// current signal state or NULL if no current signal state exists.
	SignalStateInformation<CONFDATATYPE>
	currentSignalStateInformation__debug(void) noexcept {
	if (CurrentSignalState) {
	return CurrentSignalState->signalStateInformation();
	} else {
	return NULL;
	}
	}
	};

	} // End namespace agent
	} // End namespace rosa

	#endif // ROSA_AGENT_SIGNALSTATEDETECTOR_HPP
	diff --git a/include/rosa/support/math.hpp b/include/rosa/support/math.hpp
	index f88a13d..705a08c 100644
	--- a/include/rosa/support/math.hpp
	+++ b/include/rosa/support/math.hpp
	@@ -1,57 +1,131 @@
	//===-- rosa/support/math.hpp ------------------------------------ C++ --===//
	//
	// The RoSA Framework
	//
	//===----------------------------------------------------------------------===//
	///
	/// \file rosa/support/math.hpp
	///
	/// \author David Juhasz (david.juhasz@tuwien.ac.at)
	///
	/// \date 2017
	///
	/// \brief Math helpers.
	///
	//===----------------------------------------------------------------------===//

	#ifndef ROSA_SUPPORT_MATH_HPP
	#define ROSA_SUPPORT_MATH_HPP

	+#include <algorithm>
	#include <cmath>
	+#include <cstdarg>
	#include <cstdlib>
	#include <limits>
	#include <type_traits>

	namespace rosa {

	/// Computes log base 2 of a number.
	///
	/// \param N the number to compute log base 2 for
	///
	/// \return log base 2 of \p N
	constexpr size_t log2(const size_t N) {
	return ((N < 2) ? 1 : 1 + log2(N / 2));
	}

	/// Tells the next representable floating point value.
	///
	/// \tparam T type to operate on
	///
	/// \note The second type argument enforces \p T being a floating point type,
	/// always use the default value!
	///
	/// \param V value to which find the next representable one
	///
	/// \return the next representable value of type \p T after value \p V
	///
	/// \pre Type \p T must be a floating point type, which is enforced by
	/// `std::enable_if` in the second type argument.
	template <typename T,
	typename = std::enable_if_t<std::is_floating_point<T>::value>>
	T nextRepresentableFloatingPoint(const T V) {
	return std::nextafter(V, std::numeric_limits<T>::infinity());
	}

	+// copied from the internet and adapted
	+// (https://stackoverflow.com/questions/1657883/variable-number-of-arguments-in-c)
	+/// Conjuncts two or more values with each other.
	+///
	+/// \param two or more values of the same datatype
	+///
	+/// \return the conjunction of the values given as parameter.
	+template <typename CONFDATATYPE>
	+CONFDATATYPE fuzzyAND(int n_args, ...) noexcept {
	+ // TODO: check datatype, if there are at least two arguments, and if they are
	+ // between 0 and 1
	+ // David suggests: nstead of a variadic argument, you could pass the values as
	+ // an std::array (with a template argument for the length). When you pass the
	+ // values as a container, you can simply use std::max_element and
	+ // std::min_element to have a one-liner implementation of the these fuzzy
	+ // functions.
	+ va_list ap;
	+ va_start(ap, n_args);
	+ CONFDATATYPE min = va_arg(ap, CONFDATATYPE);
	+ for (int i = 2; i <= n_args; i++) {
	+ CONFDATATYPE a = va_arg(ap, CONFDATATYPE);
	+ min = std::min(a, min);
	+ }
	+ va_end(ap);
	+ return min;
	+}
	+
	+/// Disjuncts two or more values with each other.
	+///
	+/// \param two or more values of the same datatype
	+///
	+/// \return the disjunction of the values given as parameter.
	+// copied from the internet
	+// (https://stackoverflow.com/questions/1657883/variable-number-of-arguments-in-c)
	+template <typename CONFDATATYPE>
	+CONFDATATYPE fuzzyOR(int n_args, ...) noexcept {
	+ // TODO: check datatype and if they are between 0 and 1
	+ // David suggests: nstead of a variadic argument, you could pass the values as
	+ // an std::array (with a template argument for the length). When you pass the
	+ // values as a container, you can simply use std::max_element and
	+ // std::min_element to have a one-liner implementation of the these fuzzy
	+ // functions.
	+ va_list ap;
	+ va_start(ap, n_args);
	+ CONFDATATYPE max = va_arg(ap, CONFDATATYPE);
	+ for (int i = 2; i <= n_args; i++) {
	+ CONFDATATYPE a = va_arg(ap, CONFDATATYPE);
	+ max = std::max(a, max);
	+ }
	+ va_end(ap);
	+ return max;
	+}
	+
	+template <typename INDATATYPE, typename PROCDATATYPE>
	+PROCDATATYPE relativeDistance(INDATATYPE NewValue,
	+ INDATATYPE HistoryValue) noexcept {
	+ PROCDATATYPE Dist = HistoryValue - NewValue;
	+
	+ if (Dist == 0) {
	+ return 0;
	+ } else {
	+ Dist = Dist / NewValue;
	+ if (Dist < 0) {
	+ // TODO: I guess this multiplication here should not be done because
	+ // it could be that the distance fuzzy functions are not symetrical
	+ //(negative and positive side)
	+ Dist = Dist * (-1);
	+ }
	+ return (Dist);
	+ }
	+}
	+
	} // End namespace rosa

	#endif // ROSA_SUPPORT_MATH_HPP

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