diff --git a/libraries/GST/GST.cpp b/libraries/GST/GST.cpp
new file mode 100644
index 00000000..d2dacb5b
--- /dev/null
+++ b/libraries/GST/GST.cpp
@@ -0,0 +1,226 @@
+//
+//    FILE: GST.cpp
+// VERSION: 0.1.1
+// PURPOSE: Arduino library for Gold Standard Test metrics
+//     URL: https://github.com/RobTillaart/GST
+//          https://en.wikipedia.org/wiki/Sensitivity_and_specificity
+//          https://en.wikipedia.org/wiki/Confusion_matrix
+//
+// formula's based upon Wikipedia.
+
+
+#include "GST.h"
+
+
+GST::GST()
+{
+  clearAll();
+};
+
+
+///////////////////////////////////////////////////////
+//
+//  INPUT FUNCTIONS
+//
+void GST::setTruePositive(float v)
+{
+  TP = v;
+  AP = TP + FN;
+};
+
+
+void GST::setTrueNegative(float v)
+{
+  TN = v;
+  AN = TN + FP;
+};
+
+
+void GST::setFalsePositive(float v)
+{
+  FP = v;
+  AN = TN + FP;
+};
+
+
+void GST::setFalseNegative(float v)
+{
+  FN = v;
+  AP = TP + FN;
+};
+
+
+void GST::clearAll()
+{
+  AP = 0;
+  AN = 0;
+  TP = 0;
+  TN = 0;
+  FP = 0;
+  FN = 0;
+}
+
+
+//  These are used for updating the test matrix
+float GST::addTruePositive(float v)
+{
+  TP += v;
+  AP = TP + FN;
+  return TP;
+};
+
+
+float GST::addTrueNegative(float v)
+{
+  TN += v;
+  AN = TN + FP;
+  return TN;
+};
+
+
+float GST::addFalsePositive(float v)
+{
+  FP += v;
+  AN = TN + FP;
+  return FP;
+};
+
+
+float GST::addFalseNegative(float v)
+{
+  FN += v;
+  AP = TP + FN;
+  return FN;
+};
+
+
+///////////////////////////////////////////////////////
+//
+//  OUTPUT FUNCTIONS I
+//
+float GST::getTruePositive()   { return TP; };
+float GST::getTrueNegative()   { return TN; };
+float GST::getFalsePositive()  { return FP; };
+float GST::getFalseNegative()  { return FN; };
+
+float GST::getTotal()          { return AP + AN; };
+float GST::getActualPositive() { return AP; };
+float GST::getActualNegative() { return AN; };
+float GST::getTestedPositive() { return TP + FP; };
+float GST::getTestedNegative() { return TN + FN; };
+
+float GST::sensitivity()       { return TPR(); };
+float GST::specificity()       { return TNR(); };
+
+
+float GST::truePositiveRate()  { return TPR(); };
+float GST::TPR() { return TP / AP; };
+float GST::trueNegativeRate()  { return TNR(); };
+float GST::TNR() { return TN / AN; };
+float GST::falseNegativeRate() { return FNR(); };
+float GST::FNR() { return FN / AP; };
+float GST::falsePositiveRate() { return FPR(); };
+float GST::FPR() { return FP / AN; };
+
+
+///////////////////////////////////////////////////////
+//
+//  OUTPUT FUNCTIONS II
+//
+float GST::positivePredictiveValue() { return PPV(); };
+float GST::PPV() { return TP / (TP + FP); };
+float GST::negativePredictiveValue() { return NPV(); };
+float GST::NPV() { return TN / (TN + FN); };
+float GST::falseDiscoveryRate() { return FDR(); };
+float GST::FDR() { return FP / (TP + FP); };
+float GST::falseOmissionRate() { return FOR(); };
+float GST::FOR() { return FN / (TN + FN); };
+
+
+float GST::positiveLikelihoodRatio() { return LRplus(); };
+float GST::LRplus()  { return TPR() / FPR(); };
+float GST::negativeLikelihoodRatio() { return LRminus(); };
+float GST::LRminus() { return FNR() / TNR(); };
+
+
+float GST::prevalenceThreshold()
+{
+  return sqrt(FPR()) / (sqrt(TPR()) + sqrt(FPR()));
+};
+
+
+float GST::threatScore()
+{
+  return TP / (TP + FN + FP);
+};
+
+
+float GST::criticalSuccessIndex()
+{
+  return threatScore();
+};
+
+
+float GST::prevalence()
+{
+  return AP / (AP + AN);
+};
+
+
+float GST::accuracy()
+{
+  return (TP + TN) / (AP + AN);
+};
+
+
+float GST::balancedAccuracy()
+{
+  return (TPR() + TNR()) * 0.5;
+};
+
+
+float GST::F1Score()
+{
+  return (2 * TP) / (2 * TP + FP + FN);
+};
+
+
+float GST::MatthewsCorrelationCoefficient() { return MCC(); };
+float GST::phi() { return MCC(); };
+float GST::MCC()
+{
+  return (TP*TN - FP*FN)/sqrt((TP+FP) * (TP+FN) * (TN+FP) * (TN+FN));
+};
+
+
+float GST::FowlkesMallowsIndex() { return FM(); };
+float GST::FM()
+{
+  return sqrt(PPV()*TPR());
+};
+
+
+float GST::BookmakerInformedness() { return BM(); };
+float GST::BM() 
+{
+  return TPR() + TNR() - 1;
+};
+
+
+float GST::markedness() { return MK(); };
+float GST::deltaP() { return MK(); };
+float GST::MK() 
+{
+  return PPV() + NPV() - 1;
+};
+
+
+float GST::diagnosticOddsRatio() { return DOR(); };
+float GST::DOR()
+{
+  return LRplus() / LRminus();
+};
+
+
+// -- END OF FILE --
+
diff --git a/libraries/GST/GST.h b/libraries/GST/GST.h
index 443c7026..5103073e 100644
--- a/libraries/GST/GST.h
+++ b/libraries/GST/GST.h
@@ -1,110 +1,116 @@
 #pragma once
 //
 //    FILE: GST.h
-// VERSION: 0.1.0
+// VERSION: 0.1.1
 // PURPOSE: Arduino library for Gold Standard Test metrics
 //     URL: https://github.com/RobTillaart/GST
 //          https://en.wikipedia.org/wiki/Sensitivity_and_specificity
 //          https://en.wikipedia.org/wiki/Confusion_matrix
 //
-// formula's based upon wikipedia.
+// formula's based upon Wikipedia.
+
+#define GST_LIB_VERSION           (F("0.1.1"))
 
 
-#define GST_LIB_VERSION           (F("0.1.0"))
+#include "Arduino.h"
 
 
 class GST
 {
 public:
-  GST() {};
+  GST();
 
-  // These 4 need to be filled in.
-  void setTruePositive(float v)   { TP = v; P = TP + FN; };
-  void setTrueNegative(float v)   { TN = v; N = TN + FP; };
-  void setFalsePositive(float v)  { FP = v; N = TN + FP; };
-  void setFalseNegative(float v)  { FN = v; P = TP + FN; };
+  //  These four values of the matrix need to be set to get started.
+  void setTruePositive(float v = 0);
+  void setTrueNegative(float v = 0);
+  void setFalsePositive(float v = 0);
+  void setFalseNegative(float v = 0);
+  void clearAll();
 
-  float getTruePositive()   { return TP; };
-  float getTrueNegative()   { return TN; };
-  float getFalsePositive()  { return FP; };
-  float getFalseNegative()  { return FN; };
-
-  float getTotal()          { return  P + N; };
-  float getActualPositive() { return  P; };
-  float getActualNegative() { return  N; };
-  float getTestedPositive() { return TP + FP; };
-  float getTestedNegative() { return TN + FN; };
-
-  float sensitivity()       { return TPR(); };
-  float specificity()       { return TNR(); };
+  //  These are used for updating the test matrix
+  float addTruePositive(float v);
+  float addTrueNegative(float v);
+  float addFalsePositive(float v);
+  float addFalseNegative(float v);
 
 
+  //  Output functions I
+  float getTruePositive();
+  float getTrueNegative();
+  float getFalsePositive();
+  float getFalseNegative();
 
-  //  true positive rate
-  float TPR() { return TP / P; };
-  //  true negative rate
-  float TNR() { return TN / N; };
+  float getTotal();
+  float getActualPositive();
+  float getActualNegative();
+  float getTestedPositive();
+  float getTestedNegative();
 
-  //  false negative rate
-  float FNR() { return FN / (FN + TP); };
-  //  false positive rate
-  float FPR() { return FP / (FP + TN); };
+  float sensitivity();
+  float specificity();
 
 
-
-  //  positive predictive value
-  float PPV() { return TP / (TP + FP); };
-  //  negative predictive value
-  float NPV() { return TN / (TN + FN); };
-
-  //  false discovery rate
-  float FDR() { return FP / (FP + TP); };
-  //  false omission rate
-  float FOR() { return FN / (FN + TN); };
+  float truePositiveRate();
+  float TPR();
+  float trueNegativeRate();
+  float TNR();
+  float falseNegativeRate();
+  float FNR();
+  float falsePositiveRate();
+  float FPR();
 
 
-
-  //  positive likelihood ratio
-  float LRplus()  { return TPR() / FPR(); };
-  //  negative likelihood ratio
-  float LRminus() { return FNR() / TNR(); };
+  //  Output functions II
+  float positivePredictiveValue();
+  float PPV();
+  float negativePredictiveValue();
+  float NPV();
+  float falseDiscoveryRate();
+  float FDR();
+  float falseOmissionRate();
+  float FOR();
 
 
-
-  float prevalenceThreshold()  { return sqrt(FPR()) / (sqrt(TPR()) + sqrt(FPR())); };
-  float threatScore()  { return TP / (TP + FN + FP); };
-  float criticalSuccessIndex() { return threatScore(); };
+  float positiveLikelihoodRatio();
+  float LRplus();
+  float negativeLikelihoodRatio();
+  float LRminus();
 
 
-
-  float prevalence()       { return P / (P + N); };
-  float accuracy()         { return (TP + TN) / (P + N); };
-  float balancedAccuracy() { return (TPR() + TNR()) / 2; };
-  float F1Score()          { return (2 * TP)/(2 * TP + FP + FN); };
+  float prevalenceThreshold();
+  float threatScore();
+  float criticalSuccessIndex();
 
 
-
-  //  Matthews correlation coefficient
-  float MCC() { return (TP*TN-FP*FN)/sqrt((TP+FP)*(TP+FN)*(TN+FP)*(TN+FN)); };
-  float phi() { return MCC(); };
-  //  Fowlkes–Mallows index
-  float FM() { return sqrt(PPV()*TPR()); };
-  //  Bookmaker informedness
-  float BM() { return TPR() + TNR() - 1; };
-  //  markedness
-  float MK() { return PPV() + NPV() - 1; };
-  float deltaP() { return MK(); };
-  //  diagnostic odds ratio
-  float DOR() { return LRplus() / LRminus(); };
+  float prevalence();
+  float accuracy();
+  float balancedAccuracy();
+  float F1Score();
 
 
-private:
-  float P  = 0;
-  float N  = 0;
-  float TP = 0;
-  float TN = 0;
-  float FP = 0;
-  float FN = 0;
+  float MatthewsCorrelationCoefficient();
+  float phi();
+  float MCC();
+  float FowlkesMallowsIndex();
+  float FM();
+  float BookmakerInformedness();
+  float BM();
+
+
+  float markedness();
+  float deltaP();
+  float MK();
+  float diagnosticOddsRatio();
+  float DOR();
+
+
+private: 
+  float AP;   //  actual positive
+  float AN;   //  actual negative
+  float TP;   //  true positive
+  float TN;   //  true negative
+  float FP;   //  false positive
+  float FN;   //  false positive
 };
 
 
diff --git a/libraries/GST/README.md b/libraries/GST/README.md
index 766df6e6..0f339668 100644
--- a/libraries/GST/README.md
+++ b/libraries/GST/README.md
@@ -13,30 +13,140 @@ Arduino library for Gold Standard Test metrics.
 
 ## Description
 
-The GST library is **experimental**.
+Note: **experimental**
+
+The GST library is an implementation of the **Gold Standard Test**.
 
 
 #### Links
 
+These sites describe the functions in more detail.
+
 - https://en.wikipedia.org/wiki/Sensitivity_and_specificity
 - https://en.wikipedia.org/wiki/Confusion_matrix
 
 
+#### Performance
+
+The math functions are from pretty straightforward to rather complex.
+
+It is possible to optimize functions with intermediate values if needed. 
+However the right way to optimize depends on the way the library is used. 
+
+
+#### Related libraries
+
+- https://github.com/RobTillaart/Statistic
+
+
 ## Interface
 
-See .h file
+See .h file for all functions. Many function exist in a long descriptive name and an acronym version. Here only the long names are given.
+
+For the definitions please check - https://en.wikipedia.org/wiki/Sensitivity_and_specificity or 
+https://en.wikipedia.org/wiki/Confusion_matrix
+
+
+### Input functions
+
+These four numbers should all be set before output functions make sense.
+The parameter **value** is typical absolute value measured or counted.
+If the parameter is omitted, the default 0 will be used to reset the value.
+
+- **void setTruePositive(float value = 0)** set the internal TP value.
+- **void setTrueNegative(float value = 0)** set the internal TN value.
+- **void setFalsePositive(float value = 0)** set the internal FP value.
+- **void setFalseNegative(float value = 0)** set the internal FN value.
+- **void clearAll()** reset all the above to 0.
+
+In tests one often want to increase / change the numbers.
+This can be done with the **addTruePositive()** etc functions. 
+After every addition all output functions can be called.
+
+- **float addTruePositive(float value)** increases the internal TP value.
+Use a negative value to decrease.
+Returns the new value of TP.
+- **float addTrueNegative(float value)** increases the internal TN value.
+Use a negative value to decrease.
+Returns the new value of TN.
+- **float addFalsePositive(float value)** increases the internal FP value.
+Use a negative value to decrease.
+Returns the new value of FP.
+- **float addFalseNegative(float value)** increases the internal FN value.
+Use a negative value to decrease.
+Returns the new value of FN.
+
+
+### Output functions I
+
+Basic output
+
+- **float getTruePositive()** returns internal TP.
+- **float getTrueNegative()** returns internal TN.
+- **float getFalsePositive()** returns internal FP.
+- **float getFalseNegative()** returns internal FN.
+
+
+- **float getTotal()** returns total of four numbers.
+- **float getActualPositive()**
+- **float getActualNegative()**
+- **float getTestedPositive()**
+- **float getTestedNegative()**
+
+
+- **float sensitivity()** equals truePositiveRate().
+- **float specificity()** equals trueNegativeRate()
+
+
+- **float truePositiveRate()**
+- **float trueNegativeRate()**
+- **float falseNegativeRate()**
+- **float falsePositiveRate()**
+
+
+### Output functions II
+
+These are the more 'complex' functions.
+Read the Wikipedia pages for their uses.
+
+- **float positivePredictiveValue()**
+- **float negativePredictiveValue()**
+- **float falseDiscoveryRate()**
+- **float falseOmissionRate()**
+
+
+- **float positiveLikelihoodRatio()**
+- **float negativeLikelihoodRatio()**
+
+
+- **float prevalenceThreshold()**
+- **float threatScore()**
+- **float criticalSuccessIndex()**
+
+
+- **float prevalence()**
+- **float accuracy()**
+- **float balancedAccuracy()**
+- **float F1Score()**
+
+
+- **float MatthewsCorrelationCoefficient()**
+- **float FowlkesMallowsIndex()**
+- **float BookmakerInformedness()**
+
+
+- **float markedness()**
+- **float deltaP()**
+- **float diagnosticOddsRatio()**
 
 
 ## Future
 
-- documentation
-  - improve
-  - more links?
+- improve documentation
+- add functions
+  - percentage functions for TP TN FP and  FN?
 - test
   - complete the CI test coverage.
 - examples
   - add real life examples.
   - combination with a sensor? batch testing?
-- code
-  - full name functions instead of acronyms. (wrap?)
-  - is GST a good class name?
diff --git a/libraries/GST/changelog.md b/libraries/GST/changelog.md
index f4983db4..8fcf132b 100644
--- a/libraries/GST/changelog.md
+++ b/libraries/GST/changelog.md
@@ -2,7 +2,18 @@
 # GST Changelog
 
 
-## 0.1.0 2022-02-25
+## 0.1.1  2022-06-08
+
+- add **addTruePositive()** etc functions.
+- add defaults for **setTruePositive(value = 0)** etc functions
+- add long descriptive names for the short functions.
+- add derived class GoldenStandardTest, for descriptive name
+- added some documentation
+- split off GST.cpp file, prevent - https://github.com/RobTillaart/CRC/issues/21
+
+
+## 0.1.0  2022-02-25
+
 - initial version
 -
 
diff --git a/libraries/GST/examples/GST_add_runtime/GST_add_runtime.ino b/libraries/GST/examples/GST_add_runtime/GST_add_runtime.ino
new file mode 100644
index 00000000..15ed248b
--- /dev/null
+++ b/libraries/GST/examples/GST_add_runtime/GST_add_runtime.ino
@@ -0,0 +1,121 @@
+//    FILE: GST_add_runtime.ino
+//  AUTHOR: Rob Tillaart
+// PURPOSE: demo
+//     URL: https://github.com/RobTillaart/GST
+
+
+#include "Arduino.h"
+#include "GST.h"
+
+
+GST gst;
+
+
+void setup()
+{
+  Serial.begin(115200);
+  while (!Serial);
+  Serial.println(__FILE__);
+
+  gst.setTruePositive(0);
+  gst.setTrueNegative(0);
+  gst.setFalsePositive(0);
+  gst.setFalseNegative(0);
+
+}
+
+void loop()
+{
+  //  simulate a test result
+  delay(500);
+  int score = random(4);
+  switch (score)
+  {
+    case 0:
+      gst.addTruePositive(1);
+      break;
+    case 1:
+      gst.addTrueNegative(1);
+      break;
+    case 2:
+      gst.addFalsePositive(1);
+      break;
+    case 3:
+      gst.addFalseNegative(1);
+      break;
+  }
+  confusion_matrix();
+  // confusion_matrix_normalized();
+
+
+}
+
+
+void confusion_matrix()
+{
+  Serial.println();
+  Serial.println(__FUNCTION__);
+  Serial.println();
+
+  //  PRINTED IN A MATRIX
+  Serial.print("\t");
+  Serial.print(gst.getTotal());
+  Serial.print("\t");
+  Serial.print(gst.getTestedPositive());
+  Serial.print("\t");
+  Serial.println(gst.getTestedNegative());
+
+  Serial.print("\t");
+  Serial.print(gst.getActualPositive());
+  Serial.print("\t");
+  Serial.print(gst.getTruePositive());
+  Serial.print("\t");
+  Serial.println(gst.getFalseNegative());
+
+  Serial.print("\t");
+  Serial.print(gst.getActualNegative());
+  Serial.print("\t");
+  Serial.print(gst.getFalsePositive());
+  Serial.print("\t");
+  Serial.println(gst.getTrueNegative());
+
+  Serial.println();
+  Serial.print("\tSensitivity:\t");
+  Serial.println(gst.sensitivity(), 4);
+  Serial.print("\tSpecificity:\t");
+  Serial.println(gst.specificity(), 4);
+}
+
+
+void confusion_matrix_normalized()
+{
+  Serial.println();
+  Serial.println(__FUNCTION__);
+  Serial.println();
+
+  //  PRINTED IN A MATRIX
+  Serial.print("\t");
+  Serial.print("100.00%");
+  Serial.print("\t");
+  Serial.print(gst.getTestedPositive());
+  Serial.print("\t");
+  Serial.println(gst.getTestedNegative());
+
+  Serial.print("\t");
+  Serial.print(gst.getActualPositive());
+  Serial.print("\t");
+  Serial.print(gst.TPR(), 4);
+  Serial.print("\t");
+  Serial.println(gst.FNR(), 4);
+
+  Serial.print("\t");
+  Serial.print(gst.getActualNegative());
+  Serial.print("\t");
+  Serial.print(gst.FPR(), 4);
+  Serial.print("\t");
+  Serial.println(gst.TNR(), 4);
+}
+
+
+
+// -- END OF FILE --
diff --git a/libraries/GST/keywords.txt b/libraries/GST/keywords.txt
index d1a467c3..5c9faac8 100644
--- a/libraries/GST/keywords.txt
+++ b/libraries/GST/keywords.txt
@@ -9,6 +9,12 @@ setTruePositive	KEYWORD2
 setTrueNegative	KEYWORD2
 setFalsePositive	KEYWORD2
 setFalseNegative	KEYWORD2
+clearAll	KEYWORD2
+
+addTruePositive	KEYWORD2
+addTrueNegative	KEYWORD2
+addFalsePositive	KEYWORD2
+addFalseNegative	KEYWORD2
 
 getTruePositive	KEYWORD2
 getTrueNegative	KEYWORD2
@@ -60,6 +66,29 @@ deltaP	KEYWORD2
 DOR	KEYWORD2
 
 
+truePositiveRate	KEYWORD2
+trueNegativeRate	KEYWORD2
+falseNegativeRate	KEYWORD2
+falsePositiveRate	KEYWORD2
+
+
+positivePredictiveValue	KEYWORD2
+negativePredictiveValue	KEYWORD2
+falseDiscoveryRate	KEYWORD2
+falseOmissionRate	KEYWORD2
+
+
+positiveLikelihoodRatio	KEYWORD2
+negativeLikelihoodRatio	KEYWORD2
+
+
+MatthewsCorrelationCoefficient	KEYWORD2
+FowlkesMallowsIndex	KEYWORD2
+BookmakerInformedness	KEYWORD2
+markedness	KEYWORD2
+diagnosticOddsRatio	KEYWORD2
+
+
 # Constants (LITERAL1)
 GST_LIB_VERSION	LITERAL1
 
diff --git a/libraries/GST/library.json b/libraries/GST/library.json
index 00317ba8..f5bafe8c 100644
--- a/libraries/GST/library.json
+++ b/libraries/GST/library.json
@@ -15,7 +15,7 @@
     "type": "git",
     "url": "https://github.com/RobTillaart/GST.git"
   },
-  "version": "0.1.0",
+  "version": "0.1.1",
   "license": "MIT",
   "frameworks": "arduino",
   "platforms": "*",
diff --git a/libraries/GST/library.properties b/libraries/GST/library.properties
index dccb3c7c..e9725827 100644
--- a/libraries/GST/library.properties
+++ b/libraries/GST/library.properties
@@ -1,5 +1,5 @@
 name=GST
-version=0.1.0
+version=0.1.1
 author=Rob Tillaart <rob.tillaart@gmail.com>
 maintainer=Rob Tillaart <rob.tillaart@gmail.com>
 sentence=Arduino library for Golden Standard Test, confusion matrix.