diff --git a/src/eva2/server/go/problems/F16Problem.java b/src/eva2/server/go/problems/F16Problem.java
index d207f451..f0ae0f4c 100644
--- a/src/eva2/server/go/problems/F16Problem.java
+++ b/src/eva2/server/go/problems/F16Problem.java
@@ -1,6 +1,15 @@
 package eva2.server.go.problems;
 
-public class F16Problem extends AbstractProblemDouble implements InterfaceMultimodalProblem, Interface2DBorderProblem {
+import eva2.server.go.operators.postprocess.SolutionHistogram;
+
+/**
+ * The Vincent function: Multiple optima with increasing density near the lower bounds, 
+ * therefore decreasing attractor size. All have an equal best fitness of zero.
+ * 
+ * @author mkron
+ *
+ */
+public class F16Problem extends AbstractProblemDouble implements InterfaceMultimodalProblem, Interface2DBorderProblem, InterfaceInterestingHistogram {
 	int dim = 10;
 	
 	public F16Problem() {
@@ -11,6 +20,10 @@ public class F16Problem extends AbstractProblemDouble implements InterfaceMultim
 		dim = other.dim;
 	}
 	
+	public F16Problem(int theDim) {
+		this.dim=theDim;
+	}
+
 	@Override
 	public double[] eval(double[] x) {
 		x = rotateMaybe(x);
@@ -47,10 +60,15 @@ public class F16Problem extends AbstractProblemDouble implements InterfaceMultim
 	}
 
 	public String getName() {
-		return "Vincent function";
+		return "Vincent";
 	}
 	
 	public static String globalInfo() {
-		return "Multiple optima with increasing densitiy near the lower bounds, therefore decreasing attractor size.";
+		return "The Vincent function: Multiple optima with increasing densitiy near the lower bounds, therefore decreasing attractor size. All have an equal best fitness of zero.";
+	}
+
+	public SolutionHistogram getHistogram() {
+		return new SolutionHistogram(-0.001, 0.599, 15);
+//		return new SolutionHistogram(-0.001, 0.099, 5);
 	}
 }
diff --git a/src/eva2/server/go/problems/F17Problem.java b/src/eva2/server/go/problems/F17Problem.java
index 6aa6c691..c1a4cf37 100644
--- a/src/eva2/server/go/problems/F17Problem.java
+++ b/src/eva2/server/go/problems/F17Problem.java
@@ -5,7 +5,7 @@ import eva2.server.go.operators.postprocess.SolutionHistogram;
  * Bohachevsky function, numerous optima on an oval hyperparabola with similar attractor sizes 
  * but decreasing fitness towards the bounds. Described e.g. in Shir&Bäck, PPSN 2006, 
  * "Niche radius adaption in the CMA-ES Niching Algorithm".
- * 
+ * f_B(\vec{x})=\sum_{i=1}^{n-1} x_i^2+2(x_{i+1}^2)+0.7-0.3 cos (3 \pi x_i)-0.4 cos (4 \pi x_{i+1})
  */
 public class F17Problem extends AbstractProblemDouble implements
 		InterfaceMultimodalProblem, InterfaceInterestingHistogram{
diff --git a/src/eva2/server/go/problems/F19Problem.java b/src/eva2/server/go/problems/F19Problem.java
index 9043a1e2..b1189e58 100644
--- a/src/eva2/server/go/problems/F19Problem.java
+++ b/src/eva2/server/go/problems/F19Problem.java
@@ -13,7 +13,7 @@ import eva2.tools.math.RNG;
  *
  */
 public class F19Problem extends AbstractProblemDouble implements
-InterfaceMultimodalProblem, InterfaceInterestingHistogram {
+InterfaceMultimodalProblem, InterfaceInterestingHistogram, InterfaceFirstOrderDerivableProblem {
 	int dim = 10;
 	transient private double[] alphas, As;
 	transient private int[] A,B;
@@ -57,6 +57,17 @@ InterfaceMultimodalProblem, InterfaceInterestingHistogram {
 		}
 		return v;
 	}
+
+	/**
+	 * Calculate partial derivation of the B_i function by the j-th coordinate
+	 * @param x
+	 * @param i
+	 * @return
+	 */
+	private double derivedTransform(double[] x, int i, int j) {
+		double v = get(A, i, j)*Math.cos(x[j])-get(B, i, j)*Math.sin(x[j]);
+		return v;
+	}
 	
 	/**
 	 * Get a value in row i, col j, from matrix M (represented as vector).
@@ -111,5 +122,21 @@ InterfaceMultimodalProblem, InterfaceInterestingHistogram {
 		if (getProblemDimension()<15) return new SolutionHistogram(0, 8, 16);
 		else return new SolutionHistogram(0, 40000, 16);
 	}
+
+	public double[] getFirstOrderGradients(double[] x) {
+		x = rotateMaybe(x);
+		double[] res = new double[x.length];
+		double[] Bs = transform(x);
+		
+		for (int k=0; k<getProblemDimension(); k++) {
+			double sum=0;
+			for (int i=0; i<getProblemDimension(); i++) {
+				sum += (-2*As[i]*derivedTransform(x, i, k)+2*Bs[i]*derivedTransform(x, i, k));
+			}
+			res[k]=sum;
+		}
+		return res;
+	}
+
 }