1 files changed, 112 insertions, 0 deletions
diff --git a/src/jcgp/backend/modules/fitness/TestCaseProblem.java b/src/jcgp/backend/modules/fitness/TestCaseProblem.java
new file mode 100644
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+++ b/src/jcgp/backend/modules/fitness/TestCaseProblem.java
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+package jcgp.backend.modules.fitness;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import jcgp.backend.population.Chromosome;
+import jcgp.backend.population.Population;
+import jcgp.backend.resources.Resources;
+import jcgp.backend.resources.parameters.IntegerParameter;
+import jcgp.backend.resources.parameters.Parameter;
+
+/**
+ * 
+ * This fitness function module implements a simple test case evaluator.
+ * 
+ * A TestCase object is a 
+ * 
+ * 
+ * @author Eduardo Pedroni
+ *
+ */
+public abstract class TestCaseProblem<U> extends Problem {
+	
+	public static class TestCase<T> {
+
+		private T[] inputs;
+		private T[] outputs;
+		
+		public TestCase(T[] inputs, T[] outputs) {
+			this.inputs = inputs;
+			this.outputs = outputs;
+		}
+		
+		public T getInput(int index) {
+			return inputs[index];
+		}
+		
+		public T getOutput(int index) {
+			return outputs[index];
+		}
+		
+		public T[] getInputs() {
+			return inputs;
+		}
+		
+		public T[] getOutputs() {
+			return outputs;
+		}
+	}
+	
+	private ArrayList<TestCase<U>> testCases;
+	private IntegerParameter maxFitness;
+	
+	public TestCaseProblem() {
+		maxFitness = new IntegerParameter(0, "Max fitness", true, false) {
+			@Override
+			public void validate(int newValue) {
+				// blank
+			}
+		};
+		testCases = new ArrayList<TestCase<U>>();
+	}
+	
+	
+	@Override
+	public void evaluate(Population population, Resources resources) {
+		// for every chromosome in the population
+		for (int i = 0; i < resources.getInt("popSize"); i++) {
+			// assume an initial fitness of 0
+			int fitness = 0;
+			// for each test case
+			for (int t = 0; t < testCases.size(); t++) {
+				population.getChromosome(i).setInputs(testCases.get(t).getInputs());
+				// check each output
+				for (int o = 0; o < resources.getInt("outputs"); o++) {
+					if (population.getChromosome(i).getOutput(o).calculate() == testCases.get(t).getOutput(o)) {
+						fitness++;
+					}
+				}
+			}
+			// assign the resulting fitness to the respective individual
+			population.getChromosome(i).setFitness(fitness);
+		}
+	}
+	
+	@Override
+	public Parameter[] getLocalParameters() {
+		return new Parameter[]{maxFitness};
+	}
+	
+	private int getMaxFitness() {
+		int fitness = 0;
+		
+		for (TestCase<U> tc : testCases) {
+			fitness += tc.getOutputs().length;
+		}
+		
+		return fitness;
+	}
+	
+	public void setTestCases(List<TestCase<U>> testCases) {
+		this.testCases.clear();
+		this.testCases.addAll(testCases);
+		maxFitness.set(getMaxFitness());
+	}
+	
+	@Override
+	public boolean isPerfectSolution(Chromosome fittest) {
+		return fittest.getFitness() >= maxFitness.get();
+	}
+}
+