Program: 21250
Project: 21250
Buggy source:
public static void main(String[] args) throws Exception {
  oneNormalVarBN=BayesianNetworkLoader.loadFromFile("String_Node_Str");
  System.out.println(oneNormalVarBN);
  for (int i=0; i < batchSize.length; i++) {
    for (int j=0; j < deltaValue.length; j++) {
      for (int k=0; k < memoryPopulationVI.length; k++) {
        for (int l=0; l < learningRate.length; l++) {
          initSVBLearners(batchSize[i],deltaValue[j]);
          initVILearners(batchSize[i],memoryPopulationVI[k],learningRate[l]);
          String path="String_Node_Str";
          writerPredLL=new PrintWriter(path + "String_Node_Str" + "String_Node_Str"+ batchSize[i]+ "String_Node_Str"+ deltaValue[j]+ "String_Node_Str"+ memoryPopulationVI[k]+ "String_Node_Str"+ learningRate[i]+ "String_Node_Str","String_Node_Str");
          writerLambda=new PrintWriter(path + "String_Node_Str" + "String_Node_Str"+ batchSize[i]+ "String_Node_Str"+ deltaValue[j]+ "String_Node_Str"+ memoryPopulationVI[k]+ "String_Node_Str"+ learningRate[i]+ "String_Node_Str","String_Node_Str");
          writerMean=new PrintWriter(path + "String_Node_Str" + "String_Node_Str"+ batchSize[i]+ "String_Node_Str"+ deltaValue[j]+ "String_Node_Str"+ memoryPopulationVI[k]+ "String_Node_Str"+ learningRate[i]+ "String_Node_Str","String_Node_Str");
          scenarioNoConceptDrift(batchSize[i]);
          writerPredLL.close();
          writerLambda.close();
          writerMean.close();
        }
      }
    }
  }
}

Fixed version (ground truth):
public static void main(String[] args) throws Exception {
  network=BayesianNetworkLoader.loadFromFile("String_Node_Str");
  System.out.println(network);
  for (int i=0; i < batchSize.length; i++) {
    for (int j=0; j < deltaValue.length; j++) {
      for (int k=0; k < memoryPopulationVI.length; k++) {
        for (int l=0; l < learningRate.length; l++) {
          initSVBLearners(batchSize[i],deltaValue[j]);
          initVILearners(batchSize[i],memoryPopulationVI[k],learningRate[l]);
          String path="String_Node_Str";
          writerPredLL=new PrintWriter(path + "String_Node_Str" + "String_Node_Str"+ batchSize[i]+ "String_Node_Str"+ deltaValue[j]+ "String_Node_Str"+ memoryPopulationVI[k]+ "String_Node_Str"+ learningRate[i]+ "String_Node_Str","String_Node_Str");
          writerLambda=new PrintWriter(path + "String_Node_Str" + "String_Node_Str"+ batchSize[i]+ "String_Node_Str"+ deltaValue[j]+ "String_Node_Str"+ memoryPopulationVI[k]+ "String_Node_Str"+ learningRate[i]+ "String_Node_Str","String_Node_Str");
          writerMean=new PrintWriter(path + "String_Node_Str" + "String_Node_Str"+ batchSize[i]+ "String_Node_Str"+ deltaValue[j]+ "String_Node_Str"+ memoryPopulationVI[k]+ "String_Node_Str"+ learningRate[i]+ "String_Node_Str","String_Node_Str");
          writerGamma=new PrintWriter(path + "String_Node_Str" + "String_Node_Str"+ batchSize[i]+ "String_Node_Str"+ deltaValue[j]+ "String_Node_Str"+ memoryPopulationVI[k]+ "String_Node_Str"+ learningRate[i]+ "String_Node_Str","String_Node_Str");
          scenarioMixedConceptDrift(batchSize[i]);
          writerPredLL.close();
          writerLambda.close();
          writerMean.close();
          writerGamma.close();
        }
      }
    }
  }
}