Program: 32204
Project: 32204
Buggy source:
@SuppressWarnings("String_Node_Str") public void buildNetwork(){
  network=new BasicNetwork();
  network.addLayer(new BasicLayer(new ActivationLinear(),true,trainSet.getInputSize()));
  int numLayers=(Integer)modelConfig.getParams().get(NUM_HIDDEN_LAYERS);
  List<String> actFunc=(List<String>)modelConfig.getParams().get(ACTIVATION_FUNC);
  List<Integer> hiddenNodeList=(List<Integer>)modelConfig.getParams().get(NUM_HIDDEN_NODES);
  if (numLayers != 0 && (numLayers != actFunc.size() || numLayers != hiddenNodeList.size())) {
    throw new RuntimeException("String_Node_Str");
  }
  log.info("String_Node_Str" + numLayers + "String_Node_Str"+ Arrays.toString(hiddenNodeList.toArray())+ "String_Node_Str"+ Arrays.toString(actFunc.toArray()));
  for (int i=0; i < numLayers; i++) {
    String func=actFunc.get(i);
    Integer numHiddenNode=hiddenNodeList.get(i);
    if ("String_Node_Str".equalsIgnoreCase(func)) {
      network.addLayer(new BasicLayer(new ActivationLinear(),true,numHiddenNode));
    }
 else     if (func.equalsIgnoreCase("String_Node_Str")) {
      network.addLayer(new BasicLayer(new ActivationSigmoid(),true,numHiddenNode));
    }
 else     if (func.equalsIgnoreCase("String_Node_Str")) {
      network.addLayer(new BasicLayer(new ActivationTANH(),true,numHiddenNode));
    }
 else     if (func.equalsIgnoreCase("String_Node_Str")) {
      network.addLayer(new BasicLayer(new ActivationLOG(),true,numHiddenNode));
    }
 else     if (func.equalsIgnoreCase("String_Node_Str")) {
      network.addLayer(new BasicLayer(new ActivationSIN(),true,numHiddenNode));
    }
 else {
      log.info("String_Node_Str" + func + "String_Node_Str");
      network.addLayer(new BasicLayer(new ActivationSigmoid(),true,numHiddenNode));
    }
  }
  network.addLayer(new BasicLayer(new ActivationSigmoid(),false,trainSet.getIdealSize()));
  network.getStructure().finalizeStructure();
  if (!modelConfig.isFixInitialInput()) {
    network.reset();
  }
 else {
    int numWeight=0;
    for (int i=0; i < network.getLayerCount() - 1; i++) {
      numWeight=numWeight + network.getLayerTotalNeuronCount(i) * network.getLayerNeuronCount(i + 1);
    }
    log.info("String_Node_Str" + numWeight + "String_Node_Str");
    loadWeightsInput(numWeight);
  }
}

Fixed version (ground truth):
@SuppressWarnings("String_Node_Str") public void buildNetwork(){
  network=new BasicNetwork();
  network.addLayer(new BasicLayer(new ActivationLinear(),true,trainSet.getInputSize()));
  int numLayers=(Integer)modelConfig.getParams().get(NUM_HIDDEN_LAYERS);
  List<String> actFunc=(List<String>)modelConfig.getParams().get(ACTIVATION_FUNC);
  List<Integer> hiddenNodeList=(List<Integer>)modelConfig.getParams().get(NUM_HIDDEN_NODES);
  if (numLayers != 0 && (numLayers != actFunc.size() || numLayers != hiddenNodeList.size())) {
    throw new RuntimeException("String_Node_Str");
  }
  if (toLoggingProcess)   log.info("String_Node_Str" + numLayers + "String_Node_Str"+ Arrays.toString(hiddenNodeList.toArray())+ "String_Node_Str"+ Arrays.toString(actFunc.toArray()));
  for (int i=0; i < numLayers; i++) {
    String func=actFunc.get(i);
    Integer numHiddenNode=hiddenNodeList.get(i);
    if ("String_Node_Str".equalsIgnoreCase(func)) {
      network.addLayer(new BasicLayer(new ActivationLinear(),true,numHiddenNode));
    }
 else     if (func.equalsIgnoreCase("String_Node_Str")) {
      network.addLayer(new BasicLayer(new ActivationSigmoid(),true,numHiddenNode));
    }
 else     if (func.equalsIgnoreCase("String_Node_Str")) {
      network.addLayer(new BasicLayer(new ActivationTANH(),true,numHiddenNode));
    }
 else     if (func.equalsIgnoreCase("String_Node_Str")) {
      network.addLayer(new BasicLayer(new ActivationLOG(),true,numHiddenNode));
    }
 else     if (func.equalsIgnoreCase("String_Node_Str")) {
      network.addLayer(new BasicLayer(new ActivationSIN(),true,numHiddenNode));
    }
 else {
      log.info("String_Node_Str" + func + "String_Node_Str");
      network.addLayer(new BasicLayer(new ActivationSigmoid(),true,numHiddenNode));
    }
  }
  network.addLayer(new BasicLayer(new ActivationSigmoid(),false,trainSet.getIdealSize()));
  network.getStructure().finalizeStructure();
  if (!modelConfig.isFixInitialInput()) {
    network.reset();
  }
 else {
    int numWeight=0;
    for (int i=0; i < network.getLayerCount() - 1; i++) {
      numWeight=numWeight + network.getLayerTotalNeuronCount(i) * network.getLayerNeuronCount(i + 1);
    }
    log.info("String_Node_Str" + numWeight + "String_Node_Str");
    loadWeightsInput(numWeight);
  }
}