Program: 32056
Project: 32056
Buggy source:
/** 
 * @param alg
 * @return
 */
public static Map<String,Object> createParamsByAlg(ALGORITHM alg){
  Map<String,Object> params=new HashMap<String,Object>();
  if (ALGORITHM.NN.equals(alg)) {
    params.put(NNTrainer.PROPAGATION,"String_Node_Str");
    params.put(NNTrainer.LEARNING_RATE,0.1);
    params.put(NNTrainer.NUM_HIDDEN_LAYERS,1);
    List<Integer> nodes=new ArrayList<Integer>();
    nodes.add(50);
    params.put(NNTrainer.NUM_HIDDEN_NODES,nodes);
    List<String> func=new ArrayList<String>();
    func.add("String_Node_Str");
    params.put(NNTrainer.ACTIVATION_FUNC,func);
    params.put("String_Node_Str",0.0);
  }
 else   if (ALGORITHM.SVM.equals(alg)) {
    params.put(SVMTrainer.SVM_KERNEL,"String_Node_Str");
    params.put(SVMTrainer.SVM_GAMMA,1.0);
    params.put(SVMTrainer.SVM_CONST,1.0);
  }
 else   if (ALGORITHM.RF.equals(alg)) {
    params.put("String_Node_Str","String_Node_Str");
    params.put("String_Node_Str",10);
    params.put("String_Node_Str",256);
    params.put("String_Node_Str","String_Node_Str");
  }
 else   if (ALGORITHM.GBDT.equals(alg)) {
    params.put("String_Node_Str","String_Node_Str");
    params.put("String_Node_Str",10);
    params.put("String_Node_Str",256);
    params.put("String_Node_Str","String_Node_Str");
    params.put(NNTrainer.LEARNING_RATE,0.1);
  }
 else   if (ALGORITHM.LR.equals(alg)) {
    params.put(LogisticRegressionTrainer.LEARNING_RATE,0.1);
    params.put("String_Node_Str",0.0);
    params.put("String_Node_Str","String_Node_Str");
  }
  return params;
}

Fixed version (ground truth):
/** 
 * @param alg
 * @return
 */
public static Map<String,Object> createParamsByAlg(ALGORITHM alg){
  Map<String,Object> params=new HashMap<String,Object>();
  if (ALGORITHM.NN.equals(alg)) {
    params.put(NNTrainer.PROPAGATION,"String_Node_Str");
    params.put(NNTrainer.LEARNING_RATE,0.1);
    params.put(NNTrainer.NUM_HIDDEN_LAYERS,1);
    List<Integer> nodes=new ArrayList<Integer>();
    nodes.add(50);
    params.put(NNTrainer.NUM_HIDDEN_NODES,nodes);
    List<String> func=new ArrayList<String>();
    func.add("String_Node_Str");
    params.put(NNTrainer.ACTIVATION_FUNC,func);
    params.put("String_Node_Str",0.0);
  }
 else   if (ALGORITHM.SVM.equals(alg)) {
    params.put(SVMTrainer.SVM_KERNEL,"String_Node_Str");
    params.put(SVMTrainer.SVM_GAMMA,1.0);
    params.put(SVMTrainer.SVM_CONST,1.0);
  }
 else   if (ALGORITHM.RF.equals(alg)) {
    params.put("String_Node_Str","String_Node_Str");
    params.put("String_Node_Str",10);
    params.put("String_Node_Str",1);
    params.put("String_Node_Str",0.0);
    params.put("String_Node_Str",256);
    params.put("String_Node_Str","String_Node_Str");
    params.put("String_Node_Str","String_Node_Str");
  }
 else   if (ALGORITHM.GBDT.equals(alg)) {
    params.put("String_Node_Str","String_Node_Str");
    params.put("String_Node_Str",10);
    params.put("String_Node_Str",1);
    params.put("String_Node_Str",0.0);
    params.put("String_Node_Str",256);
    params.put("String_Node_Str","String_Node_Str");
    params.put(NNTrainer.LEARNING_RATE,0.1);
    params.put("String_Node_Str","String_Node_Str");
  }
 else   if (ALGORITHM.LR.equals(alg)) {
    params.put(LogisticRegressionTrainer.LEARNING_RATE,0.1);
    params.put("String_Node_Str",0.0);
    params.put("String_Node_Str","String_Node_Str");
  }
  return params;
}