Program: 32963
Project: 32963
Buggy source:
public MultiLabel predictByDynamic(){
  Map<Integer,DynamicProgramming> DPs=new HashMap<>();
  double[] maxClusterProb=new double[numClusters];
  for (int k=0; k < numClusters; k++) {
    DPs.put(k,new DynamicProgramming(probs[k],logProbs[k]));
    maxClusterProb[k]=DPs.get(k).nextHighestProb();
  }
  double[] cond1=new double[numClusters];
  double[] sumPiD=new double[numClusters];
  for (int k=0; k < numClusters; k++) {
    cond1[k]=maxClusterProb[k] - 1.0 / logisticProb[k] + 1;
    double sum=0.0;
    for (int r=0; r < numClusters; r++) {
      if (r == k) {
        continue;
      }
      sum+=logisticProb[r] * maxClusterProb[r];
    }
    sumPiD[k]=sum;
  }
  double maxLogProb=Double.NEGATIVE_INFINITY;
  Vector predVector=new DenseVector(numLabels);
  int iter=0;
  int maxIter=100;
  while (DPs.size() > 0 && iter < maxIter) {
    List<Integer> removeList=new LinkedList<>();
    for (    Map.Entry<Integer,DynamicProgramming> entry : DPs.entrySet()) {
      int k=entry.getKey();
      DynamicProgramming dp=entry.getValue();
      double prob=dp.nextHighestProb();
      Vector candidateY=dp.nextHighestVector();
      if ((candidateY.maxValue() == 0.0) && !allowEmpty) {
        if (dp.dp.size() == 0) {
          removeList.add(k);
        }
        continue;
      }
      double logProb=logProbYnGivenXnLogisticProb(candidateY);
      if (logProb >= maxLogProb) {
        predVector=candidateY;
        maxLogProb=logProb;
        maxIter=iter;
      }
      if (checkStop(prob,cond1[k],maxLogProb,sumPiD[k],k) || dp.dp.size() == 0) {
        removeList.add(k);
      }
    }
    for (    int k : removeList) {
      DPs.remove(k);
    }
    iter++;
  }
  MultiLabel predLabel=new MultiLabel();
  for (int l=0; l < numLabels; l++) {
    if (predVector.get(l) == 1.0) {
      predLabel.addLabel(l);
    }
  }
  if (iter == maxIter) {
    MultiLabel sampleLabel=predictBySampling();
    Vector sampleVector=new DenseVector(numLabels);
    for (    int l : sampleLabel.getMatchedLabels()) {
      sampleVector.set(l,1.0);
    }
    double sampleLogProb=logProbYnGivenXnLogisticProb(sampleVector);
    if (sampleLogProb > maxLogProb) {
      return sampleLabel;
    }
  }
  return predLabel;
}

Fixed version (ground truth):
public MultiLabel predictByDynamic(){
  Map<Integer,DynamicProgramming> DPs=new HashMap<>();
  double[] maxClusterProb=new double[numClusters];
  for (int k=0; k < numClusters; k++) {
    DPs.put(k,new DynamicProgramming(probs[k],logProbs[k]));
    maxClusterProb[k]=DPs.get(k).nextHighestProb();
  }
  double[] cond1=new double[numClusters];
  double[] sumPiD=new double[numClusters];
  for (int k=0; k < numClusters; k++) {
    cond1[k]=maxClusterProb[k] - 1.0 / logisticProb[k] + 1;
    double sum=0.0;
    for (int r=0; r < numClusters; r++) {
      if (r == k) {
        continue;
      }
      sum+=logisticProb[r] * maxClusterProb[r];
    }
    sumPiD[k]=sum;
  }
  double maxLogProb=Double.NEGATIVE_INFINITY;
  Vector predVector=new DenseVector(numLabels);
  while (DPs.size() > 0) {
    List<Integer> removeList=new LinkedList<>();
    for (    Map.Entry<Integer,DynamicProgramming> entry : DPs.entrySet()) {
      int k=entry.getKey();
      DynamicProgramming dp=entry.getValue();
      double prob=dp.nextHighestProb();
      Vector candidateY=dp.nextHighestVector();
      if ((candidateY.maxValue() == 0.0) && !allowEmpty) {
        if (dp.dp.size() == 0) {
          removeList.add(k);
        }
        continue;
      }
      double logProb=logProbYnGivenXnLogisticProb(candidateY);
      if (logProb >= maxLogProb) {
        predVector=candidateY;
        maxLogProb=logProb;
      }
      if (checkStop(prob,cond1[k],maxLogProb,sumPiD[k],k) || dp.dp.size() == 0) {
        removeList.add(k);
      }
    }
    for (    int k : removeList) {
      DPs.remove(k);
    }
  }
  MultiLabel predLabel=new MultiLabel();
  for (int l=0; l < numLabels; l++) {
    if (predVector.get(l) == 1.0) {
      predLabel.addLabel(l);
    }
  }
  return predLabel;
}