Program: 50994
Project: 50994
Buggy source:
public static void main(String[] args){
  long[] seeds={11,21,31,41,51,61,71,81,91,101};
  double[] cs={1,10,100,1000};
  int[] depths={1,2,3};
  int[] iterations={0,2,4,6};
  double fraction=0.1;
  dataset=new RDFFileDataSet("String_Node_Str",RDFFormat.TURTLE);
  List<EvaluationFunction> evalFuncs=new ArrayList<EvaluationFunction>();
  evalFuncs.add(new Accuracy());
  evalFuncs.add(new F1());
  ResultsTable resTable=new ResultsTable();
  resTable.setManWU(0.05);
  resTable.setDigits(3);
  boolean inference=true;
  for (  int d : depths) {
    resTable.newRow("String_Node_Str");
    for (    int it : iterations) {
      List<List<Result>> res=new ArrayList<List<Result>>();
      for (      long seed : seeds) {
        long[] s2={seed};
        loadDataSet(fraction,seed);
        List<Double> targets=EvaluationUtils.createTarget(labels);
        LibLINEARParameters linParms=new LibLINEARParameters(LibLINEARParameters.SVC_DUAL,cs);
        linParms.setEvalFunction(new Accuracy());
        linParms.setDoCrossValidation(false);
        linParms.setSplitFraction((float)0.8);
        linParms.setEps(0.1);
        Map<Double,Double> counts=EvaluationUtils.computeClassCounts(targets);
        int[] wLabels=new int[counts.size()];
        double[] weights=new double[counts.size()];
        for (        double label : counts.keySet()) {
          wLabels[(int)label - 1]=(int)label;
          weights[(int)label - 1]=1 / counts.get(label);
        }
        linParms.setWeightLabels(wLabels);
        linParms.setWeights(weights);
        RDFLinearKernelExperiment exp=new RDFLinearKernelExperiment(new RDFWLSubTreeKernel(it,d,inference,true),s2,linParms,dataset,instances,targets,blackList,evalFuncs);
        res.add(exp.getResults());
        System.out.println("String_Node_Str" + d + "String_Node_Str"+ it);
        exp.run();
      }
      for (      Result res2 : Result.mergeResultLists(res)) {
        resTable.addResult(res2);
      }
    }
  }
  resTable.addCompResults(resTable.getBestResults());
  System.out.println(resTable);
}

Fixed version (ground truth):
public static void main(String[] args){
  long[] seeds={11,21,31,41,51,61,71,81,91,101};
  double[] cs={1,10,100,1000};
  int[] depths={1,2,3};
  int[] iterations={0};
  double fraction=0.1;
  dataset=new RDFFileDataSet("String_Node_Str",RDFFormat.TURTLE);
  List<EvaluationFunction> evalFuncs=new ArrayList<EvaluationFunction>();
  evalFuncs.add(new Accuracy());
  evalFuncs.add(new F1());
  ResultsTable resTable=new ResultsTable();
  resTable.setManWU(0.05);
  resTable.setDigits(3);
  boolean inference=true;
  for (  int d : depths) {
    resTable.newRow("String_Node_Str");
    for (    int it : iterations) {
      List<List<Result>> res=new ArrayList<List<Result>>();
      for (      long seed : seeds) {
        long[] s2={seed};
        loadDataSet(fraction,seed);
        List<Double> targets=EvaluationUtils.createTarget(labels);
        LibLINEARParameters linParms=new LibLINEARParameters(LibLINEARParameters.SVC_DUAL,cs);
        linParms.setEvalFunction(new Accuracy());
        linParms.setDoCrossValidation(false);
        linParms.setSplitFraction((float)0.8);
        linParms.setEps(0.1);
        Map<Double,Double> counts=EvaluationUtils.computeClassCounts(targets);
        int[] wLabels=new int[counts.size()];
        double[] weights=new double[counts.size()];
        for (        double label : counts.keySet()) {
          wLabels[(int)label - 1]=(int)label;
          weights[(int)label - 1]=1 / counts.get(label);
        }
        linParms.setWeightLabels(wLabels);
        linParms.setWeights(weights);
        RDFLinearKernelExperiment exp=new RDFLinearKernelExperiment(new RDFWLSubTreeKernel(it,d,inference,true),s2,linParms,dataset,instances,targets,blackList,evalFuncs);
        res.add(exp.getResults());
        System.out.println("String_Node_Str" + d + "String_Node_Str"+ it);
        exp.run();
      }
      for (      Result res2 : Result.mergeResultLists(res)) {
        resTable.addResult(res2);
      }
    }
  }
  resTable.addCompResults(resTable.getBestResults());
  System.out.println(resTable);
}