Program: 131285
Project: 131285
Buggy source:
@Override public void annotate(AnnoSentenceCollection inputSents){
  log.info("String_Node_Str" + pruneModel);
  JointNlpFgModel model=(JointNlpFgModel)Files.deserialize(pruneModel);
  ObsFeatureConjoiner ofc=model.getOfc();
  CorpusStatistics cs=model.getCs();
  JointNlpFeatureExtractorPrm fePrm=model.getFePrm();
  exPrm.fgPrm.includeSrl=false;
  exPrm.fgPrm.dpPrm=new DepParseFactorGraphBuilderPrm();
  exPrm.fgPrm.dpPrm.linkVarType=VarType.PREDICTED;
  exPrm.fgPrm.dpPrm.grandparentFactors=false;
  exPrm.fgPrm.dpPrm.siblingFactors=false;
  exPrm.fgPrm.dpPrm.unaryFactors=true;
  exPrm.fgPrm.dpPrm.useProjDepTreeFactor=true;
  exPrm.fePrm=fePrm;
  JointNlpFgExamplesBuilder builder=new JointNlpFgExamplesBuilder(exPrm,ofc,cs,false);
  FgExampleList data=builder.getData(inputSents);
  log.info("String_Node_Str");
  int numEdgesTot=0;
  int numEdgesKept=0;
  Timer timer=new Timer();
  timer.start();
  for (int i=0; i < inputSents.size(); i++) {
    LFgExample ex=data.get(i);
    AnnoSentence inputSent=inputSents.get(i);
    JointNlpDecoder decoder=new JointNlpDecoder(dPrm);
    AnnoSentence predSent=decoder.decode(model,ex,inputSent);
    DepEdgeMask mask=predSent.getDepEdgeMask();
    if (mask != null) {
      if (inputSent.getDepEdgeMask() == null) {
        inputSent.setDepEdgeMask(mask);
      }
 else {
        inputSent.getDepEdgeMask().and(mask);
      }
    }
    numEdgesKept+=mask.getCount();
    int n=predSent.getWords().size();
    numEdgesTot+=n * n;
  }
  timer.stop();
  log.info(String.format("String_Node_Str",inputSents.getNumTokens() / timer.totSec()));
  int numEdgesPruned=numEdgesTot - numEdgesKept;
  log.info(String.format("String_Node_Str",numEdgesPruned,numEdgesTot,(double)numEdgesPruned / numEdgesTot));
}

Fixed version (ground truth):
@Override public void annotate(AnnoSentenceCollection inputSents){
  log.info("String_Node_Str" + pruneModel);
  JointNlpFgModel model=(JointNlpFgModel)Files.deserialize(pruneModel);
  ObsFeatureConjoiner ofc=model.getOfc();
  CorpusStatistics cs=model.getCs();
  JointNlpFeatureExtractorPrm fePrm=model.getFePrm();
  exPrm.fgPrm.includeSrl=false;
  exPrm.fgPrm.dpPrm=new DepParseFactorGraphBuilderPrm();
  exPrm.fgPrm.dpPrm.linkVarType=VarType.PREDICTED;
  exPrm.fgPrm.dpPrm.grandparentFactors=false;
  exPrm.fgPrm.dpPrm.siblingFactors=false;
  exPrm.fgPrm.dpPrm.unaryFactors=true;
  exPrm.fgPrm.dpPrm.useProjDepTreeFactor=true;
  exPrm.fgPrm.dpPrm.pruneEdges=true;
  exPrm.fePrm=fePrm;
  JointNlpFgExamplesBuilder builder=new JointNlpFgExamplesBuilder(exPrm,ofc,cs,false);
  FgExampleList data=builder.getData(inputSents);
  log.info("String_Node_Str");
  int numEdgesTot=0;
  int numEdgesKept=0;
  Timer timer=new Timer();
  timer.start();
  for (int i=0; i < inputSents.size(); i++) {
    LFgExample ex=data.get(i);
    AnnoSentence inputSent=inputSents.get(i);
    JointNlpDecoder decoder=new JointNlpDecoder(dPrm);
    AnnoSentence predSent=decoder.decode(model,ex,inputSent);
    DepEdgeMask mask=predSent.getDepEdgeMask();
    if (mask != null) {
      if (inputSent.getDepEdgeMask() == null) {
        inputSent.setDepEdgeMask(mask);
      }
 else {
        inputSent.getDepEdgeMask().and(mask);
      }
    }
    numEdgesKept+=mask.getCount();
    int n=predSent.getWords().size();
    numEdgesTot+=n * n;
  }
  timer.stop();
  log.info(String.format("String_Node_Str",inputSents.getNumTokens() / timer.totSec()));
  int numEdgesPruned=numEdgesTot - numEdgesKept;
  log.info(String.format("String_Node_Str",numEdgesPruned,numEdgesTot,(double)numEdgesPruned / numEdgesTot));
}