Program: 19993
Project: 19993
Buggy source:
/** 
 * A test routine
 */
public static void main(String[] args) throws Exception {
  String propsPath;
  if (args.length == 0) {
    propsPath="String_Node_Str";
  }
 else {
    propsPath=args[0];
  }
  Timer.start("String_Node_Str");
  SphinxProperties.initContext("String_Node_Str",new URL(propsPath));
  LargeTrigramModel sm=new LargeTrigramModel("String_Node_Str");
  Timer.stop("String_Node_Str");
  Timer.dumpAll();
  LogMath logMath=LogMath.getLogMath("String_Node_Str");
  BufferedReader reader=new BufferedReader(new InputStreamReader(System.in));
  String input;
  System.out.println("String_Node_Str" + sm.getMaxDepth());
  System.out.print("String_Node_Str");
  while ((input=reader.readLine()) != null) {
    StringTokenizer st=new StringTokenizer(input);
    List list=new ArrayList();
    while (st.hasMoreTokens()) {
      String tok=(String)st.nextToken();
      list.add(tok);
    }
    WordSequence wordSequence=new WordSequence(list);
    System.out.println("String_Node_Str" + wordSequence + "String_Node_Str"+ sm.getProbability(wordSequence)+ "String_Node_Str"+ logMath.logToLn(sm.getProbability(wordSequence))+ "String_Node_Str");
    System.out.print("String_Node_Str");
  }
  Timer timer=Timer.getTimer("String_Node_Str","String_Node_Str");
  List list1=new ArrayList();
  WordSequence ws1=new WordSequence("String_Node_Str","String_Node_Str","String_Node_Str");
  WordSequence ws2=new WordSequence("String_Node_Str","String_Node_Str","String_Node_Str");
  for (int i=0; i < 1000000; i++) {
    timer.start();
    sm.getProbability(ws1);
    timer.stop();
    timer.start();
    sm.getProbability(ws2);
    timer.stop();
  }
  Timer.dumpAll("String_Node_Str");
}

Fixed version (ground truth):
/** 
 * A test routine
 */
public static void main(String[] args) throws Exception {
  String propsPath;
  if (args.length == 0) {
    propsPath="String_Node_Str";
  }
 else {
    propsPath=args[0];
  }
  Timer.start("String_Node_Str");
  SphinxProperties.initContext("String_Node_Str",new URL(propsPath));
  LargeTrigramModel sm=new LargeTrigramModel("String_Node_Str");
  Timer.stop("String_Node_Str");
  Timer.dumpAll();
  LogMath logMath=LogMath.getLogMath("String_Node_Str");
  BufferedReader reader=new BufferedReader(new InputStreamReader(System.in));
  String input;
  System.out.println("String_Node_Str" + sm.getMaxDepth());
  System.out.print("String_Node_Str");
  while ((input=reader.readLine()) != null) {
    StringTokenizer st=new StringTokenizer(input);
    List list=new ArrayList();
    while (st.hasMoreTokens()) {
      String tok=(String)st.nextToken();
      list.add(tok);
    }
    WordSequence wordSequence=new WordSequence(list);
    float logProbability=sm.getProbability(wordSequence);
    System.out.println("String_Node_Str" + wordSequence + "String_Node_Str"+ logProbability+ "String_Node_Str"+ LogMath.logToLog(logProbability,logMath.getLogBase(),10.0f)+ "String_Node_Str");
    System.out.print("String_Node_Str");
  }
  Timer timer=Timer.getTimer("String_Node_Str","String_Node_Str");
  List list1=new ArrayList();
  WordSequence ws1=new WordSequence("String_Node_Str","String_Node_Str","String_Node_Str");
  WordSequence ws2=new WordSequence("String_Node_Str","String_Node_Str","String_Node_Str");
  for (int i=0; i < 1000000; i++) {
    timer.start();
    sm.getProbability(ws1);
    timer.stop();
    timer.start();
    sm.getProbability(ws2);
    timer.stop();
  }
  Timer.dumpAll("String_Node_Str");
}