/**@class java.util.concurrent.RecursiveTask
@extends java.util.concurrent.ForkJoinTask

 A recursive result-bearing {@link java.util.concurrent.ForkJoinTask}.

 <p>For a classic example, here is a task computing Fibonacci numbers:

 <pre> {@code
 class Fibonacci extends RecursiveTask<Integer> {
   final int n;
   Fibonacci(int n) { this.n = n; }
   protected Integer compute() {
     if (n <= 1)
       return n;
     Fibonacci f1 = new Fibonacci(n - 1);
     f1.fork();
     Fibonacci f2 = new Fibonacci(n - 2);
     return f2.compute() + f1.join();
   }
 }}</pre>

 However, besides being a dumb way to compute Fibonacci functions
 (there is a simple fast linear algorithm that you'd use in
 practice), this is likely to perform poorly because the smallest
 subtasks are too small to be worthwhile splitting up. Instead, as
 is the case for nearly all fork/join applications, you'd pick some
 minimum granularity size (for example 10 here) for which you always
 sequentially solve rather than subdividing.

 @since 1.7
 @author Doug Lea
*/
var RecursiveTask = {

/**
*/
getRawResult : function(  ) {},


};