--- jsr166/src/jsr166y/RecursiveTask.java	2009/01/06 14:30:31	1.1
+++ jsr166/src/jsr166y/RecursiveTask.java	2009/07/23 23:07:57	1.7
@@ -10,20 +10,19 @@ package jsr166y;
  * Recursive result-bearing ForkJoinTasks.
  * <p> For a classic example, here is a task computing Fibonacci numbers:
  *
- * <pre>
- * class Fibonacci extends RecursiveTask&lt;Integer&gt; {
+ *  <pre> {@code
+ * class Fibonacci extends RecursiveTask<Integer> {
  *   final int n;
- *   Fibonnaci(int n) { this.n = n; }
+ *   Fibonacci(int n) { this.n = n; }
  *   Integer compute() {
- *     if (n &lt;= 1)
+ *     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>
+ * }}</pre>
  *
  * However, besides being a dumb way to compute Fibonacci functions
  * (there is a simple fast linear algorithm that you'd use in
@@ -31,24 +30,20 @@ package jsr166y;
  * 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.  
+ * sequentially solve rather than subdividing.
  *
+ * @since 1.7
+ * @author Doug Lea
  */
 public abstract class RecursiveTask<V> extends ForkJoinTask<V> {
 
     /**
-     * Empty contructor for use by subclasses.
-     */
-    protected RecursiveTask() {
-    }
-
-    /**
      * The result returned by compute method.
      */
     V result;
 
     /**
-     * The main computation performed by this task. 
+     * The main computation performed by this task.
      */
     protected abstract V compute();
 
@@ -61,7 +56,7 @@ public abstract class RecursiveTask<V> e
     }
 
     /**
-     * Implements execution conventions for RecursiveTask
+     * Implements execution conventions for RecursiveTask.
      */
     protected final boolean exec() {
         result = compute();