*
 * <p>Keep a strong reference to this object until all of the associated referents have been
 * finalized. If this object is garbage collected earlier, the backing thread will not invoke {@code
 * finalizeReferent()} on the remaining references.
 *
 * <p>As an example of how this is used, imagine you have a class {@code MyServer} that creates a

 *
 * <p>Keep a strong reference to this object until all of the associated referents have been
 * finalized. If this object is garbage collected earlier, the backing thread will not invoke {@code
 * finalizeReferent()} on the remaining references.
 *
 * <p>As an example of how this is used, imagine you have a class {@code MyServer} that creates a

  public void add(double x, double y) {
    // We extend the recursive expression for the one-variable case at Art of Computer Programming
    // vol. 2, Knuth, 4.2.2, (16) to the two-variable case. We have two value series x_i and y_i.
    // We define the arithmetic means X_n = 1/n \sum_{i=1}^n x_i, and Y_n = 1/n \sum_{i=1}^n y_i.
    // We also define the sum of the products of the differences from the means

       * - columnIterator.remove() succeeded, so it must have returned a value, so it must have been
       * initialized by next() -- which initializes rowEntry, too.
       *
       * - rowEntry isn't cleared except below. If it was cleared below, then either
       *   columnIterator.remove() would have failed above (if the user hasn't called next() since
       *   then) or rowEntry would have been initialized by next() (as discussed above).
       */

   * safe to do so. The exact circumstances under which a copy will or will not be performed are
   * undocumented and subject to change.
   *
   * @throws IllegalArgumentException if two keys have the same value or two values have the same
   *     key
   * @throws NullPointerException if any key or value in {@code map} is null
   */
  public static <K, V> ImmutableBiMap<K, V> copyOf(Map<? extends K, ? extends V> map) {

    }

    // All of the seed values should have been visible, so we should have gotten removal
    // notifications for all of them.
    for (int i = 0; i < nSeededEntries; i++) {
      assertEquals("b" + i, removalNotifications.get("b" + i));
    }

    // Each of the values added to the map should either still be there, or have seen a removal
    // notification.

  }

  /**
   * Removes all mappings from this map whose values are zero.
   *
   * <p>This method is not atomic: the map may be visible in intermediate states, where some of the
   * zero values have been removed and others have not.
   */
  public void removeAllZeros() {
    Iterator<Entry<K, AtomicLong>> entryIterator = map.entrySet().iterator();
    while (entryIterator.hasNext()) {

   * An enum representing the state of a node during DFS. {@code PENDING} means that the node is on
   * the stack of the DFS, while {@code COMPLETE} means that the node and all its successors have
   * been already explored. Any node that has not been explored will not have a state at all.
   */
  private enum NodeVisitState {
    PENDING,
    COMPLETE
  }

         * large that doing the lookup is noticeably slower than redoing the work would be.
         *
         * Ideally we'd have a real eviction policy, but until we see a problem in practice, I hope
         * that this will suffice. I have not even benchmarked with different size limits.
         */
        if (validClasses.size() > 1000) {
          validClasses.clear();
        }

        // test whether the hash values have same output bits
        same |= ~(hash1 ^ hash2);
        // test whether the hash values have different output bits
        diff |= (hash1 ^ hash2);

        count++;
        // check whether we've exceeded the probabilistically
        // likely number of trials to have proven no funneling
        if (count > maxCount) {
          Assert.fail(