* the capacity, it is doubled in size unless some other thread
   * holds the lock. If a hashed slot is empty, and lock is
   * available, a new Cell is created. Otherwise, if the slot
   * exists, a CAS is tried.  Retries proceed by "double hashing",
   * using a secondary hash (Marsaglia XorShift) to try to find a
   * free slot.
   *
   * The table size is capped because, when there are more threads

   * the capacity, it is doubled in size unless some other thread
   * holds the lock. If a hashed slot is empty, and lock is
   * available, a new Cell is created. Otherwise, if the slot
   * exists, a CAS is tried.  Retries proceed by "double hashing",
   * using a secondary hash (Marsaglia XorShift) to try to find a
   * free slot.
   *
   * The table size is capped because, when there are more threads

   * the capacity, it is doubled in size unless some other thread
   * holds the lock. If a hashed slot is empty, and lock is
   * available, a new Cell is created. Otherwise, if the slot
   * exists, a CAS is tried.  Retries proceed by "double hashing",
   * using a secondary hash (Marsaglia XorShift) to try to find a
   * free slot.
   *
   * The table size is capped because, when there are more threads

      int hash = element.hashCode();
      for (int j = Hashing.smear(hash); ; j++) {
        int index = j & mask;
        Object value = table[index];
        if (value == null) {
          // Came to an empty slot. Put the element here.
          elements[uniques++] = element;
          table[index] = element;
          hashCode += hash;
          break;
        } else if (value.equals(element)) {
          break;

    //     fgha[c]|[b]de -> fgha[b]|[c]de. Because these two blocks are the same size, we are done.
    // The Dolphin algorithm is attractive because it does the fewest array reads and writes: each
    // array slot is read and written exactly once. However, it can have very poor memory locality:
    // benchmarking shows it can take 7 times longer than the other two in some cases. The other two

    /** Gets the key for this entry. */
    K getKey();

    /** Gets the value for the entry. */
    V getValue();
  }

  /*
   * Note: the following classes have a lot of duplicate code. It sucks, but it saves a lot of
   * memory. If only Java had mixins!
   */

  /** Base class for {@link InternalEntry} implementations for strong keys. */

    }

    // Some better conventions for the test poms needs to be created and each of these tests
    // that represent a verification of a specification item needs to be a couple lines at most.
    // The expressions help a lot, but we need a clean to pick up a directory of POMs, automatically load
    // them into a resolver, create the expression to extract the data to validate the Model, and the URI

    assertEquals(2, copy.size());
    assertSame(copy, copy.iterator().next().member);
  }

  /*
   * The behavior of toString() and iteration is tested by LinkedHashMultiset,
   * which shares a lot of code with HashMultiset and has deterministic
   * iteration order.
   */

 * string formatting itself should not be a concern.
 *
 * <p>As with any performance concerns, you should consider profiling your code (in a production
 * environment if possible) before spending a lot of effort on tweaking a particular element.
 *
 * <h3>Other types of preconditions</h3>
 *
 * <p>Not every type of precondition failure is supported by these methods. Continue to throw

   * instead.
   *
   * <p><b>Performance note:</b> {@link ArrayList} and {@link java.util.ArrayDeque} consistently
   * outperform {@code LinkedList} except in certain rare and specific situations. Unless you have
   * spent a lot of time benchmarking your specific needs, use one of those instead.
   *
   * <p><b>Note:</b> this method is now unnecessary and should be treated as deprecated. Instead,