}

  @Override
  public Spliterator<E> spliterator() {
    return delegate.spliterator();
  }

  @Override
  public void forEach(Consumer<? super E> action) {
    delegate.forEach(action);
  }

  @Override
  public int size() {
    return delegate.size();
  }

  @Override
  public boolean contains(@CheckForNull Object object) {
    return delegate.contains(object);
  }

  @Override
  public int size() {
    return valueList.size();
  }

  @Override
  public void forEach(BiConsumer<? super K, ? super V> action) {
    checkNotNull(action);
    ImmutableList<K> keyList = keySet.asList();
    for (int i = 0; i < size(); i++) {
      action.accept(keyList.get(i), valueList.get(i));
    }
  }

  @Override
  @CheckForNull
  public V get(@CheckForNull Object key) {

   * us to the point of the next scheduling time, since we always maintain that. And what we mean by
   * "an unused RateLimiter" is also defined by that notion: when we observe that the
   * "expected arrival time of the next request" is actually in the past, then the difference (now -
   * past) is the amount of time that the RateLimiter was formally unused, and it is that amount of

   * State#NEW new}, it is {@linkplain State#TERMINATED terminated} without having been started nor
   * stopped. If the service has already been stopped, this method returns immediately without
   * taking action.
   *
   * @return this
   * @since 15.0
   */
  @CanIgnoreReturnValue
  Service stopAsync();

  /**
   * Waits for the {@link Service} to reach the {@linkplain State#RUNNING running state}.
   *

 *
 * <p>It is guaranteed that {@code encoding.decode(encoding.encode(x))} is always equal to {@code
 * x}, but the reverse does not necessarily hold.
 *
 * <table>
 * <caption>Encodings</caption>
 * <tr>
 * <th>Encoding
 * <th>Alphabet
 * <th>{@code char:byte} ratio
 * <th>Default padding
 * <th>Comments
 * <tr>
 * <td>{@link #base16()}
 * <td>0-9 A-F
 * <td>2.00
 * <td>N/A

     * at table entries if it is 0.
     *
     * - All (synchronized) write operations should write to the "count" field after structurally
     * changing any bin. The operations must not take any action that could even momentarily cause a
     * concurrent read operation to see inconsistent data. This is made easier by the nature of the

          # repo_token: ${{ secrets.SCORECARD_TOKEN }}

          # Public repositories:
          #   - Publish results to OpenSSF REST API for easy access by consumers
          #   - Allows the repository to include the Scorecard badge.
          #   - See https://github.com/ossf/scorecard-action#publishing-results.
          # For private repositories:

        backingEntries.remove();
        toRemove = null;
      }
    };
  }

  @Override
  public void forEachEntry(ObjIntConsumer<? super E> action) {
    checkNotNull(action);
    backingMap.forEach((element, count) -> action.accept(element, count.get()));
  }

  @Override
  public void clear() {
    for (Count frequency : backingMap.values()) {
      frequency.set(0);
    }

    1.0,
    Math.PI,
    (double) Integer.MAX_VALUE,
    (double) Long.MAX_VALUE,
    Double.MAX_VALUE,
    Double.POSITIVE_INFINITY,
    Double.NaN,
    Float.MAX_VALUE,
  };

  /** The notion of equality used by AtomicDouble */
  static boolean bitEquals(double x, double y) {
    return Double.doubleToRawLongBits(x) == Double.doubleToRawLongBits(y);
  }

  static void assertBitEquals(double x, double y) {

     * didn't see that discussed in the review, which included many other
     * changes: http://goo.gl/okTTdr
     *
     * TODO(cpovirk): decide what the best long-term action here is: force users
     * to suppress (as we do now), stop testing entrySet().add() at all, make
     * entrySet().add() tests tolerant of either behavior, introduce a map