// If duplicates are allowed, this IdentityHashMap will record the final Entry for each
    // duplicated key. We will use this final Entry to overwrite earlier slots in the entries array
    // that have the same key. Then a second pass will remove all but the first of the slots that
    // have this Entry. The value in the map becomes false when this first entry has been copied, so
    // we know not to copy the remaining ones.

    }

    private @Nullable Object[] lastEntryForEachKey(
        @Nullable Object[] localAlternatingKeysAndValues, int size) {
      Set<Object> seenKeys = new HashSet<>();
      BitSet dups = new BitSet(); // slots that are overridden by a later duplicate key
      for (int i = size - 1; i >= 0; i--) {
        Object key = requireNonNull(localAlternatingKeysAndValues[2 * i]);
        if (!seenKeys.add(key)) {
          dups.set(i);

     */
    private static <K, V> Entry<K, V> @Nullable [] lastEntryForEachKey(
        Entry<K, V>[] entries, int size) {
      Set<K> seen = new HashSet<>();
      BitSet dups = new BitSet(); // slots that are overridden by a later duplicate key
      for (int i = size - 1; i >= 0; i--) {
        if (!seen.add(entries[i].getKey())) {
          dups.set(i);
        }
      }
      if (dups.isEmpty()) {

    // Add values up to 40. This covers cases like "square of a prime" and such.
    for (int i = 1; i <= 40; i++) {
      intValues.add(i);
    }
    // Now add values near 2^N for lots of values of N.
    for (int exponent : asList(2, 3, 4, 9, 15, 16, 17, 24, 25, 30)) {
      int x = 1 << exponent;
      intValues.add(x, x + 1, x - 1);
    }

    /*
     * TODO: cpovirk - Pre-size the HashMap based on the number of enum values? (But *not* based on
     * the number of entries in the map, as that makes it easy for hostile inputs to trigger lots of
     * allocation—not that any program should be deserializing hostile inputs to begin with!)
     */
    setDelegates(new EnumMap<K, V>(keyTypeOrObjectUnderJ2cl), new HashMap<V, K>());

    return new ExpiringMemoizingSupplier<>(delegate, toNanosSaturated(duration));
  }

  @VisibleForTesting
  @SuppressWarnings("GoodTime") // lots of violations
  static final class ExpiringMemoizingSupplier<T extends @Nullable Object>
      implements Supplier<T>, Serializable {
    private transient Object lock = new Object();

    final Supplier<T> delegate;

    return new ExpiringMemoizingSupplier<>(delegate, toNanosSaturated(duration));
  }

  @VisibleForTesting
  @SuppressWarnings("GoodTime") // lots of violations
  static final class ExpiringMemoizingSupplier<T extends @Nullable Object>
      implements Supplier<T>, Serializable {
    private transient Object lock = new Object();

    final Supplier<T> delegate;

    //     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

        // We only ever register ArrayReferences with the queue so this is always safe.
        ArrayReference<? extends L> arrayRef = (ArrayReference<? extends L>) ref;
        // Try to clear out the array slot, n.b. if we fail that is fine, in either case the
        // arrayRef will be out of the array after this step.
        locks.compareAndSet(arrayRef.index, arrayRef, null);
      }
    }

    @Override

  /**
   * This is a less carefully-controlled version of {@link #testRemovalNotification_clear} - this is
   * a black-box test that tries to create lots of different thread-interleavings, and asserts that
   * each computation is affected by a call to {@code clear()} (and therefore gets passed to the