}

        ComparisonChain classify(int result) {
          return (result < 0) ? LESS : (result > 0) ? GREATER : ACTIVE;
        }

        @Override
        public int result() {
          return 0;
        }
      };

  private static final ComparisonChain LESS = new InactiveComparisonChain(-1);

  private static final ComparisonChain GREATER = new InactiveComparisonChain(1);

   * until a nonzero result is found; imposes "dictionary order." If the end of one iterable is
   * reached, but not the other, the shorter iterable is considered to be less than the longer one.
   * For example, a lexicographical natural ordering over integers considers {@code [] < [1] < [1,
   * 1] < [1, 2] < [2]}.
   *

 *
 * <p>The time taken to compute multiple quantiles on the same dataset using {@link Scale#indexes
 * indexes} is generally less than the total time taken to compute each of them separately, and
 * sometimes much less. For example, on a large enough dataset, computing the 90th and 99th
 * percentiles together takes about 55% as long as computing them separately.
 *

  @CheckForNull
  public abstract C next(C value);

  /**
   * Returns the unique greatest value of type {@code C} that is less than {@code value}, or {@code
   * null} if none exists. Inverse operation to {@link #next}.
   *
   * @param value any value of type {@code C}
   * @return the greatest value less than {@code value}, or {@code null} if {@code value} is {@code
   *     minValue()}
   */
  @CheckForNull

      throw new ArithmeticException("ceilingPowerOfTwo(" + x + ") is not representable as a long");
    }
    return 1L << -Long.numberOfLeadingZeros(x - 1);
  }

  /**
   * Returns the largest power of two less than or equal to {@code x}. This is equivalent to {@code
   * checkedPow(2, log2(x, FLOOR))}.
   *
   * @throws IllegalArgumentException if {@code x <= 0}
   * @since 20.0
   */

  }

  public void testExpectedFpp() {
    BloomFilter<Object> bf = BloomFilter.create(HashTestUtils.BAD_FUNNEL, 10, 0.03);
    double fpp = bf.expectedFpp();
    assertEquals(0.0, fpp);
    // usually completed in less than 200 iterations
    while (fpp != 1.0) {
      boolean changed = bf.put(new Object());
      double newFpp = bf.expectedFpp();
      // if changed, the new fpp is strictly higher, otherwise it is the same

@GwtCompatible(emulated = true)
@ElementTypesAreNonnullByDefault
public abstract class FluentFuture<V extends @Nullable Object>
    extends GwtFluentFutureCatchingSpecialization<V> {

  /**
   * A less abstract subclass of AbstractFuture. This can be used to optimize setFuture by ensuring
   * that {@link #get} calls exactly the implementation of {@link AbstractFuture#get}.
   */

        || (stimuli.length >= 5 && removes > 2)) {
      // removes are the most expensive thing to test, since they often throw exceptions with stack
      // traces, so we test them a bit less aggressively
      return;
    }

    MultiExceptionListIterator reference = new MultiExceptionListIterator(expectedElements);
    I target = newTargetIterator();
    for (int i = 0; i < stimuli.length; i++) {

      stopwatch.sleepMillis(rate * 1000);
      limiter.setRate(rate);
      long burst = measureTotalTimeMillis(limiter, oneSecWorthOfWork, new Random());
      // we allow one second worth of work to go in a burst (i.e. take less than a second)
      assertTrue(burst <= 1000);
      long afterBurst = measureTotalTimeMillis(limiter, oneSecWorthOfWork, new Random());
      // but work beyond that must take at least one second

      ValueEntry<K, V> entry) {
    succeedsInMultimap(entry.getPredecessorInMultimap(), entry.getSuccessorInMultimap());
  }

  /**
   * LinkedHashMultimap entries are in no less than three coexisting linked lists: a bucket in the
   * hash table for a {@code Set<V>} associated with a key, the linked list of insertion-ordered