assertThat(rangeSet.asRanges()).isEmpty();
    } else if (a.isEmpty()) {
      assertThat(rangeSet.asRanges()).contains(b);
    } else if (b.isEmpty()) {
      assertThat(rangeSet.asRanges()).contains(a);
    } else if (a.isConnected(b)) {
      assertThat(rangeSet.asRanges()).containsExactly(a.span(b));
    } else {
      if (a.lowerEndpoint() < b.lowerEndpoint()) {

        return n;
      default:
        if (n < factorials.length) {
          return factorials[n] / (factorials[k] * factorials[n - k]);
        } else if (k >= biggestBinomials.length || n > biggestBinomials[k]) {
          return Long.MAX_VALUE;
        } else if (k < biggestSimpleBinomials.length && n <= biggestSimpleBinomials[k]) {
          // guaranteed not to overflow
          long result = n--;

    } else {
      return Collections.unmodifiableSortedSet((SortedSet<E>) collection);
    }
  }

  @Override
  Collection<V> wrapCollection(@ParametricNullness K key, Collection<V> collection) {
    if (collection instanceof NavigableSet) {
      return new WrappedNavigableSet(key, (NavigableSet<V>) collection, null);
    } else {

    } else {
      return Collections.unmodifiableSortedSet((SortedSet<E>) collection);
    }
  }

  @Override
  Collection<V> wrapCollection(@ParametricNullness K key, Collection<V> collection) {
    if (collection instanceof NavigableSet) {
      return new WrappedNavigableSet(key, (NavigableSet<V>) collection, null);
    } else {

      double populationCovariance = stats.populationCovariance();
      if (values.hasAnyNonFinite()) {
        assertWithMessage("population covariance of " + values).that(populationCovariance).isNaN();
      } else {
        assertWithMessage("population covariance of " + values)
            .that(populationCovariance)
            .isWithin(ALLOWED_ERROR)
            .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);

      double populationCovariance = stats.populationCovariance();
      if (values.hasAnyNonFinite()) {
        assertWithMessage("population covariance of " + values).that(populationCovariance).isNaN();
      } else {
        assertWithMessage("population covariance of " + values)
            .that(populationCovariance)
            .isWithin(ALLOWED_ERROR)
            .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);

  }

  private class ComposeFunction implements Function<Integer, String> {
    @Override
    public String apply(Integer input) {
      if (input.intValue() == VALID_INPUT_DATA) {
        return RESULT_DATA;
      } else {
        throw WRAPPED_EXCEPTION;
      }
    }
  }

  public void testFutureGetThrowsFunctionException() throws Exception {
    inputFuture.set(EXCEPTION_DATA);
    listener.assertException(WRAPPED_EXCEPTION);

    assertEqualInOrder(values, multimap().get(key));

    if (!values.isEmpty()) {
      assertEqualInOrder(values, multimap().asMap().get(key));
      assertFalse(multimap().isEmpty());
    } else {
      assertNull(multimap().asMap().get(key));
    }

    assertEquals(values.size(), multimap().get(key).size());
    assertEquals(values.size() > 0, multimap().containsKey(key));

    Timestamped<V> value = cachingHashMap.get(key);

    if (value == null) {
      statsCounter.recordMisses(1);
      return null;
    } else if (!isExpired(value)) {
      statsCounter.recordHits(1);
      value.updateTimestamp();
      return value.getValue();
    } else {
      statsCounter.recordEviction();
      statsCounter.recordMisses(1);
      // `key` was in the cache, so it's a K.

  }

  private void setSucceeds(int pred, int succ) {
    if (pred == ENDPOINT) {
      firstEntry = succ;
    } else {
      setSuccessor(pred, succ);
    }

    if (succ == ENDPOINT) {
      lastEntry = pred;
    } else {
      setPredecessor(succ, pred);
    }
  }

  @Override
  void insertEntry(