// to the given dividend, so that we don't have half of our divisions being
  // trivial because the divisor is bigger than the dividend.
  // Using remainder here does not give us a uniform distribution but it should
  // not have a big impact on the measurement.
  private static long randomDivisor(long dividend) {
    long r = randomSource.nextLong();
    if (dividend == -1) {

      new RegularImmutableMap<>((Entry<Object, Object>[]) ImmutableMap.EMPTY_ENTRY_ARRAY, null, 0);

  /**
   * Closed addressing tends to perform well even with high load factors. Being conservative here
   * ensures that the table is still likely to be relatively sparse (hence it misses fast) while
   * saving space.
   */
  @VisibleForTesting static final double MAX_LOAD_FACTOR = 1.2;

  /**

How to contribute
=================

Thank you so much for wanting to contribute to Guava! Here are a few important
things you should know about contributing:

1.  API changes require discussion, use cases, etc. Code comes later.
2.  Pull requests are great for small fixes for bugs, documentation, etc.
3.  Pull requests are not merged directly into the master branch.
4.  Code contributions require signing a Google CLA.

API changes
-----------

        # changing the positional parameters here affects neither the number of
        # iterations, nor the values presented in `arg`.
        shift                   # remove old arg
        set -- "$@" "$arg"      # push replacement arg
    done
fi


# Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.

    return result;
  }

  /*
   * For discussion of the safety of the following methods for operating on predecessors and
   * successors, see the comments near the end of CompactHashMap, noting that the methods here call
   * requirePredecessors() and requireSuccessors(), which are defined at the end of this file.
   */

  private int getPredecessor(int entry) {
    return requirePredecessors()[entry] - 1;
  }

    // See Dispatcher.LegacyAsyncDispatcher for an explanation of why there aren't really any
    // useful testable guarantees about the behavior of that dispatcher in a multithreaded
    // environment. Here we simply test that all the expected dispatches happened in some order.
    assertThat(dispatchedSubscribers).containsExactly(i1, i2, i3, s1, s1, s1, s1, s2, s2, s2, s2);
  }

  public void testImmediateDispatcher() {

  // to the given dividend, so that we don't have half of our divisions being
  // trivial because the divisor is bigger than the dividend.
  // Using remainder here does not give us a uniform distribution but it should
  // not have a big impact on the measurement.
  private static long randomDivisor(long dividend) {
    long r = randomSource.nextLong();
    if (dividend == -1) {

   * analysis that that means "plain {@code T}" rather than the inferred type {@code @Nullable T}.
   * (And even if annotations on local variables were permitted as an optional hint, no annotation
   * would be the right tool for the job here: {@code @Nullable} is the annotation that we're trying
   * to get rid of, and {@code @NonNull} would be wrong for our use case for the same reason as

              builderWithKeys.treeSetValues(),
              builderWithKeys.enumSetValues(RoundingMode.class))) {
        /*
         * Temporarily inlining SerializableTester here for obscure internal reasons.
         */
        reserializeAndAssert(builder.build());
      }
    }
  }

  @GwtIncompatible
  @J2ktIncompatible

      @Override
      public int hashCode() {
        return 1;
      }
    }
  }

  private static void assertContains(String expectedSubstring, String actual) {
    // TODO(kevinb): use a Truth assertion here
    if (!actual.contains(expectedSubstring)) {
      fail("expected <" + actual + "> to contain <" + expectedSubstring + ">");
    }
  }