"R0.34, R0.28, R0.25, R0.25", // #5
        "U4.25", // #6
        "R0.00, R0.72, R0.66, R0.59, R0.53, R0.47, R0.41", // #7
        "R0.34, R0.28, R0.25, R0.25"); // #7 (cont.), note, this matches #5
  }

  public void testWarmUpAndUpdateWithColdFactor() {
    RateLimiter limiter = RateLimiter.create(5.0, 4000, MILLISECONDS, 10.0, stopwatch);
    for (int i = 0; i < 8; i++) {

    table.put("foo", 4, 'a');
    table.put("cat", 1, 'b');
    table.clear();
    populate(table, data);
    return table;
  }

  @Override
  protected TreeBasedTable<String, Integer, Character> create(@Nullable Object... data) {
    TreeBasedTable<String, Integer, Character> table = TreeBasedTable.create();
    table.put("foo", 4, 'a');
    table.put("cat", 1, 'b');
    table.clear();
    populate(table, data);

 * granted immediately, but it is the <i>next</i> request that will experience extra throttling,
 * thus paying for the cost of the expensive task.
 *
 * @author Dimitris Andreou
 * @since 13.0
 */
// TODO(user): switch to nano precision. A natural unit of cost is "bytes", and a micro precision
// would mean a maximum rate of "1MB/s", which might be small in some cases.
@Beta
@J2ktIncompatible
@GwtIncompatible

    assertTrue(multimap.containsKey("foo"));
    assertFalse(multimap.containsKey("cat"));
    assertTrue(multimap.containsValue(1));
    assertFalse(multimap.containsValue(5));
    assertTrue(multimap.containsEntry("foo", 1));
    assertFalse(multimap.containsEntry("cat", 1));
    assertFalse(multimap.containsEntry("foo", 5));
    assertFalse(multimap.entries().isEmpty());

    assertTrue(multimap.containsKey("foo"));
    assertFalse(multimap.containsKey("cat"));
    assertTrue(multimap.containsValue(1));
    assertFalse(multimap.containsValue(5));
    assertTrue(multimap.containsEntry("foo", 1));
    assertFalse(multimap.containsEntry("cat", 1));
    assertFalse(multimap.containsEntry("foo", 5));
    assertFalse(multimap.entries().isEmpty());

          Tables.immutableCell("bar", 1, 'a'),
          Tables.immutableCell("bar", 2, 'b'),
          Tables.immutableCell("foo", 3, 'c'),
          Tables.immutableCell("bar", 1, 'b'),
          Tables.immutableCell("cat", 2, 'b'));
    }

    @Override
    public Set<Cell<String, Integer, Character>> create(Object... elements) {
      Table<String, Integer, Character> table = createTable();
      for (Object element : elements) {

 *
 * <p>The extra bookkeeping done by cycle detecting locks comes at some cost to performance.
 * Benchmarks (as of December 2011) show that:
 *
 * <ul>
 *   <li>for an unnested {@code lock()} and {@code unlock()}, a cycle detecting lock takes 38ns as
 *       opposed to the 24ns taken by a plain lock.
 *   <li>for nested locking, the cost increases with the depth of the nesting:
 *       <ul>

 *       add overloads that accept start and end indexes.
 *   <li>Access to all collection-based utilities via {@link #asList} (though at the cost of
 *       allocating garbage).
 * </ul>
 *
 * <p>Disadvantages compared to {@code int[]}:
 *
 * <ul>
 *   <li>Memory footprint has a fixed overhead (about 24 bytes per instance).

 *       add overloads that accept start and end indexes.
 *   <li>Access to all collection-based utilities via {@link #asList} (though at the cost of
 *       allocating garbage).
 * </ul>
 *
 * <p>Disadvantages compared to {@code double[]}:
 *
 * <ul>
 *   <li>Memory footprint has a fixed overhead (about 24 bytes per instance).

    // * The element with (index == from) should be kept.
    // * Everything with (index > from) has not been checked yet.

    // Check from the end of the list backwards (minimize expected cost of
    // moving elements when remove() is called). Stop before 'from' because
    // we already know that should be kept.
    for (int n = list.size() - 1; n > from; n--) {
      if (predicate.apply(list.get(n))) {