* offering expected O(n + k log k) performance (worst case O(n log k)) for n calls to {@link
 * #offer} and a call to {@link #topK}, with O(k) memory. In comparison, quickselect has the same
 * asymptotics but requires O(n) memory, and a {@code PriorityQueue} implementation takes O(n log
 * k). In benchmarks, this implementation performs at least as well as either implementation, and
 * degrades more gracefully for worst-case input.
 *

   *     .collect(least(2, comparingInt(String::length)))
   * // returns {"foo", "quux"}
   * }</pre>
   *
   * <p>This {@code Collector} uses O(k) memory and takes expected time O(n) (worst-case O(n log
   * k)), as opposed to e.g. {@code Stream.sorted(comparator).limit(k)}, which currently takes O(n
   * log n) time and O(n) space.
   *
   * @throws IllegalArgumentException if {@code k < 0}
   * @since 22.0

   *     .collect(least(2, comparingInt(String::length)))
   * // returns {"foo", "quux"}
   * }</pre>
   *
   * <p>This {@code Collector} uses O(k) memory and takes expected time O(n) (worst-case O(n log
   * k)), as opposed to e.g. {@code Stream.sorted(comparator).limit(k)}, which currently takes O(n
   * log n) time and O(n) space.
   *
   * @throws IllegalArgumentException if {@code k < 0}
   */

  }

  @Override
  public boolean contains(@CheckForNull Object object) {
    if (object == null) {
      return false;
    }
    try {
      @SuppressWarnings("unchecked") // The worst case is usually CCE, which we catch.
      C c = (C) object;
      return range.contains(c);
    } catch (ClassCastException e) {
      return false;
    }
  }

  @Override

    // Raising this number slows the worst-case contains behavior, speeds up hashFloodingDetected,
    // and reduces the false-positive probability.
    static final int MAX_RUN_MULTIPLIER = 13;

    /**
     * Checks the whole hash table for poor hash distribution. Takes O(n) in the worst case, O(n /
     * log n) on average.
     *

   *       simply switch over to use the JDK implementation wholesale if probable hash flooding is
   *       detected, sacrificing the compactness guarantee in very rare cases in exchange for much
   *       more reliable worst-case behavior.
   *   <li>null, if no entries have yet been added to the map
   * </ul>
   */
  @CheckForNull private transient Object table;

  /**

   *       simply switch over to use the JDK implementation wholesale if probable hash flooding is
   *       detected, sacrificing the compactness guarantee in very rare cases in exchange for much
   *       more reliable worst-case behavior.
   *   <li>null, if no entries have yet been added to the map
   * </ul>
   */
  @CheckForNull private transient Object table;

  /**

   * negation is cheaper to precompute than the matcher itself; it tries to build small hash tables
   * for matchers that only match a few characters, and so on. In the worst-case scenario, it
   * constructs an eight-kilobyte bit array and queries that. In many situations this produces a
   * matcher which is faster to query than the original.
   */
  @GwtIncompatible // SmallCharMatcher

   * negation is cheaper to precompute than the matcher itself; it tries to build small hash tables
   * for matchers that only match a few characters, and so on. In the worst-case scenario, it
   * constructs an eight-kilobyte bit array and queries that. In many situations this produces a
   * matcher which is faster to query than the original.
   */
  @GwtIncompatible // SmallCharMatcher

// dropped from the byte slice with no replacement. The characters in s and the
// output are interpreted as UTF-8-encoded code points.
func Map(mapping func(r rune) rune, s []byte) []byte {
	// In the worst case, the slice can grow when mapped, making
	// things unpleasant. But it's so rare we barge in assuming it's
	// fine. It could also shrink but that falls out naturally.
	b := make([]byte, 0, len(s))