*
 * <p>Unlike {@code java.util.HashMap}, iteration is only proportional to the actual {@code size()},
 * which is optimal, and <i>not</i> the size of the internal hashtable, which could be much larger
 * than {@code size()}. Furthermore, this structure places significantly reduced load on the garbage
 * collector by only using a constant number of internal objects.
 *

   * @return the value with the specified row and column
   * @throws IndexOutOfBoundsException if either index is negative, {@code rowIndex} is greater than
   *     or equal to the number of allowed row keys, or {@code columnIndex} is greater than or equal
   *     to the number of allowed column keys
   */
  public @Nullable V at(int rowIndex, int columnIndex) {

     * and the arithmetic mean is always higher than the geometric mean.
     *
     * b) this iteration converges to floor(sqrt(x)). In fact, the number of correct digits doubles
     * with each iteration, so this algorithm takes O(log(digits)) iterations.
     *
     * We start out with a double-precision approximation, which may be higher or lower than the

              "estimated size of spliterator after trySplit (%s) is larger than original size (%s)",
              spliterator.estimateSize(), originalSize));
    }
    if (trySplit != null) {
      if (trySplit.estimateSize() > originalSize) {
        fail(
            format(
                "estimated size of trySplit result (%s) is larger than original size (%s)",
                trySplit.estimateSize(), originalSize));

              "estimated size of spliterator after trySplit (%s) is larger than original size (%s)",
              spliterator.estimateSize(), originalSize));
    }
    if (trySplit != null) {
      if (trySplit.estimateSize() > originalSize) {
        fail(
            format(
                "estimated size of trySplit result (%s) is larger than original size (%s)",
                trySplit.estimateSize(), originalSize));

   *
   * <p>Among the improvements that this method and {@code LoadingCache.get(K)} both provide are:
   *
   * <ul>
   *   <li>{@linkplain LoadingCache#get(Object) awaiting the result of a pending load} rather than
   *       starting a redundant one
   *   <li>eliminating the error-prone caching boilerplate
   *   <li>tracking load {@linkplain #stats statistics}
   * </ul>
   *

  /**
   * Returns a view of a slice of this byte source that is at most {@code length} bytes long
   * starting at the given {@code offset}. If {@code offset} is greater than the size of this
   * source, the returned source will be empty. If {@code offset + length} is greater than the size
   * of this source, the returned source will contain the slice starting at {@code offset} and
   * ending at the end of this source.
   *

     * <p>
     * There are no predefined minimum or maximum values, but it's recommended
     * to use values that allow for future adjustments (e.g., using values
     * like 100, 200, 300 rather than consecutive numbers).
     *
     * @return the priority value for ordering
     */
    int value();

   * in the other.
   */
  SortedMultiset<E> descendingMultiset();

  /**
   * Returns a view of this multiset restricted to the elements less than {@code upperBound},
   * optionally including {@code upperBound} itself. The returned multiset is a view of this
   * multiset, so changes to one will be reflected in the other. The returned multiset supports all

   * in the other.
   */
  SortedMultiset<E> descendingMultiset();

  /**
   * Returns a view of this multiset restricted to the elements less than {@code upperBound},
   * optionally including {@code upperBound} itself. The returned multiset is a view of this
   * multiset, so changes to one will be reflected in the other. The returned multiset supports all