} else {
      ((int[]) table)[index] = entry;
    }
  }

  /**
   * Returns a larger power of 2 hashtable size given the current mask.
   *
   * <p>For hashtable sizes less than or equal to 32, the returned power of 2 is 4x the current
   * hashtable size to reduce expensive rehashing. Otherwise the returned power of 2 is 2x the
   * current hashtable size.
   */
  static int newCapacity(int mask) {

    } else {
      ((int[]) table)[index] = entry;
    }
  }

  /**
   * Returns a larger power of 2 hashtable size given the current mask.
   *
   * <p>For hashtable sizes less than or equal to 32, the returned power of 2 is 4x the current
   * hashtable size to reduce expensive rehashing. Otherwise the returned power of 2 is 2x the
   * current hashtable size.
   */
  static int newCapacity(int mask) {

  }

  private static final int MAX_TABLE_SIZE = Ints.MAX_POWER_OF_TWO;

  static int closedTableSize(int expectedEntries, double loadFactor) {
    // Get the recommended table size.
    // Round down to the nearest power of 2.
    expectedEntries = max(expectedEntries, 2);
    int tableSize = Integer.highestOneBit(expectedEntries);
    // Check to make sure that we will not exceed the maximum load factor.

   * the least significant bit zero is chosen. (In such cases, both of the nearest representable
   * values are even integers; this method returns the one that is a multiple of a greater power of
   * two.)
   *
   * @throws ArithmeticException if {@code mode} is {@link RoundingMode#UNNECESSARY} and {@code x}
   *     is not precisely representable as a {@code double}
   * @since 30.0
   */

        a full-time Guava team member. [Feedback](https://stackoverflow.com/a/4543114) from our
        users indicates that they really appreciate Guava's high power-to-weight ratio. It's
        important to us to keep Guava as easy to use and understand as we can. That means boiling
        features down to compact but powerful abstractions, and controlling feature bloat carefully.

  static AtomicLong requests = new AtomicLong(0);
  static AtomicLong misses = new AtomicLong(0);

  @BeforeExperiment
  void setUp() {
    // random integers will be generated in this range, then raised to the
    // power of (1/concentration) and floor()ed
    max = Ints.checkedCast((long) Math.pow(distinctKeys, concentration));

    cache =
        CacheBuilder.newBuilder()
            .concurrencyLevel(segments)

  static AtomicLong requests = new AtomicLong(0);
  static AtomicLong misses = new AtomicLong(0);

  @BeforeExperiment
  void setUp() {
    // random integers will be generated in this range, then raised to the
    // power of (1/concentration) and floor()ed
    max = Ints.checkedCast((long) Math.pow(distinctKeys, concentration));

    cache =
        CacheBuilder.newBuilder()
            .concurrencyLevel(segments)

  }

  private static final int MAX_TABLE_SIZE = Ints.MAX_POWER_OF_TWO;

  static int closedTableSize(int expectedEntries, double loadFactor) {
    // Get the recommended table size.
    // Round down to the nearest power of 2.
    expectedEntries = max(expectedEntries, 2);
    int tableSize = Integer.highestOneBit(expectedEntries);
    // Check to make sure that we will not exceed the maximum load factor.

   * the least significant bit zero is chosen. (In such cases, both of the nearest representable
   * values are even integers; this method returns the one that is a multiple of a greater power of
   * two.)
   *
   * @throws ArithmeticException if {@code mode} is {@link RoundingMode#UNNECESSARY} and {@code x}
   *     is not precisely representable as a {@code double}
   * @since 30.0
   */

  static boolean isFinite(double d) {
    return getExponent(d) <= MAX_EXPONENT;
  }

  static boolean isNormal(double d) {
    return getExponent(d) >= MIN_EXPONENT;
  }

  /*
   * Returns x scaled by a power of 2 such that it is in the range [1, 2). Assumes x is positive,
   * normal, and finite.
   */
  static double scaleNormalize(double x) {
    long significand = doubleToRawLongBits(x) & SIGNIFICAND_MASK;