if (headerCount + 1 > dynamicTable.size) { // Need to grow the dynamic table.
            val doubled = arrayOfNulls<Header>(dynamicTable.size * 2)
            System.arraycopy(dynamicTable, 0, doubled, dynamicTable.size, dynamicTable.size)
            nextHeaderIndex = dynamicTable.size - 1
            dynamicTable = doubled
          }
          index = nextHeaderIndex--
          dynamicTable[index] = entry

   * #create(Funnel, int, double)}, or smaller. If it is significantly higher, it is usually the
   * case that too many elements (more than expected) have been put in the {@code BloomFilter},
   * degenerating it.
   *
   * @since 14.0 (since 11.0 as expectedFalsePositiveProbability())
   */
  public double expectedFpp() {
    return Math.pow((double) bits.bitCount() / bitSize(), numHashFunctions);
  }

    public void setAvailable_PercentileRanks(double[] values) {
        setAvailable_PercentileRanks(values, null);
    }

    public void setAvailable_PercentileRanks(double[] values, ConditionOptionCall<PercentileRanksAggregationBuilder> opLambda) {
        setAvailable_PercentileRanks("available", values, opLambda);
    }

    public void setAvailable_PercentileRanks(String name, double[] values,

        Duration duration = Duration.between(resource.getStartTime(), MonotonicClock.now());
        long nanos = duration.toNanos();
        if (nanos > 0) {
            double seconds = nanos / (double) TimeUnit.SECONDS.toNanos(1); // Convert to fractional seconds
            double bytesPerSecond = contentLength / seconds;
            message.append(" at ");
            format.formatRate(message, bytesPerSecond);
        }

 *
 * @author Louis Wasserman
 */
@NullUnmarked
public class ApacheBenchmark {
  private enum Impl {
    GUAVA {
      @Override
      public double factorialDouble(int n) {
        return DoubleMath.factorial(n);
      }

      @Override
      public int gcdInt(int a, int b) {
        return IntMath.gcd(a, b);
      }

      @Override

    public void setAvailable_PercentileRanks(double[] values) {
        setAvailable_PercentileRanks(values, null);
    }

    public void setAvailable_PercentileRanks(double[] values, ConditionOptionCall<PercentileRanksAggregationBuilder> opLambda) {
        setAvailable_PercentileRanks("available", values, opLambda);
    }

    public void setAvailable_PercentileRanks(String name, double[] values,

    Set<Class<?>> primitives = Primitives.allPrimitiveTypes();
    assertThat(primitives)
        .containsExactly(
            boolean.class,
            byte.class,
            char.class,
            double.class,
            float.class,
            int.class,
            long.class,
            short.class,
            void.class);

  private static final String S2 = "44 one million";
  private static final String S3 = "Lowly laundry lefties";
  private static final String S4 = "89273487U#*&#";
  private static final Double D0 = 9.234d;
  private static final Double D1 = -1.2e55;

  @Benchmark
  int hashString_2(int reps) {
    int dummy = 0;
    for (int i = 0; i < reps; i++) {
      dummy += Objects.hashCode(S0, S1);
    }
    return dummy;
  }

  static int smearedHash(@Nullable Object o) {
    return smear((o == null) ? 0 : o.hashCode());
  }

  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);

   * result is chosen from those possibilities uniformly at random.
   *
   * <p>Zero is treated as having log2 == 0.
   */
  static double randomDouble(int maxExponent) {
    double result = RANDOM_SOURCE.nextDouble();
    result = Math.scalb(result, RANDOM_SOURCE.nextInt(maxExponent + 1));
    return RANDOM_SOURCE.nextBoolean() ? result : -result;
  }