int j = i & ARRAY_MASK;
      tmp += LongMath.sqrt(positive[j], mode);
    }
    return tmp;
  }

  @Benchmark
  int divide(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += LongMath.divide(longs[j], nonzero[j], mode);
    }
    return tmp;
  }

        assertEquals(0x0010, response.getAttributes());
        // getLastWriteTime returns lastWriteTime (from readUTime) + serverTimeZoneOffset
        // readUTime multiplies the seconds value by 1000, and writeUTime divides milliseconds by 1000
        // So the round-trip should preserve the milliseconds value
        assertEquals(sampleTimeMillis + serverTimeZoneOffset, response.getLastWriteTime());
        assertEquals(1024, response.getSize());

        result *= i;
      }
      return BigInteger.valueOf(result);
    }

    /*
     * We want each multiplication to have both sides with approximately the same number of digits.
     * Currently, we just divide the range in half.
     */
    int mid = (n1 + n2) >>> 1;
    return oldSlowFactorial(n1, mid).multiply(oldSlowFactorial(mid, n2));
  }

  @Benchmark
  int slowFactorial(int reps) {
    int tmp = 0;

    int bytesToCopy = bufferSize - buffer.position();
    for (int i = 0; i < bytesToCopy; i++) {
      buffer.put(readBuffer.get());
    }
    munch(); // buffer becomes empty here, since chunkSize divides bufferSize

    // Now process directly from the rest of the input buffer
    while (readBuffer.remaining() >= chunkSize) {
      process(readBuffer);
    }

    }

    private double singleQuantileFromSorted(int index, int scale, double[] dataset) {
      long numerator = (long) index * (dataset.length - 1);
      int positionFloor = (int) LongMath.divide(numerator, scale, RoundingMode.DOWN);
      int remainder = (int) (numerator - positionFloor * scale);
      if (remainder == 0) {
        return dataset[positionFloor];
      } else {

      BigInteger.valueOf(Integer.MAX_VALUE)
          .multiply(BigInteger.valueOf(3L))
          .divide(BigInteger.valueOf(4L))
          .doubleValue();
  static final double LARGE_INTEGER_VALUES_POPULATION_VARIANCE =
      BigInteger.valueOf(Integer.MAX_VALUE)
          .multiply(BigInteger.valueOf(Integer.MAX_VALUE))
          .divide(BigInteger.valueOf(16L))
          .doubleValue();

        if (b != 0) {
          UnsignedLong aUnsigned = UnsignedLong.fromLongBits(a);
          UnsignedLong bUnsigned = UnsignedLong.fromLongBits(b);
          long expected =
              aUnsigned.bigIntegerValue().divide(bUnsigned.bigIntegerValue()).longValue();
          UnsignedLong unsignedDiv = aUnsigned.dividedBy(bUnsigned);
          assertThat(unsignedDiv.longValue()).isEqualTo(expected);
        }
      }
    }
  }

            final BigInteger firstBigInt = BigInteger.valueOf(first);
            BigInteger completeBigInt = lastBigInt.add(firstBigInt.shiftLeft(32));
            completeBigInt = completeBigInt.divide(BigInteger.valueOf(10000L));
            completeBigInt = completeBigInt.add(BigInteger.valueOf(-SmbConstants.MILLISECONDS_BETWEEN_1970_AND_1601));
            date = new Date(completeBigInt.longValue());
        }

      // non-negative int, we can do long-arithmetic on index * (dataset.length - 1) / scale to get
      // a rounded ratio and a remainder which can be expressed as ints, without risk of overflow:
      int quotient = (int) LongMath.divide(numerator, scale, RoundingMode.DOWN);
      int remainder = (int) (numerator - (long) quotient * scale);
      selectInPlace(quotient, dataset, 0, dataset.length - 1);
      if (remainder == 0) {

import static com.google.common.base.Preconditions.checkPositionIndexes;
import static com.google.common.base.Preconditions.checkState;
import static com.google.common.math.IntMath.divide;
import static com.google.common.math.IntMath.log2;
import static java.lang.Math.max;
import static java.lang.Math.min;
import static java.math.RoundingMode.CEILING;
import static java.math.RoundingMode.FLOOR;