}

  @Override
  protected Map<String, Integer> makePopulatedMap() {
    Table<Character, String, Integer> table = HashBasedTable.create();
    table.put('a', "one", 2);
    table.put('a', "two", 4);
    table.put('a', "three", 6);
    table.put('b', "four", 8);
    return Tables.transformValues(table, TableCollectionTest.DIVIDE_BY_2).row('a');
  }

    }

    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 {

    }

    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 {

  }

  /**
   * Verifies that the specified expected result is always produced by collecting the specified
   * inputs, regardless of how the elements are divided.
   */
  @SafeVarargs
  @CanIgnoreReturnValue
  @SuppressWarnings("nullness") // TODO(cpovirk): Remove after we fix whatever the bug is.

  // to the given dividend, so that we don't have half of our divisions being
  // trivial because the divisor is bigger than the dividend.
  // Using remainder here does not give us a uniform distribution but it should
  // not have a big impact on the measurement.
  private static long randomDivisor(long dividend) {
    long r = RANDOM_SOURCE.nextLong();
    if (dividend == -1) {
      return r;
    } else {

    return Tables.transformValues(table, DIVIDE_BY_2);
  }

  @Override
  protected Map<String, Integer> makePopulatedMap() {
    Table<String, Character, Integer> table = HashBasedTable.create();
    table.put("one", 'a', 1);
    table.put("two", 'a', 2);
    table.put("three", 'a', 3);
    table.put("four", 'b', 4);
    return Tables.transformValues(table, DIVIDE_BY_2).column('a');
  }

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

  @Benchmark
  int divide(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += BigIntegerMath.divide(nonzero1[j], nonzero2[j], mode).intValue();
    }
    return tmp;
  }

  @Benchmark
  long roundToDouble(int reps) {
    long tmp = 0;

        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);
    }

        if (b != 0) {
          UnsignedInteger aUnsigned = UnsignedInteger.fromIntBits(a);
          UnsignedInteger bUnsigned = UnsignedInteger.fromIntBits(b);
          int expected = aUnsigned.bigIntegerValue().divide(bUnsigned.bigIntegerValue()).intValue();
          UnsignedInteger unsignedDiv = aUnsigned.dividedBy(bUnsigned);
          assertThat(unsignedDiv.intValue()).isEqualTo(expected);
        }
      }
    }
  }