}

  /**
   * Returns the minimum of the two values. If the values compare as 0, the first is returned.
   *
   * <p>The recommended solution for finding the {@code minimum} of some values depends on the type
   * of your data and the number of elements you have. Read more in the Guava User Guide article on
   * <a href="https://github.com/google/guava/wiki/CollectionUtilitiesExplained#comparators">{@code

  public void testLog2HalfEven() {
    for (BigInteger x : POSITIVE_BIGINTEGER_CANDIDATES) {
      int halfEven = BigIntegerMath.log2(x, HALF_EVEN);
      // Now figure out what rounding mode we should behave like (it depends if FLOOR was
      // odd/even).
      boolean floorWasEven = (BigIntegerMath.log2(x, FLOOR) & 1) == 0;
      assertEquals(BigIntegerMath.log2(x, floorWasEven ? HALF_DOWN : HALF_UP), halfEven);
    }
  }

  public void testLog2HalfEven() {
    for (BigInteger x : POSITIVE_BIGINTEGER_CANDIDATES) {
      int halfEven = BigIntegerMath.log2(x, HALF_EVEN);
      // Now figure out what rounding mode we should behave like (it depends if FLOOR was
      // odd/even).
      boolean floorWasEven = (BigIntegerMath.log2(x, FLOOR) & 1) == 0;
      assertEquals(BigIntegerMath.log2(x, floorWasEven ? HALF_DOWN : HALF_UP), halfEven);
    }
  }

   * depending on the implementation. For example, two {@link SetMultimap} instances with the same
   * key-value mappings are equal, but equality of two {@link ListMultimap} instances depends on the
   * ordering of the values for each key.
   *
   * <p>A non-empty {@link SetMultimap} cannot be equal to a non-empty {@link ListMultimap}, since

 *
 * <p>When calling {@link ScaleAndIndex#compute} (in {@linkplain ScaleAndIndexes#compute either
 * form}), the memory requirement is 8*N bytes for the copy of the dataset plus an overhead which is
 * independent of N (but depends on the quantiles being computed). When calling {@link
 * ScaleAndIndex#computeInPlace computeInPlace} (in {@linkplain ScaleAndIndexes#computeInPlace

      return div;
    }

    /*
     * Normal Java division rounds towards 0, consistently with RoundingMode.DOWN. We just have to
     * deal with the cases where rounding towards 0 is wrong, which typically depends on the sign of
     * p / q.
     *
     * signum is 1 if p and q are both nonnegative or both negative, and -1 otherwise.
     */
    int signum = 1 | (int) ((p ^ q) >> (Long.SIZE - 1));
    boolean increment;

    if (expected != actual) {
      fail("Expected for " + a + " " + op + " " + b + " = " + expected + ", but got " + actual);
    }
  }

  // Depends on the correctness of BigIntegerMath.factorial.
  public void testFactorial() {
    for (int n = 0; n <= 50; n++) {
      BigInteger expectedBig = BigIntegerMath.factorial(n);

      TestByteSource okSource = new TestByteSource(bytes);
      assertThrows(IOException.class, () -> okSource.copyTo(new TestByteSink(option)));
      // ensure stream was closed IF it was opened (depends on implementation whether or not it's
      // opened at all if sink.newOutputStream() throws).
      assertTrue(
          "stream not closed when copying to sink with option: " + option,

   * population, this is an estimator of the population standard deviation of the population which
   * is less biased than {@link #populationStandardDeviation()} (the unbiased estimator depends on
   * the distribution). The count must be greater than one.
   *
   * <p>This is not guaranteed to return zero when the dataset consists of the same value multiple

    List<Integer> fromList = Lists.newLinkedList(SOME_SEQUENTIAL_LIST);
    List<String> list = Lists.transform(fromList, SOME_FUNCTION);
    assertTransformIterator(list);
  }

  /**
   * This test depends on the fact that {@code AbstractSequentialList.iterator} transforms the
   * {@code iterator()} call into a call on {@code listIterator(int)}. This is fine because the
   * behavior is clearly documented so it's not expected to change.