}
	// Prefer newest modtime.
	if x.ModTime != o.ModTime {
		return x.ModTime > o.ModTime
	}

	// The following doesn't make too much sense, but we want sort to be consistent nonetheless.
	// Prefer lower types
	if x.Type != o.Type {
		return x.Type < o.Type
	}
	// Consistent sort on signature
	if v := bytes.Compare(x.Signature[:], o.Signature[:]); v != 0 {
		return v > 0
	}
	// On ID mismatch

// input DN, as LDAP equality is not a simple Golang string equality. However,
// we assume the value returned by the LDAP server is canonical. Additionally,
// the attribute type names in the DN are lower-cased.
//
// Return values:
//
// If the DN is found, the normalized (string) value and any requested
// attributes are returned and error is nil.
//

	sqlFnUTCNow      FuncName = "UTCNOW"

	// String
	sqlFnCharLength      FuncName = "CHAR_LENGTH"
	sqlFnCharacterLength FuncName = "CHARACTER_LENGTH"
	sqlFnLower           FuncName = "LOWER"
	sqlFnSubstring       FuncName = "SUBSTRING"
	sqlFnTrim            FuncName = "TRIM"
	sqlFnUpper           FuncName = "UPPER"
)

var (
	errUnimplementedCast = errors.New("This cast not yet implemented")

 *
 * <p><b>For users targeting Android API level 24 or higher:</b> This class will eventually
 * implement {@code BiPredicate<T, T>} (as it does in the main Guava artifact), but we currently
 * target a lower API level. In the meantime, if you have support for method references you can use
 * an equivalence as a bi-predicate like this: {@code myEquivalence::equivalent}.
 *
 * @author Bob Lee
 * @author Ben Yu

  // should be collected, as well as to actually change the replica count.
  optional CrossVersionObjectReference scaleTargetRef = 1;

  // minReplicas is the lower limit for the number of replicas to which the autoscaler
  // can scale down.  It defaults to 1 pod.  minReplicas is allowed to be 0 if the
  // alpha feature gate HPAScaleToZero is enabled and at least one Object or External

    assertMean(2, 1, 3);

    assertMean(-2, -3, -1);
    assertMean(0, -1, 1);
    assertMean(1, -1, 3);
    assertMean((1 << 30) - 1, -1, Integer.MAX_VALUE);

    // Even-sized ranges should prefer the lower mean
    assertMean(2, 1, 4);
    assertMean(-3, -4, -1);
    assertMean(0, -1, 2);
    assertMean(0, Integer.MIN_VALUE + 2, Integer.MAX_VALUE);
    assertMean(0, 0, 1);
    assertMean(-1, -1, 0);

     * with each iteration, so this algorithm takes O(log(digits)) iterations.
     *
     * We start out with a double-precision approximation, which may be higher or lower than the
     * true value. Therefore, we perform at least one Newton iteration to get a guess that's
     * definitely >= floor(sqrt(x)), and then continue the iteration until we reach a fixed point.
     */

   * value} is greater than {@code max}, {@code max} is returned.
   *
   * @param value the {@code char} value to constrain
   * @param min the lower bound (inclusive) of the range to constrain {@code value} to
   * @param max the upper bound (inclusive) of the range to constrain {@code value} to
   * @throws IllegalArgumentException if {@code min > max}
   * @since 21.0

   * value} is greater than {@code max}, {@code max} is returned.
   *
   * @param value the {@code short} value to constrain
   * @param min the lower bound (inclusive) of the range to constrain {@code value} to
   * @param max the upper bound (inclusive) of the range to constrain {@code value} to
   * @throws IllegalArgumentException if {@code min > max}
   * @since 21.0

   * value} is greater than {@code max}, {@code max} is returned.
   *
   * @param value the {@code short} value to constrain
   * @param min the lower bound (inclusive) of the range to constrain {@code value} to
   * @param max the upper bound (inclusive) of the range to constrain {@code value} to
   * @throws IllegalArgumentException if {@code min > max}
   * @since 21.0