var commitRE = /^(?:\d+:)?([0-9a-f]{6,40})$/; // e.g "8486:ab29d2698a47" or "ab29d2698a47"
var gerritChangeIdRE = /^I[0-9a-f]{4,40}$/; // e.g. Id69c00d908d18151486007ec03da5495b34b05f5
var pkgRE = /^[a-z0-9_\/]+$/;

function urlForInput(t) {
    if (!t) {
        return null;
    }

    if (numericRE.test(t)) {
        if (t < 150000) {
            // We could use the golang.org/cl/ handler here, but

  /**
   * Returns a linear transformation giving the best fit to the data according to <a
   * href="http://mathworld.wolfram.com/LeastSquaresFitting.html">Ordinary Least Squares linear
   * regression</a> of {@code y} as a function of {@code x}. The count must be greater than one, and
   * either the {@code x} or {@code y} data must have a non-zero population variance (i.e. {@code

 * limitations under the License.
 */

package com.google.common.util.concurrent;

import static com.google.common.collect.Iterables.concat;

import com.google.common.base.Functions;
import com.google.common.base.Supplier;
import com.google.common.collect.ImmutableList;
import com.google.common.collect.Lists;
import com.google.common.collect.Maps;
import com.google.common.collect.Ordering;

 * limitations under the License.
 */

package com.google.common.collect;

import static java.util.Arrays.asList;

import com.google.common.base.Function;
import com.google.common.collect.Multiset.Entry;
import com.google.common.collect.testing.SetTestSuiteBuilder;
import com.google.common.collect.testing.TestStringSetGenerator;

 * limitations under the License.
 */

package com.google.common.util.concurrent;

import static com.google.common.collect.Iterables.concat;

import com.google.common.base.Functions;
import com.google.common.base.Supplier;
import com.google.common.collect.ImmutableList;
import com.google.common.collect.Lists;
import com.google.common.collect.Maps;
import com.google.common.collect.Ordering;

import java.util.Enumeration;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Locale;
import java.util.Map;
import java.util.Set;
import java.util.function.Function;

import org.apache.maven.internal.impl.model.DefaultInterpolator;

/**
 * Enhancement of the standard <code>Properties</code>
 * managing the maintain of comments, etc.
 */

	healthCheckClusterPath     = "/cluster"
	healthCheckClusterReadPath = "/cluster/read"
	healthCheckPathPrefix      = minioReservedBucketPath + healthCheckPath
)

// registerHealthCheckRouter - add handler functions for liveness and readiness routes.
func registerHealthCheckRouter(router *mux.Router) {
	// Healthcheck router
	healthRouter := router.PathPrefix(healthCheckPathPrefix).Subrouter()

class STSElement(object):
    """STS aware XML parsing class. Wraps a root element name and
    cElementTree.Element instance. Provides STS namespace aware parsing
    functions.

    """

    def __init__(self, root_name, element):
        self.root_name = root_name
        self.element = element

    @classmethod
    def fromstring(cls, root_name, data):

	// Owner represents unique ID for this instance, an owner who originally requested
	// the locked resource, useful primarily in figuring out stale locks.
	Owner string

	// Source contains the line number, function and file name of the code
	// on the client node that requested the lock.
	Source string `msgp:"omitempty"`

	// Quorum represents the expected quorum for this lock type.
	Quorum *int `msgp:"omitempty"`
}

  /**
   * Returns a linear transformation giving the best fit to the data according to <a
   * href="http://mathworld.wolfram.com/LeastSquaresFitting.html">Ordinary Least Squares linear
   * regression</a> of {@code y} as a function of {@code x}. The count must be greater than one, and
   * either the {@code x} or {@code y} data must have a non-zero population variance (i.e. {@code