// methods of this class.
  private long count = 0;
  private double mean = 0.0; // any finite value will do, we only use it to multiply by zero for sum
  private double sumOfSquaresOfDeltas = 0.0;
  private double min = NaN; // any value will do
  private double max = NaN; // any value will do

  /** Adds the given value to the dataset. */
  public void add(double value) {

  }

  public void testToImmutableMapMerging() {
    Collector<Entry<AnEnum, Integer>, ?, ImmutableMap<AnEnum, Integer>> collector =
        toImmutableEnumMap(Entry::getKey, Entry::getValue, Integer::sum);
    Equivalence<ImmutableMap<AnEnum, Integer>> equivalence =
        Equivalence.equals().<Entry<AnEnum, Integer>>pairwise().onResultOf(ImmutableMap::entrySet);
    CollectorTester.of(collector, equivalence)

	if ns.IdentifierMaxLength == 0 {
		ns.IdentifierMaxLength = 64
	}

	if utf8.RuneCountInString(formattedName) > ns.IdentifierMaxLength {
		h := sha1.New()
		h.Write([]byte(formattedName))
		bs := h.Sum(nil)

		formattedName = formattedName[0:ns.IdentifierMaxLength-8] + hex.EncodeToString(bs)[:8]
	}
	return formattedName
}

var (
	// https://github.com/golang/lint/blob/master/lint.go#L770

import java.util.stream.DoubleStream;
import java.util.stream.IntStream;
import java.util.stream.LongStream;
import org.jspecify.annotations.Nullable;

/**
 * A bundle of statistical summary values -- sum, count, mean/average, min and max, and several
 * forms of variance -- that were computed from a single set of zero or more floating-point values.
 *
 * <p>There are two ways to obtain a {@code Stats} instance:
 *
 * <ul>

        }

        // Calculate moving average (simple approach)
        if (!responseTimeHistory.isEmpty()) {
            long sum = responseTimeHistory.stream().mapToLong(Long::longValue).sum();
            avgResponseTime.set(sum / responseTimeHistory.size());

            // Calculate 95th percentile

      expectAddFailure(multiset, entry);
    }
  }

  private static int totalSize(Iterable<? extends Entry<?>> entries) {
    int sum = 0;
    for (Entry<?> entry : entries) {
      sum += entry.getCount();
    }
    return sum;
  }

  private enum SubMultisetSpec {
    TAIL_CLOSED {
      @Override
      <E> List<Entry<E>> expectedEntries(int targetEntry, List<Entry<E>> entries) {

		if err != nil {
			t.Fatalf("%s : %s", instanceType, err.Error())
		}

		for _, object := range testCase.objectToUploads {
			md5Bytes := md5.Sum([]byte(object.content))
			oi, err := obj.PutObject(context.Background(), testCase.bucketName, object.name, mustGetPutObjReader(t, strings.NewReader(object.content),

        regA(builder);
        return builder;
    }

    protected SumAggregationBuilder regSumA(String name, String field) {
        SumAggregationBuilder builder = AggregationBuilders.sum(name).field(field);
        regA(builder);
        return builder;
    }

    protected ExtendedStatsAggregationBuilder regExtendedStatsA(String name, String field) {

 * operations at random. Each thread keeps track of the per-key deltas that it's directly
 * responsible for; after all threads have completed, we sum the per-key deltas and compare to the
 * existing multiset values.
 *
 * @author mike nonemacher
 */

@NullUnmarked
public class ConcurrentHashMultisetBasherTest extends TestCase {

			nil, nil),
		prometheus.GaugeValue,
		float64(offlineDisks.Sum()),
	)

	// MinIO Total Disks per node
	ch <- prometheus.MustNewConstMetric(
		prometheus.NewDesc(
			prometheus.BuildFQName(minioNamespace, "drives", "total"),
			"Total number of drives for current MinIO server instance",
			nil, nil),
		prometheus.GaugeValue,
		float64(totalDisks.Sum()),
	)

	for _, disk := range server.Disks {