}

// exponentialMovingAverage calculates the exponential moving average
func exponentialMovingAverage(beta, previousAvg, incrementAvg float64) float64 {
	return (1-beta)*incrementAvg + beta*previousAvg
}

// getExpMovingAvgBytesPerSecond returns the exponential moving average for the bucket/target in bytes
func (m *rateMeasurement) getExpMovingAvgBytesPerSecond() float64 {
	m.lock.Lock()

    /**
     * Builds a new min-max priority queue using the previously specified options, and having no
     * initial contents.
     */
    public <T extends B> MinMaxPriorityQueue<T> create() {
      return create(Collections.<T>emptySet());
    }

    /**
     * Builds a new min-max priority queue using the previously specified options, and having the
     * given initial elements.
     */

If <code>list</code> pointed to a cyclic list,
then the original program would never access <code>*p</code> or <code>*q</code>,
but the rewritten program would.
(Moving `*p` ahead would be safe if the compiler can prove `*p` will not panic;
moving `*q` ahead would also require the compiler proving that no other
goroutine can access `*q`.)
</p>

<p>
Not introducing data races also means not assuming that called functions

	sync.RWMutex                 // mutex for Cache
	mostRecentStatsMu sync.Mutex // mutex for mostRecentStats

	wlock sync.RWMutex // mutex for active workers

	movingAvgTicker *time.Ticker // Ticker for calculating moving averages
	wTimer          *time.Ticker // ticker for calculating active workers
	qTimer          *time.Ticker // ticker for calculating queue stats
}

func (r *ReplicationStats) trackEWMA() {
	for {
		select {

            }
            return buf.toString();
        }
    }

    public ArtifactVersion matchVersion(List<ArtifactVersion> versions) {
        // TODO could be more efficient by sorting the list and then moving along the restrictions in order?

        ArtifactVersion matched = null;
        for (ArtifactVersion version : versions) {
            if (containsVersion(version)) {

            }

            if (closed) {
              throw IOException("stream closed")
            } else if (readBuffer.size > 0L) {
              // Prepare to read bytes. Start by moving them to the caller's buffer.
              readBytesDelivered = readBuffer.read(sink, minOf(byteCount, readBuffer.size))
              readBytes.update(total = readBytesDelivered)

    Collection<String> collection = map.values();

    LenientSerializableTester.reserializeAndAssertElementsEqual(collection);
  }

  // TODO: Re-enable this test after moving to new serialization format in ImmutableMap.
  @J2ktIncompatible
  @GwtIncompatible // SerializableTester
  @SuppressWarnings("unchecked")

 *
 * This implementation uses an array for the dynamic table and a list for indexed entries. Dynamic
 * entries are added to the array, starting in the last position moving forward. When the array
 * fills, it is doubled.
 */
@Suppress("NAME_SHADOWING")
object Hpack {
  private const val PREFIX_4_BITS = 0x0f
  private const val PREFIX_5_BITS = 0x1f

	Rotational bool
	Metrics    DiskMetrics
	Error      string // carries the error over the network
}

// DiskMetrics has the information about XL Storage APIs
// the number of calls of each API and the moving average of
// the duration of each API.
type DiskMetrics struct {
	LastMinute              map[string]AccElem `json:"apiLatencies,omitempty"`
	APICalls                map[string]uint64  `json:"apiCalls,omitempty"`

    @Override
    public boolean contains(@CheckForNull Object target) {
      // Overridden to prevent a ton of boxing
      return (target instanceof Long) && Longs.indexOf(array, (Long) target, start, end) != -1;
    }

    @Override
    public int indexOf(@CheckForNull Object target) {
      // Overridden to prevent a ton of boxing
      if (target instanceof Long) {
        int i = Longs.indexOf(array, (Long) target, start, end);