return
		}
	}
}

func (sr *SRStats) updateMovingAvg() {
	sr.lock.Lock()
	defer sr.lock.Unlock()
	for _, s := range sr.M {
		s.XferRateLrg.measure.updateExponentialMovingAverage(time.Now())
		s.XferRateSml.measure.updateExponentialMovingAverage(time.Now())
	}
}

// SRMetric captures replication metrics for a deployment
type SRMetric struct {

  private void weaklyReferenceQueue() {
    frq = new FinalizableReferenceQueue();
    queueReference = new WeakReference<>(frq.queue);

    /*
     * Queue and clear a reference for good measure. We test later on that
     * the finalizer thread stopped, but we should test that it actually
     * started first.
     */
    reference =
        new FinalizableWeakReference<Object>(new Object(), frq) {

  private void weaklyReferenceQueue() {
    frq = new FinalizableReferenceQueue();
    queueReference = new WeakReference<>(frq.queue);

    /*
     * Queue and clear a reference for good measure. We test later on that
     * the finalizer thread stopped, but we should test that it actually
     * started first.
     */
    reference =
        new FinalizableWeakReference<Object>(new Object(), frq) {

			return
		}
	}
}

func (r *ReplicationStats) updateMovingAvg() {
	r.RLock()
	for _, s := range r.Cache {
		for _, st := range s.Stats {
			st.XferRateLrg.measure.updateExponentialMovingAverage(time.Now())
			st.XferRateSml.measure.updateExponentialMovingAverage(time.Now())
		}
	}
	r.RUnlock()
}

// ActiveWorkers returns worker stats
func (r *ReplicationStats) ActiveWorkers() ActiveWorkerStat {

  // +optional
  optional string holderIdentity = 1;

  // leaseDurationSeconds is a duration that candidates for a lease need
  // to wait to force acquire it. This is measure against time of last
  // observed renewTime.
  // +optional
  optional int32 leaseDurationSeconds = 2;

  // acquireTime is a time when the current lease was acquired.
  // +optional

      label: "Orthogonality: How does this change interact or overlap with existing features?"
      description: "Is the goal of this change a performance improvement? If so, what quantifiable improvement should we expect? How would we measure it?"
    validations:
      required: false

  - type: textarea
    id: learning-curve
    attributes:
      label: "Would this change make Go easier or harder to learn, and why?"

  - type: textarea

  }

  @Footprint
  Object sizeOfStriped() {
    return impl.get(numStripes);
  }

  // a place to put the locks in sizeOfPopulatedStriped so they don't get GC'd before we measure
  final List<Lock> locks = new ArrayList<>(numStripes);

  @Footprint
  Object sizeOfPopulatedStriped() {
    locks.clear();
    Striped<Lock> striped = impl.get(numStripes);
    for (int i : stripes) {

  }

  @Footprint
  Object sizeOfStriped() {
    return impl.get(numStripes);
  }

  // a place to put the locks in sizeOfPopulatedStriped so they don't get GC'd before we measure
  final List<Lock> locks = new ArrayList<>(numStripes);

  @Footprint
  Object sizeOfPopulatedStriped() {
    locks.clear();
    Striped<Lock> striped = impl.get(numStripes);
    for (int i : stripes) {

) : ConnectionListener() {
  val eventSequence: Deque<ConnectionEvent> = ConcurrentLinkedDeque()

  private val forbiddenLocks = mutableSetOf<Any>()

  /** The timestamp of the last taken event, used to measure elapsed time between events. */
  private var lastTimestampNs: Long? = null

  /** Confirm that the thread does not hold a lock on `lock` during the callback. */
  fun forbidLock(lock: Any) {
    forbiddenLocks.add(lock)

    b ^= (b >>> 47);
    b *= mul;
    return b;
  }

  /**
   * Computes intermediate hash of 32 bytes of byte array from the given offset. Results are
   * returned in the output array because when we last measured, this was 12% faster than allocating
   * new arrays every time.
   */
  private static void weakHashLength32WithSeeds(
      byte[] bytes, int offset, long seedA, long seedB, long[] output) {