/**
   * A map of contents pre-created before experiment starts to only measure map creation cost. The
   * implementation for the creation of contents is independent and could be different from that of
   * the map under test.
   */
  Map<Element, Element> contents;

  /** Map pre-created before experiment starts to only measure iteration cost during experiment. */
  Map<Element, Element> map;

				totalDownloadTTFB = append(totalDownloadTTFB, throughputHighestResults[i].DownloadTTFB...)
			}

			result.PUTStats.Response = totalUploadTimes.Measure()
			result.GETStats.Response = totalDownloadTimes.Measure()
			result.GETStats.TTFB = totalDownloadTTFB.Measure()

			result.Size = opts.objectSize
			result.Disks = globalEndpoints.NEndpoints()
			result.Servers = len(globalNotificationSys.peerClients) + 1

			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 {

  attributes:
    label: Summary
    description: >
      What change are you proposing to the upload configuration, and why?
      For new upload configuration, which new counters will be collected, what
      do they measure, and why is it important to collect them?
      Note that uploaded data must not carry sensitive user information.
      See [go.dev/doc/telemetry#proposals](https://go.dev/doc/telemetry#proposals)

 * fixed but arbitrary point in time. Note that most users should use {@link Stopwatch} instead of
 * interacting with this class directly.
 *
 * <p><b>Warning:</b> this interface can only be used to measure elapsed time, not wall time.
 *
 * @author Kevin Bourrillion
 * @since 10.0 (<a href="https://github.com/google/guava/wiki/Compatibility">mostly
 *     source-compatible</a> since 9.0)
 */
@GwtCompatible

) : 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)

  }

  @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) {

  private val eventsForMatching = ConcurrentLinkedDeque<CallEvent>()

  private val forbiddenLocks = mutableListOf<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)

      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