// +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

	"holderIdentity":       "holderIdentity contains the identity of the holder of a current lease.",
	"leaseDurationSeconds": "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.",
	"acquireTime":          "acquireTime is a time when the current lease was acquired.",

  }

  @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) {

	// can keep the process hung indefinitely, as long as we signal it often
	// enough.)
	timeout := 10 * time.Second

	// The subprocess begins sleeping for 1s after it writes to stdout, so measure
	// the timeout from here (not from when we started creating the process).
	// That should reduce noise from process startup overhead.
	ready := time.Now()

	// With the repro running, we can continuously send to it

  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) {

      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

// we simulate a lock-free queue by adding the Record to a ring buffer.
// Omitting the locking makes this little more than a copy of the Record,
// but that is a worthwhile thing to measure because Records are on the large
// side. Since nothing actually reads from the ring buffer, it can handle an
// arbitrary number of Records without either blocking or allocation.
type asyncHandler struct {

    public void setup() throws CloneNotSupportedException {
        input = new byte[hashSize];
        random.nextBytes(input);
        processorFactory = HASHERS.get(type);
    }

    @Benchmark
    public void measure(Blackhole blackhole) {
        HashProcessor processor = processorFactory.create();
        processor.process(input, blackhole);
    }

    interface HashProcessor {

		mem.setValue(encodedVals)
		mem.header().count = 0

		ws.fuzz(context.Background(), fuzzArgs{Limit: 1})
	}
}

// BenchmarkWorkerPing acts as the coordinator and measures the time it takes
// a worker to respond to N pings. This is a rough measure of our RPC latency.
func BenchmarkWorkerPing(b *testing.B) {
	if race.Enabled {
		b.Skip("TODO(48504): fix and re-enable")
	}
	b.SetParallelism(1)
	w := newWorkerForTest(b)

) : 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)