attachDetachController        = "attach_detach_controller"
)

var (
	inUseVolumeMetricDesc = metrics.NewDesc(
		metrics.BuildFQName("", "storage_count", "attachable_volumes_in_use"),
		"Measure number of volumes in use",
		[]string{"node", "volume_plugin"}, nil,
		metrics.ALPHA, "")

	totalVolumesMetricDesc = metrics.NewDesc(
		metrics.BuildFQName("", "attachdetach_controller", "total_volumes"),

var zeros = []string{"0", "0", "0", "0", "0", "0", "0", "0"}

// parseIPSlow is like ParseIP, but aims for readability above
// speed. It's the reference implementation for correctness checking
// and against which we measure optimized parsers.
//
// parseIPSlow understands the following forms of IP addresses:
//   - Regular IPv4: 1.2.3.4
//   - IPv4 with many leading zeros: 0000001.0000002.0000003.0000004

            .map(it -> (ExecutableElement) it)
            // Ensure that the elements have a stable order, as the annotation processing engine does not guarantee that for type elements.
            // The order in which the executable elements are listed should be the order in which they appear in the code but
            // we take an extra measure of care here and ensure the ordering between all elements.

// Input parameters and resulting value is number of microseconds.
func MilliCPUToQuota(milliCPU int64, period int64) (quota int64) {
	// CFS quota is measured in two values:
	//  - cfs_period_us=100ms (the amount of time to measure usage across given by period)
	//  - cfs_quota=20ms (the amount of cpu time allowed to be used across a period)
	// so in the above example, you are limited to 20% of a single CPU

type timestamp struct {
	time  time.Time
	label string
	start bool
}

type event struct {
	size int64  // count or amount of data processed (allocations, data size, lines, funcs, ...)
	unit string // unit of size measure (count, MB, lines, funcs, ...)
}

func (t *Timings) append(labels []string, start bool) {
	t.list = append(t.list, timestamp{time.Now(), strings.Join(labels, ":"), start})
}

	if r.hdr.Version > coverage.MetaFileVersion {
		return fmt.Errorf("meta-data file withn unknown version %d (expected %d)", r.hdr.Version, coverage.MetaFileVersion)
	}

	// Read package offsets for good measure
	r.pkgOffsets = make([]uint64, r.hdr.Entries)
	for i := uint64(0); i < r.hdr.Entries; i++ {
		if r.pkgOffsets[i], err = r.rdUint64(); err != nil {
			return err
		}
		if r.pkgOffsets[i] > r.hdr.TotalLength {

	// find the intersection between the hard resources on the quota
	// and the resources this controller can track to know what we can
	// look to measure updated usage stats for
	hardResources := ResourceNames(hardLimits)
	potentialResources := []corev1.ResourceName{}
	evaluators := registry.List()
	for _, evaluator := range evaluators {

	counts [timeHistNumBuckets * timeHistNumSubBuckets]atomic.Uint64

	// underflow counts all the times we got a negative duration
	// sample. Because of how time works on some platforms, it's
	// possible to measure negative durations. We could ignore them,
	// but we record them anyway because it's better to have some
	// signal that it's happening than just missing samples.
	underflow atomic.Uint64

) : EventListener() {
  val eventSequence: Deque<CallEvent> = ConcurrentLinkedDeque()

  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)

	return d2
}

// DurationTracker is a simple interface for tracking functions duration,
// it is safe for concurrent use by multiple goroutines.
type DurationTracker interface {
	// Track measures time spent in the given function f and
	// aggregates measured duration using aggregateFunction.
	// if Track is invoked with f from multiple goroutines concurrently,
	// then f must be safe to be invoked concurrently by multiple goroutines.
	Track(f func())