// confusing the benchmarking framework for small b.N.
				b.StopTimer()
				stop()
			})
		}
	}

	// Measure the cost of counting goroutines
	b.Run("small-nil", run(func() bool {
		GoroutineProfile(nil)
		return true
	}))

	// Measure the cost with a small set of goroutines
	n := NumGoroutine()
	p := make([]StackRecord, 2*n+2*GOMAXPROCS(0))
	b.Run("small", run(func() bool {

        coordinationService.withStateLock(unlock(locks));
    }

    private void acquireLocks(final Iterable<? extends ResourceLock> locks) {
        if (containsProjectLocks(locks)) {
            projectLockStatistics.measure(new Runnable() {
                @Override
                public void run() {
                    coordinationService.withStateLock(lock(locks));
                }
            });
        } else {

			// improvement here would be to somehow get a count the number of expressions in the regex or
			// how many states are in the regex state machine and use that to measure regex cost).
			// For now, we're making a guess that each expression in a regex is typically at least 4 chars
			// in length.
			regexCost := uint64(math.Ceil(float64(actualSize(args[1])) * common.RegexStringLengthCostFactor))

				}
			} else if len(tparams) < len(recvTParams) {
				// Reporting an error here is a stop-gap measure to avoid crashes in the
				// compiler when a type parameter/argument cannot be inferred later. It
				// may lead to follow-on errors (see issues go.dev/issue/51339, go.dev/issue/51343).
				// TODO(gri) find a better solution
				got := measure(len(tparams), "type parameter")

            .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.

	// as a result, we need to measure the usage of this object for quota
	// on updates, we need to subtract the previous measured usage
	// if usage shows no change, just return since it has no impact on quota
	deltaUsage, err := evaluator.Usage(inputObject)
	if err != nil {
		return quotas, err
	}

	// c-shared and c-archive build modes and other sources of stacks from
	// the OS (notably, any allocated by C code) are not currently measured.
	// Note this too may change in the future.
	StackSys uint64

	// Off-heap memory statistics.
	//
	// The following statistics measure runtime-internal
	// structures that are not allocated from heap memory (usually
	// because they are part of implementing the heap). Unlike

	},
	{
		// Knative Gateway simulates a full Knative routing setup. There have been a variety of performance issues and optimizations
		// around Knative's somewhat abnormal usage, so its good to keep track and measure
		Name:      "knative-gateway",
		Services:  100,
		ProxyType: model.Router,
	},

	// Testing different port types
	{
		Name:     "http",
		Services: 100,
	},
	{
		Name:     "tcp",

		p := make([]int, 30)
		for i := range p {
			p[i] = i
		}
		r.Shuffle(30, func(i, j int) { p[i], p[j] = p[j], p[i] })
	}
}

// BenchmarkShuffleOverhead uses a minimal swap function
// to measure just the shuffling overhead.
func BenchmarkShuffleOverhead(b *testing.B) {
	r := New(NewSource(1))
	for n := b.N; n > 0; n-- {
		r.Shuffle(52, func(i, j int) {
			if i < 0 || i >= 52 || j < 0 || j >= 52 {

// Otherwise, it returns true.
//
// The caller must be non-preemptible until at least stop is called or this function
// returns false. Because this is trying to measure "on-CPU" time of some event, getting
// scheduled away during it can mean that whatever we're measuring isn't a reflection
// of "on-CPU" time. The OS could deschedule us at any time, but we want to maintain as