<version>4.0.0+</version>
          <description>
            Multiple specifications of a set of reports, each having (possibly) different
            configuration. This is the reporting parallel to an {@code execution} in the build.
          </description>
          <association>
            <type>ReportSet</type>
            <multiplicity>*</multiplicity>
          </association>
        </field>

			// to exit immediately
			return
		}
	}
}

const (
	resyncWorkerCnt        = 10 // limit of number of bucket resyncs is progress at any given time
	resyncParallelRoutines = 10 // number of parallel resync ops per bucket
)

func newresyncer() *replicationResyncer {
	rs := replicationResyncer{
		statusMap:      make(map[string]BucketReplicationResyncStatus),
		workerSize:     resyncWorkerCnt,

				trace.Flow(ctx, d.traceSpan, a.traceSpan)
			}
			err = a.Actor.Act(b, ctx, a)
			span.Done()
		}
		if a.json != nil {
			a.json.TimeDone = time.Now()
		}

		// The actions run in parallel but all the updates to the
		// shared work state are serialized through b.exec.
		b.exec.Lock()
		defer b.exec.Unlock()

		if err != nil {
			if b.AllowErrors && a.Package != nil {

		// Until the server replies to this request, it can't read another,
		// so we might as well run the handler in this goroutine.
		// [*] Not strictly true: HTTP pipelining. We could let them all process
		// in parallel even if their responses need to be serialized.
		// But we're not going to implement HTTP pipelining because it
		// was never deployed in the wild and the answer is HTTP/2.
		inFlightResponse = w

	}
	base.ExitIfErrors()

	// Check for duplicate loads of the same package.
	// That should be impossible, but if it does happen then
	// we end up trying to build the same package twice,
	// usually in parallel overwriting the same files,
	// which doesn't work very well.
	seen := map[string]bool{}
	reported := map[string]bool{}
	for _, pkg := range PackageList(pkgs) {

    fi
    # Spread the remaining number of nodes evenly
    this_mig_size=$((instances_left / (NUM_MIGS - i + 1)))
    instances_left=$((instances_left - this_mig_size))

    # Run instance-groups creation in parallel.
    {
      gcloud compute instance-groups managed \
          create "${group_name}" \
          --project "${PROJECT}" \
          --zone "${ZONE}" \
          --base-instance-name "${group_name}" \

	testUploads := struct {
		sync.Mutex
		uploads []string
	}{}

	objectName := "test-object-new-multipart-parallel"
	var wg sync.WaitGroup
	for i := 0; i < 10; i++ {
		wg.Add(1)
		// Initiate NewMultipart upload on the same object 10 times concurrrently.
		go func() {
			defer wg.Done()

//	ycover[Yi0*Ymax+Ys32] = 1
//	ycover[Yi1*Ymax+Ys32] = 1
//	ycover[Yi8*Ymax+Ys32] = 1
//
// which means that Yi0, Yi1, and Yi8 all count as Ys32 (signed 32)
// if that's what an instruction can handle.
//
// In parallel with the scan through the ytable for the appropriate line, there
// is a z pointer that starts out pointing at the strange magic byte list in
// the Optab struct.  With each step past a non-matching ytable line, z

	// We've inverted the order in which it gets G's from the local P's runnable queue
	// and then advances the head pointer because we don't want to mess up the statuses of G's
	// while runqdrain() and runqsteal() are running in parallel.
	// Thus we should advance the head pointer before draining the local P into a gQueue,
	// so that we can update any gp.schedlink only after we take the full ownership of G,

		{"slice has pointer", ValueOf(s), sliceTestFn},
		{"non-map/slice", ValueOf(1), panicTestFn},
	}

	for _, tc := range tests {
		tc := tc
		t.Run(tc.name, func(t *testing.T) {
			t.Parallel()
			if !tc.testFunc(tc.value) {
				t.Errorf("unexpected result for value.Clear(): %v", tc.value)
			}
		})
	}
}

func TestValuePointerAndUnsafePointer(t *testing.T) {
	ptr := new(int)