return null;
            }
          });
    }
    assertEquals(allTasks.size() + 1, barrier.getParties());
    for (int i = 0; i < 1000; i++) {
      Collections.shuffle(allTasks);
      AbstractFuture<String> future = new AbstractFuture<String>() {};
      currentFuture.set(future);
      for (Callable<?> task : allTasks) {

		}
		buf = xlMetaV2TrimData(buf)

		vers = append(vers, metaCacheEntry{
			name:     "a",
			metadata: buf,
		})
	}

	// Shuffle...
	for i := range 100 {
		rng := rand.New(rand.NewSource(int64(i)))
		rng.Shuffle(len(vers), func(i, j int) {
			vers[i], vers[j] = vers[j], vers[i]
		})
		var entries []chan metaCacheEntry
		for _, v := range vers {
			v.cached = nil

		if len(disks) < er.setDriveCount/2 {
			return fmt.Errorf("not enough drives (found=%d, healing=%d, total=%d) are available to heal `%s`", len(disks), healing, er.setDriveCount, tracker.disk.String())
		}

		rand.Shuffle(len(disks), func(i, j int) {
			disks[i], disks[j] = disks[j], disks[i]
		})

		filterLifecycle := func(bucket, object string, fi FileInfo) bool {
			if lc == nil {
				return false
			}

			NextCycle: oldCache.Info.NextCycle,
		},
		Cache: make(map[string]dataUsageEntry, len(oldCache.Cache)),
	}

	// Put all buckets into channel.
	bucketCh := make(chan BucketInfo, len(buckets))

	// Shuffle buckets to ensure total randomness of buckets, being scanned.
	// Otherwise same set of buckets get scanned across erasure sets always.
	// at any given point in time. This allows different buckets to be scanned

pkg math, func RoundToEven(float64) float64
pkg math/big, const MaxBase = 62
pkg math/big, method (*Float) Sqrt(*Float) *Float
pkg math/big, method (*Int) CmpAbs(*Int) int
pkg math/rand, func Shuffle(int, func(int, int))
pkg math/rand, method (*Rand) Shuffle(int, func(int, int))
pkg net, method (*TCPListener) SyscallConn() (syscall.RawConn, error)
pkg net, method (*UnixListener) SyscallConn() (syscall.RawConn, error)

      misses.add("INVALID");
    }

    List<String> sampleDataList = new ArrayList<>();
    sampleDataList.addAll(hits);
    sampleDataList.addAll(misses);
    Collections.shuffle(sampleDataList);
    sampleData = sampleDataList.toArray(new String[sampleDataList.size()]);
  }

  // Since we can't pass a concrete SomeEnum.class directly, we need to use a raw type.
  @SuppressWarnings("unchecked")

		// Run for a number of times, shuffling the input to ensure that output is consistent.
		for i := range 10 {
			t.Run(fmt.Sprintf("test-%d-%s-run-%d", testID, tt.name, i), func(t *testing.T) {
				if i > 0 {
					rng.Shuffle(len(tt.m), func(i, j int) {
						tt.m[i], tt.m[j] = tt.m[j], tt.m[i]
					})
				}
				gotSelected, gotOk := tt.m.resolve(&tt.r)
				if gotOk != tt.wantOk {

		askDisks = len(disks) // use all available drives
	}

	// However many we ask, versions must exist on ~50%
	listingQuorum := (askDisks + 1) / 2

	if askDisks > 0 && len(disks) > askDisks {
		rand.Shuffle(len(disks), func(i, j int) {
			disks[i], disks[j] = disks[j], disks[i]
		})
		fallbackDisks = disks[askDisks:]
		disks = disks[:askDisks]
	}

	// How to resolve results.

 * randomly ordered data (the probability decreases faster than exponentially in N), but if you are
 * passing in unsanitized user data then a malicious user could force it. A light shuffle of the
 * data using an unpredictable seed should normally be enough to thwart this attack.
 *
 * <p>The time taken to compute multiple quantiles on the same dataset using {@link Scale#indexes

			if r != needle {
				rs = append(rs, r)
			}
		}
	}
	// Shuffle the runes so that they are not in descending order.
	// The sort is deterministic since this is used for benchmarks,
	// which need to be repeatable.
	rr := rand.New(rand.NewSource(1))
	rr.Shuffle(len(rs), func(i, j int) {
		rs[i], rs[j] = rs[j], rs[i]
	})
	uchars := string(rs)