return shuffledPartsMetadata
}

// shuffleDisks - shuffle input disks slice depending on the
// erasure distribution. Return shuffled slice of disks with
// their expected distribution.
func shuffleDisks(disks []StorageAPI, distribution []int) (shuffledDisks []StorageAPI) {
	if distribution == nil {
		return disks
	}
	shuffledDisks = make([]StorageAPI, len(disks))
	// Shuffle disks for expected distribution.

		// symbols reliably. Sort by name but use a stable sort, so that
		// any original entries with the same name (all DWARFVAR symbols
		// have empty names but different relocation sets) are not shuffled.
		// TODO: Find a better place and optimize to only sort TOC symbols.
		sort.SliceStable(ctxt.Data, func(i, j int) bool {
			return ctxt.Data[i].Name < ctxt.Data[j].Name
		})
	}

      return no_op();

    // For vectors, shuffle values by sorting instead of the obvious
    // Fisher-Yates algorithm. Fisher-Yates is simple to implement and correct,
    // but not easily parallelizable. For a sufficiently parallel architecture,
    // it is faster to sort many times, than Fisher-Yates shuffle once.
    if (input_rank == 1) {
      // Shuffle values by assigning each value a random key and sorting the

		t.Fatal(err)
	}
}

func TestDash(t *testing.T) {
	m := MapFS{
		"a-b/a": {Data: []byte("a-b/a")},
	}
	if err := TestFS(m, "a-b/a"); err != nil {
		t.Error(err)
	}
}

type shuffledFS MapFS

func (fsys shuffledFS) Open(name string) (fs.File, error) {
	f, err := MapFS(fsys).Open(name)
	if err != nil {
		return nil, err
	}
	return &shuffledFile{File: f}, nil
}

type shuffledFile struct{ fs.File }

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

// Shuffle pseudo-randomizes the order of elements.
// n is the number of elements. Shuffle panics if n < 0.
// swap swaps the elements with indexes i and j.
func (r *Rand) Shuffle(n int, swap func(i, j int)) {
	if n < 0 {
		panic("invalid argument to Shuffle")
	}

		m[i] = m[j]
		m[j] = i
	}
	return m
}

// Shuffle pseudo-randomizes the order of elements.
// n is the number of elements. Shuffle panics if n < 0.
// swap swaps the elements with indexes i and j.
func (r *Rand) Shuffle(n int, swap func(i, j int)) {
	if n < 0 {
		panic("invalid argument to Shuffle")
	}

	// Fisher-Yates shuffle: https://en.wikipedia.org/wiki/Fisher%E2%80%93Yates_shuffle

	if !bytes.Equal(b1, b2) {
		t.Errorf("mismatch after re-seed:\n%x\n%x", b1, b2)
	}
}

func TestShuffleSmall(t *testing.T) {
	// Check that Shuffle allows n=0 and n=1, but that swap is never called for them.
	r := New(NewSource(1))
	for n := 0; n <= 1; n++ {
		r.Shuffle(n, func(i, j int) { t.Fatalf("swap called, n=%d i=%d j=%d", n, i, j) })
	}
}

			p := make([]int, n) // re-usable slice for Shuffle generator
			tests := [...]struct {
				name string
				fn   func() int
			}{
				{name: "Int32N", fn: func() int { return int(r.Int32N(int32(nfact))) }},
				{name: "Perm", fn: func() int { return encodePerm(r.Perm(n)) }},
				{name: "Shuffle", fn: func() int {
					// Generate permutation using Shuffle.
					for i := range p {
						p[i] = i
					}

	s2 := byteorder.BeUint32(src[8:12])
	s3 := byteorder.BeUint32(src[12:16])

	// First round just XORs input with key.
	s0 ^= xk[0]
	s1 ^= xk[1]
	s2 ^= xk[2]
	s3 ^= xk[3]

	// Middle rounds shuffle using tables.
	// Number of rounds is set by length of expanded key.
	nr := len(xk)/4 - 2 // - 2: one above, one more below
	k := 4
	var t0, t1, t2, t3 uint32
	for r := 0; r < nr; r++ {

		m.exitCode = 0
		return
	}

	if *shuffle != "off" {
		var n int64
		var err error
		if *shuffle == "on" {
			n = time.Now().UnixNano()
		} else {
			n, err = strconv.ParseInt(*shuffle, 10, 64)
			if err != nil {
				fmt.Fprintln(os.Stderr, `testing: -shuffle should be "off", "on", or a valid integer:`, err)
				m.exitCode = 2
				return
			}
		}