// Copyright 2009 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package sort_test
import (
"cmp"
"fmt"
"internal/testenv"
"math"
"math/rand/v2"
"slices"
. "sort"
"strconv"
"strings"
"testing"
)
var ints = [...]int{74, 59, 238, -784, 9845, 959, 905, 0, 0, 42, 7586, -5467984, 7586}
var float64s = [...]float64{74.3, 59.0, math.Inf(1), 238.2, -784.0, 2.3, math.NaN(), math.NaN(), math.Inf(-1), 9845.768, -959.7485, 905, 7.8, 7.8}
var stringsData = [...]string{"", "Hello", "foo", "bar", "foo", "f00", "%*&^*&^&", "***"}
func TestSortIntSlice(t *testing.T) {
data := ints
a := IntSlice(data[0:])
Sort(a)
if !IsSorted(a) {
t.Errorf("sorted %v", ints)
t.Errorf(" got %v", data)
}
}
func TestSortFloat64Slice(t *testing.T) {
data := float64s
a := Float64Slice(data[0:])
Sort(a)
if !IsSorted(a) {
t.Errorf("sorted %v", float64s)
t.Errorf(" got %v", data)
}
}
// Compare Sort with slices.Sort sorting a float64 slice containing NaNs.
func TestSortFloat64sCompareSlicesSort(t *testing.T) {
slice1 := slices.Clone(float64s[:])
slice2 := slices.Clone(float64s[:])
Sort(Float64Slice(slice1))
slices.Sort(slice2)
// Compare for equality using cmp.Compare, which considers NaNs equal.
if !slices.EqualFunc(slice1, slice2, func(a, b float64) bool { return cmp.Compare(a, b) == 0 }) {
t.Errorf("mismatch between Sort and slices.Sort: got %v, want %v", slice1, slice2)
}
}
func TestSortStringSlice(t *testing.T) {
data := stringsData
a := StringSlice(data[0:])
Sort(a)
if !IsSorted(a) {
t.Errorf("sorted %v", stringsData)
t.Errorf(" got %v", data)
}
}
func TestInts(t *testing.T) {
data := ints
Ints(data[0:])
if !IntsAreSorted(data[0:]) {
t.Errorf("sorted %v", ints)
t.Errorf(" got %v", data)
}
}
func TestFloat64s(t *testing.T) {
data := float64s
Float64s(data[0:])
if !Float64sAreSorted(data[0:]) {
t.Errorf("sorted %v", float64s)
t.Errorf(" got %v", data)
}
}
func TestStrings(t *testing.T) {
data := stringsData
Strings(data[0:])
if !StringsAreSorted(data[0:]) {
t.Errorf("sorted %v", stringsData)
t.Errorf(" got %v", data)
}
}
func TestSlice(t *testing.T) {
data := stringsData
Slice(data[:], func(i, j int) bool {
return data[i] < data[j]
})
if !SliceIsSorted(data[:], func(i, j int) bool { return data[i] < data[j] }) {
t.Errorf("sorted %v", stringsData)
t.Errorf(" got %v", data)
}
}
func TestSortLarge_Random(t *testing.T) {
n := 1000000
if testing.Short() {
n /= 100
}
data := make([]int, n)
for i := 0; i < len(data); i++ {
data[i] = rand.IntN(100)
}
if IntsAreSorted(data) {
t.Fatalf("terrible rand.rand")
}
Ints(data)
if !IntsAreSorted(data) {
t.Errorf("sort didn't sort - 1M ints")
}
}
func TestReverseSortIntSlice(t *testing.T) {
data := ints
data1 := ints
a := IntSlice(data[0:])
Sort(a)
r := IntSlice(data1[0:])
Sort(Reverse(r))
for i := 0; i < len(data); i++ {
if a[i] != r[len(data)-1-i] {
t.Errorf("reverse sort didn't sort")
}
if i > len(data)/2 {
break
}
}
}
func TestBreakPatterns(t *testing.T) {
// Special slice used to trigger breakPatterns.
data := make([]int, 30)
for i := range data {
data[i] = 10
}
data[(len(data)/4)*1] = 0
data[(len(data)/4)*2] = 1
data[(len(data)/4)*3] = 2
Sort(IntSlice(data))
}
func TestReverseRange(t *testing.T) {
data := []int{1, 2, 3, 4, 5, 6, 7}
ReverseRange(IntSlice(data), 0, len(data))
for i := len(data) - 1; i > 0; i-- {
if data[i] > data[i-1] {
t.Fatalf("reverseRange didn't work")
}
}
data1 := []int{1, 2, 3, 4, 5, 6, 7}
data2 := []int{1, 2, 5, 4, 3, 6, 7}
ReverseRange(IntSlice(data1), 2, 5)
for i, v := range data1 {
if v != data2[i] {
t.Fatalf("reverseRange didn't work")
}
}
}
type nonDeterministicTestingData struct {
r *rand.Rand
}
func (t *nonDeterministicTestingData) Len() int {
return 500
}
func (t *nonDeterministicTestingData) Less(i, j int) bool {
if i < 0 || j < 0 || i >= t.Len() || j >= t.Len() {
panic("nondeterministic comparison out of bounds")
}
return t.r.Float32() < 0.5
}
func (t *nonDeterministicTestingData) Swap(i, j int) {
if i < 0 || j < 0 || i >= t.Len() || j >= t.Len() {
panic("nondeterministic comparison out of bounds")
}
}
func TestNonDeterministicComparison(t *testing.T) {
// Ensure that sort.Sort does not panic when Less returns inconsistent results.
// See https://golang.org/issue/14377.
defer func() {
if r := recover(); r != nil {
t.Error(r)
}
}()
td := &nonDeterministicTestingData{
r: rand.New(rand.NewPCG(0, 0)),
}
for i := 0; i < 10; i++ {
Sort(td)
}
}
func BenchmarkSortString1K(b *testing.B) {
b.StopTimer()
unsorted := make([]string, 1<<10)
for i := range unsorted {
unsorted[i] = strconv.Itoa(i ^ 0x2cc)
}
data := make([]string, len(unsorted))
for i := 0; i < b.N; i++ {
copy(data, unsorted)
b.StartTimer()
Strings(data)
b.StopTimer()
}
}
func BenchmarkSortString1K_Slice(b *testing.B) {
b.StopTimer()
unsorted := make([]string, 1<<10)
for i := range unsorted {
unsorted[i] = strconv.Itoa(i ^ 0x2cc)
}
data := make([]string, len(unsorted))
for i := 0; i < b.N; i++ {
copy(data, unsorted)
b.StartTimer()
Slice(data, func(i, j int) bool { return data[i] < data[j] })
b.StopTimer()
}
}
func BenchmarkStableString1K(b *testing.B) {
b.StopTimer()
unsorted := make([]string, 1<<10)
for i := range unsorted {
unsorted[i] = strconv.Itoa(i ^ 0x2cc)
}
data := make([]string, len(unsorted))
for i := 0; i < b.N; i++ {
copy(data, unsorted)
b.StartTimer()
Stable(StringSlice(data))
b.StopTimer()
}
}
func BenchmarkSortInt1K(b *testing.B) {
b.StopTimer()
for i := 0; i < b.N; i++ {
data := make([]int, 1<<10)
for i := 0; i < len(data); i++ {
data[i] = i ^ 0x2cc
}
b.StartTimer()
Ints(data)
b.StopTimer()
}
}
func BenchmarkSortInt1K_Sorted(b *testing.B) {
b.StopTimer()
for i := 0; i < b.N; i++ {
data := make([]int, 1<<10)
for i := 0; i < len(data); i++ {
data[i] = i
}
b.StartTimer()
Ints(data)
b.StopTimer()
}
}
func BenchmarkSortInt1K_Reversed(b *testing.B) {
b.StopTimer()
for i := 0; i < b.N; i++ {
data := make([]int, 1<<10)
for i := 0; i < len(data); i++ {
data[i] = len(data) - i
}
b.StartTimer()
Ints(data)
b.StopTimer()
}
}
func BenchmarkSortInt1K_Mod8(b *testing.B) {
b.StopTimer()
for i := 0; i < b.N; i++ {
data := make([]int, 1<<10)
for i := 0; i < len(data); i++ {
data[i] = i % 8
}
b.StartTimer()
Ints(data)
b.StopTimer()
}
}
func BenchmarkStableInt1K(b *testing.B) {
b.StopTimer()
unsorted := make([]int, 1<<10)
for i := range unsorted {
unsorted[i] = i ^ 0x2cc
}
data := make([]int, len(unsorted))
for i := 0; i < b.N; i++ {
copy(data, unsorted)
b.StartTimer()
Stable(IntSlice(data))
b.StopTimer()
}
}
func BenchmarkStableInt1K_Slice(b *testing.B) {
b.StopTimer()
unsorted := make([]int, 1<<10)
for i := range unsorted {
unsorted[i] = i ^ 0x2cc
}
data := make([]int, len(unsorted))
for i := 0; i < b.N; i++ {
copy(data, unsorted)
b.StartTimer()
SliceStable(data, func(i, j int) bool { return data[i] < data[j] })
b.StopTimer()
}
}
func BenchmarkSortInt64K(b *testing.B) {
b.StopTimer()
for i := 0; i < b.N; i++ {
data := make([]int, 1<<16)
for i := 0; i < len(data); i++ {
data[i] = i ^ 0xcccc
}
b.StartTimer()
Ints(data)
b.StopTimer()
}
}
func BenchmarkSortInt64K_Slice(b *testing.B) {
b.StopTimer()
for i := 0; i < b.N; i++ {
data := make([]int, 1<<16)
for i := 0; i < len(data); i++ {
data[i] = i ^ 0xcccc
}
b.StartTimer()
Slice(data, func(i, j int) bool { return data[i] < data[j] })
b.StopTimer()
}
}
func BenchmarkStableInt64K(b *testing.B) {
b.StopTimer()
for i := 0; i < b.N; i++ {
data := make([]int, 1<<16)
for i := 0; i < len(data); i++ {
data[i] = i ^ 0xcccc
}
b.StartTimer()
Stable(IntSlice(data))
b.StopTimer()
}
}
const (
_Sawtooth = iota
_Rand
_Stagger
_Plateau
_Shuffle
_NDist
)
const (
_Copy = iota
_Reverse
_ReverseFirstHalf
_ReverseSecondHalf
_Sorted
_Dither
_NMode
)
type testingData struct {
desc string
t *testing.T
data []int
maxswap int // number of swaps allowed
ncmp, nswap int
}
func (d *testingData) Len() int { return len(d.data) }
func (d *testingData) Less(i, j int) bool {
d.ncmp++
return d.data[i] < d.data[j]
}
func (d *testingData) Swap(i, j int) {
if d.nswap >= d.maxswap {
d.t.Fatalf("%s: used %d swaps sorting slice of %d", d.desc, d.nswap, len(d.data))
}
d.nswap++
d.data[i], d.data[j] = d.data[j], d.data[i]
}
func lg(n int) int {
i := 0
for 1<<uint(i) < n {
i++
}
return i
}
func testBentleyMcIlroy(t *testing.T, sort func(Interface), maxswap func(int) int) {
sizes := []int{100, 1023, 1024, 1025}
if testing.Short() {
sizes = []int{100, 127, 128, 129}
}
dists := []string{"sawtooth", "rand", "stagger", "plateau", "shuffle"}
modes := []string{"copy", "reverse", "reverse1", "reverse2", "sort", "dither"}
var tmp1, tmp2 [1025]int
for _, n := range sizes {
for m := 1; m < 2*n; m *= 2 {
for dist := 0; dist < _NDist; dist++ {
j := 0
k := 1
data := tmp1[0:n]
for i := 0; i < n; i++ {
switch dist {
case _Sawtooth:
data[i] = i % m
case _Rand:
data[i] = rand.IntN(m)
case _Stagger:
data[i] = (i*m + i) % n
case _Plateau:
data[i] = min(i, m)
case _Shuffle:
if rand.IntN(m) != 0 {
j += 2
data[i] = j
} else {
k += 2
data[i] = k
}
}
}
mdata := tmp2[0:n]
for mode := 0; mode < _NMode; mode++ {
switch mode {
case _Copy:
for i := 0; i < n; i++ {
mdata[i] = data[i]
}
case _Reverse:
for i := 0; i < n; i++ {
mdata[i] = data[n-i-1]
}
case _ReverseFirstHalf:
for i := 0; i < n/2; i++ {
mdata[i] = data[n/2-i-1]
}
for i := n / 2; i < n; i++ {
mdata[i] = data[i]
}
case _ReverseSecondHalf:
for i := 0; i < n/2; i++ {
mdata[i] = data[i]
}
for i := n / 2; i < n; i++ {
mdata[i] = data[n-(i-n/2)-1]
}
case _Sorted:
for i := 0; i < n; i++ {
mdata[i] = data[i]
}
// Ints is known to be correct
// because mode Sort runs after mode _Copy.
Ints(mdata)
case _Dither:
for i := 0; i < n; i++ {
mdata[i] = data[i] + i%5
}
}
desc := fmt.Sprintf("n=%d m=%d dist=%s mode=%s", n, m, dists[dist], modes[mode])
d := &testingData{desc: desc, t: t, data: mdata[0:n], maxswap: maxswap(n)}
sort(d)
// Uncomment if you are trying to improve the number of compares/swaps.
//t.Logf("%s: ncmp=%d, nswp=%d", desc, d.ncmp, d.nswap)
// If we were testing C qsort, we'd have to make a copy
// of the slice and sort it ourselves and then compare
// x against it, to ensure that qsort was only permuting
// the data, not (for example) overwriting it with zeros.
//
// In go, we don't have to be so paranoid: since the only
// mutating method Sort can call is TestingData.swap,
// it suffices here just to check that the final slice is sorted.
if !IntsAreSorted(mdata) {
t.Fatalf("%s: ints not sorted\n\t%v", desc, mdata)
}
}
}
}
}
}
func TestSortBM(t *testing.T) {
testBentleyMcIlroy(t, Sort, func(n int) int { return n * lg(n) * 12 / 10 })
}
func TestHeapsortBM(t *testing.T) {
testBentleyMcIlroy(t, Heapsort, func(n int) int { return n * lg(n) * 12 / 10 })
}
func TestStableBM(t *testing.T) {
testBentleyMcIlroy(t, Stable, func(n int) int { return n * lg(n) * lg(n) / 3 })
}
// This is based on the "antiquicksort" implementation by M. Douglas McIlroy.
// See https://www.cs.dartmouth.edu/~doug/mdmspe.pdf for more info.
type adversaryTestingData struct {
t *testing.T
data []int // item values, initialized to special gas value and changed by Less
maxcmp int // number of comparisons allowed
ncmp int // number of comparisons (calls to Less)
nsolid int // number of elements that have been set to non-gas values
candidate int // guess at current pivot
gas int // special value for unset elements, higher than everything else
}
func (d *adversaryTestingData) Len() int { return len(d.data) }
func (d *adversaryTestingData) Less(i, j int) bool {
if d.ncmp >= d.maxcmp {
d.t.Fatalf("used %d comparisons sorting adversary data with size %d", d.ncmp, len(d.data))
}
d.ncmp++
if d.data[i] == d.gas && d.data[j] == d.gas {
if i == d.candidate {
// freeze i
d.data[i] = d.nsolid
d.nsolid++
} else {
// freeze j
d.data[j] = d.nsolid
d.nsolid++
}
}
if d.data[i] == d.gas {
d.candidate = i
} else if d.data[j] == d.gas {
d.candidate = j
}
return d.data[i] < d.data[j]
}
func (d *adversaryTestingData) Swap(i, j int) {
d.data[i], d.data[j] = d.data[j], d.data[i]
}
func newAdversaryTestingData(t *testing.T, size int, maxcmp int) *adversaryTestingData {
gas := size - 1
data := make([]int, size)
for i := 0; i < size; i++ {
data[i] = gas
}
return &adversaryTestingData{t: t, data: data, maxcmp: maxcmp, gas: gas}
}
func TestAdversary(t *testing.T) {
const size = 10000 // large enough to distinguish between O(n^2) and O(n*log(n))
maxcmp := size * lg(size) * 4 // the factor 4 was found by trial and error
d := newAdversaryTestingData(t, size, maxcmp)
Sort(d) // This should degenerate to heapsort.
// Check data is fully populated and sorted.
for i, v := range d.data {
if v != i {
t.Fatalf("adversary data not fully sorted")
}
}
}
func TestStableInts(t *testing.T) {
data := ints
Stable(IntSlice(data[0:]))
if !IntsAreSorted(data[0:]) {
t.Errorf("nsorted %v\n got %v", ints, data)
}
}
type intPairs []struct {
a, b int
}
// IntPairs compare on a only.
func (d intPairs) Len() int { return len(d) }
func (d intPairs) Less(i, j int) bool { return d[i].a < d[j].a }
func (d intPairs) Swap(i, j int) { d[i], d[j] = d[j], d[i] }
// Record initial order in B.
func (d intPairs) initB() {
for i := range d {
d[i].b = i
}
}
// InOrder checks if a-equal elements were not reordered.
func (d intPairs) inOrder() bool {
lastA, lastB := -1, 0
for i := 0; i < len(d); i++ {
if lastA != d[i].a {
lastA = d[i].a
lastB = d[i].b
continue
}
if d[i].b <= lastB {
return false
}
lastB = d[i].b
}
return true
}
func TestStability(t *testing.T) {
n, m := 100000, 1000
if testing.Short() {
n, m = 1000, 100
}
data := make(intPairs, n)
// random distribution
for i := 0; i < len(data); i++ {
data[i].a = rand.IntN(m)
}
if IsSorted(data) {
t.Fatalf("terrible rand.rand")
}
data.initB()
Stable(data)
if !IsSorted(data) {
t.Errorf("Stable didn't sort %d ints", n)
}
if !data.inOrder() {
t.Errorf("Stable wasn't stable on %d ints", n)
}
// already sorted
data.initB()
Stable(data)
if !IsSorted(data) {
t.Errorf("Stable shuffled sorted %d ints (order)", n)
}
if !data.inOrder() {
t.Errorf("Stable shuffled sorted %d ints (stability)", n)
}
// sorted reversed
for i := 0; i < len(data); i++ {
data[i].a = len(data) - i
}
data.initB()
Stable(data)
if !IsSorted(data) {
t.Errorf("Stable didn't sort %d ints", n)
}
if !data.inOrder() {
t.Errorf("Stable wasn't stable on %d ints", n)
}
}
var countOpsSizes = []int{1e2, 3e2, 1e3, 3e3, 1e4, 3e4, 1e5, 3e5, 1e6}
func countOps(t *testing.T, algo func(Interface), name string) {
sizes := countOpsSizes
if testing.Short() {
sizes = sizes[:5]
}
if !testing.Verbose() {
t.Skip("Counting skipped as non-verbose mode.")
}
for _, n := range sizes {
td := testingData{
desc: name,
t: t,
data: make([]int, n),
maxswap: 1<<31 - 1,
}
for i := 0; i < n; i++ {
td.data[i] = rand.IntN(n / 5)
}
algo(&td)
t.Logf("%s %8d elements: %11d Swap, %10d Less", name, n, td.nswap, td.ncmp)
}
}
func TestCountStableOps(t *testing.T) { countOps(t, Stable, "Stable") }
func TestCountSortOps(t *testing.T) { countOps(t, Sort, "Sort ") }
func bench(b *testing.B, size int, algo func(Interface), name string) {
if strings.HasSuffix(testenv.Builder(), "-race") && size > 1e4 {
b.Skip("skipping slow benchmark on race builder")
}
b.StopTimer()
data := make(intPairs, size)
x := ^uint32(0)
for i := 0; i < b.N; i++ {
for n := size - 3; n <= size+3; n++ {
for i := 0; i < len(data); i++ {
x += x
x ^= 1
if int32(x) < 0 {
x ^= 0x88888eef
}
data[i].a = int(x % uint32(n/5))
}
data.initB()
b.StartTimer()
algo(data)
b.StopTimer()
if !IsSorted(data) {
b.Errorf("%s did not sort %d ints", name, n)
}
if name == "Stable" && !data.inOrder() {
b.Errorf("%s unstable on %d ints", name, n)
}
}
}
}
func BenchmarkSort1e2(b *testing.B) { bench(b, 1e2, Sort, "Sort") }
func BenchmarkStable1e2(b *testing.B) { bench(b, 1e2, Stable, "Stable") }
func BenchmarkSort1e4(b *testing.B) { bench(b, 1e4, Sort, "Sort") }
func BenchmarkStable1e4(b *testing.B) { bench(b, 1e4, Stable, "Stable") }
func BenchmarkSort1e6(b *testing.B) { bench(b, 1e6, Sort, "Sort") }
func BenchmarkStable1e6(b *testing.B) { bench(b, 1e6, Stable, "Stable") }