温故而知新，最新在复习数据结构和算法，结合Chrome的V8源码，看看JS中的一些实现。
首先咱们看看字符串查找在V8中是使用的哪一种算法。
咱们知道JS中的String是继承于Object，源码以下:javascript
// https://github.com/v8/v8/blob/master/src/objects/string.cc
// Line942 字符串查找方法定义
int String::IndexOf(Isolate* isolate, Handle<String> receiver,Handle<String> search, int start_index) {
...
// 省略多余代码，根据返回值可见调用SearchString方法
// Line968
return SearchString<const uc16>(isolate, receiver_content, pat_vector,start_index);
}
// Line18
#include "src/strings/string-search.h"
// 根据头引入查找该文件
// https://github.com/v8/v8/blob/master/src/strings/string-search.h
// 重点来了
// Line 20
*根据如下注释咱们能够知道, JS中的字符串查找使用的BM查找算法。模式串最小匹配长度为7
class StringSearchBase {
protected:
// Cap on the maximal shift in the Boyer-Moore implementation. By setting a
// limit, we can fix the size of tables. For a needle longer than this limit,
// search will not be optimal, since we only build tables for a suffix
// of the string, but it is a safe approximation.
static const int kBMMaxShift = Isolate::kBMMaxShift;
// Bad-char shift table stored in the state. It's length is the alphabet size.
// For patterns below this length, the skip length of Boyer-Moore is too short
// to compensate for the algorithmic overhead compared to simple brute force.
static const int kBMMinPatternLength = 7;
};
// 重点的重点 Line 54
template <typename PatternChar, typename SubjectChar>
class StringSearch : private StringSearchBase {
public:
StringSearch(Isolate* isolate, Vector<const PatternChar> pattern)
: isolate_(isolate),
pattern_(pattern),
start_(Max(0, pattern.length() - kBMMaxShift)) {
if (sizeof(PatternChar) > sizeof(SubjectChar)) {
if (!IsOneByteString(pattern_)) {
strategy_ = &FailSearch;
return;
}
}
// 获取模式串字符长度
int pattern_length = pattern_.length();
// 若是小于7
// static const int kBMMinPatternLength = 7;
if (pattern_length < kBMMinPatternLength) {
if (pattern_length == 1) {
//若是待查找字符串长度为1,使用单字符查找
strategy_ = &SingleCharSearch;
return;
}
//不然使用线性查找
strategy_ = &LinearSearch;
return;
}
// 若是大于7,使用BM查找算法
strategy_ = &InitialSearch;
}
咱们先看看各浏览器的排序算法是不是稳定排序java
在V8 v7.0/Chrome70之后,源码不在包含/src/js目录,相应的迁移到了/src/torque
关于V8 Torque的详情能够参考V8 Torquegit
// https://github.com/v8/v8/blob/6.9.454/src/js/array.js
// Line 802
// 如下能够知道sort方法返回InnerArraySort结果
DEFINE_METHOD(
GlobalArray.prototype,
sort(comparefn) {
if (!IS_UNDEFINED(comparefn) && !IS_CALLABLE(comparefn)) {
throw %make_type_error(kBadSortComparisonFunction, comparefn);
}
var array = TO_OBJECT(this);
var length = TO_LENGTH(array.length);
return InnerArraySort(array, length, comparefn);
}
);
// Line645
// 咱们接下来看InnerArraySort的定义
function InnerArraySort(array, length, comparefn) {
// In-place QuickSort algorithm.
// For short (length <= 10) arrays, insertion sort is used for efficiency.
// 原地快排算法
// 若是长度小于10,使用插入排序
function InsertionSort(a, from, to) {
for (var i = from + 1; i < to; i++) {
var element = a[i];
for (var j = i - 1; j >= from; j--) {
var tmp = a[j];
var order = comparefn(tmp, element);
if (order > 0) {
a[j + 1] = tmp;
} else {
break;
}
}
a[j + 1] = element;
}
};
// ...省略部分代码
function QuickSort(a, from, to) {
var third_index = 0;
while (true) {
// Insertion sort is faster for short arrays.
if (to - from <= 10) {
InsertionSort(a, from, to);
return;
}
// ...省略部分代码
if (to - high_start < low_end - from) {
QuickSort(a, high_start, to);
to = low_end;
} else {
QuickSort(a, from, low_end);
from = high_start;
}
}
};
if (length < 2) return array;
QuickSort(array, 0, num_non_undefined);
return array;
}
// https://github.com/v8/v8/blob/4b9b23521e6fd42373ebbcb20ebe03bf445494f9/third_party/v8/builtins/array-sort.tq
// Line1236
transitioning macro
ArrayTimSortImpl(context: Context, sortState: SortState, length: Smi) {
if (length < 2) return;
let remaining: Smi = length;
// March over the array once, left to right, finding natural runs,
// and extending short natural runs to minrun elements.
let low: Smi = 0;
const minRunLength: Smi = ComputeMinRunLength(remaining);
while (remaining != 0) {
let currentRunLength: Smi = CountAndMakeRun(low, low + remaining);
// If the run is short, extend it to min(minRunLength, remaining).
// 当前执行长度小于最小长度
if (currentRunLength < minRunLength) {
const forcedRunLength: Smi = SmiMin(minRunLength, remaining);
//使用插入排序
BinaryInsertionSort(low, low + currentRunLength, low + forcedRunLength);
currentRunLength = forcedRunLength;
}
// Push run onto pending-runs stack, and maybe merge.
PushRun(sortState, low, currentRunLength);
MergeCollapse(context, sortState);
// Advance to find next run.
low = low + currentRunLength;
remaining = remaining - currentRunLength;
}
//其余时候使用归并排序
MergeForceCollapse(context, sortState);
assert(GetPendingRunsSize(sortState) == 1);
assert(GetPendingRunLength(sortState.pendingRuns, 0) == length);
}
// Line485
// BinaryInsertionSort is the best method for sorting small arrays: it
// does few compares, but can do data movement quadratic in the number of
// elements. This is an advantage since comparisons are more expensive due
// to calling into JS.
//
// [low, high) is a contiguous range of a array, and is sorted via
// binary insertion. This sort is stable.
//
// On entry, must have low <= start <= high, and that [low, start) is
// already sorted. Pass start == low if you do not know!.
macro BinaryInsertionSort(implicit context: Context, sortState: SortState)(
low: Smi, startArg: Smi, high: Smi) {
assert(low <= startArg && startArg <= high);
const workArray = sortState.workArray;
let start: Smi = low == startArg ? (startArg + 1) : startArg;
for (; start < high; ++start) {
// Set left to where a[start] belongs.
let left: Smi = low;
let right: Smi = start;
const pivot = workArray.objects[right];
// Invariants:
// pivot >= all in [low, left).
// pivot < all in [right, start).
assert(left < right);
// Find pivot insertion point.
while (left < right) {
const mid: Smi = left + ((right - left) >> 1);
const order = sortState.Compare(pivot, workArray.objects[mid]);
if (order < 0) {
right = mid;
} else {
left = mid + 1;
}
}
assert(left == right);
// The invariants still hold, so:
// pivot >= all in [low, left) and
// pivot < all in [left, start),
//
// so pivot belongs at left. Note that if there are elements equal
// to pivot, left points to the first slot after them -- that's why
// this sort is stable. Slide over to make room.
for (let p: Smi = start; p > left; --p) {
workArray.objects[p] = workArray.objects[p - 1];
}
workArray.objects[left] = pivot;
}
}
// Regardless of invariants, merge all runs on the stack until only one
// remains. This is used at the end of the mergesort.
transitioning macro
MergeForceCollapse(context: Context, sortState: SortState) {
let pendingRuns: FixedArray = sortState.pendingRuns;
// Reload the stack size becuase MergeAt might change it.
while (GetPendingRunsSize(sortState) > 1) {
let n: Smi = GetPendingRunsSize(sortState) - 2;
if (n > 0 &&
GetPendingRunLength(pendingRuns, n - 1) <
GetPendingRunLength(pendingRuns, n + 1)) {
--n;
}
MergeAt(n);
}
}