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add 28. Implement strStr() 🍺
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@ -34,6 +34,7 @@ My LeetCode solutions with Chinese explanation. 我的LeetCode中文题解。
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| 24 |[Swap Nodes in Pairs](https://leetcode.com/problems/swap-nodes-in-pairs)|[C++](https://github.com/ShusenTang/LeetCode/blob/master/solutions/24.%20Swap%20Nodes%20in%20Pairs.md)|Medium| |
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| 26 |[Remove Duplicates from Sorted Array](https://leetcode.com/problems/remove-duplicates-from-sorted-array)|[C++](https://github.com/ShusenTang/LeetCode/blob/master/solutions/26.%20Remove%20Duplicates%20from%20Sorted%20Array.md)|Easy| |
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| 27 |[Remove Element](https://leetcode.com/problems/remove-element)|[C++](https://github.com/ShusenTang/LeetCode/blob/master/solutions/27.%20Remove%20Element.md)|Easy| |
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| 28 |[Implement strStr()](https://leetcode.com/problems/implement-strstr/)|[C++](solutions/28.%20Implement%20strStr().md)|Easy| |
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| 29 |[Divide Two Integers](https://leetcode.com/problems/divide-two-integers)|[C++](https://github.com/ShusenTang/LeetCode/blob/master/solutions/29.%20Divide%20Two%20Integers.md)|Medium| |
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| 31 |[Next Permutation](https://leetcode.com/problems/next-permutation)|[C++](https://github.com/ShusenTang/LeetCode/blob/master/solutions/31.%20Next%20Permutation.md)|Medium| |
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| 34 |[Find First and Last Position of Element in Sorted ](https://leetcode.com/problems/find-first-and-last-position-of-element-in-sorted-array/)|[C++](https://github.com/ShusenTang/LeetCode/blob/master/solutions/34.%20Find%20First%20and%20Last%20Position%20of%20Element%20in%20Sorted%20Array.md)|Medium| |
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solutions/28. Implement strStr().md
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solutions/28. Implement strStr().md
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# [28. Implement strStr()](https://leetcode.com/problems/implement-strstr/)
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# 思路
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字符串匹配。
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## 思路一、暴力
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用一个两层循环暴力匹配,可能测试样例比较弱,所以亲测时间并不慢(8ms)。
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时间复杂度O(mn),空间复杂度O(1)
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## 思路二、KMP
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字符串匹配经典的解法应该就是KMP(Knuth-Morris-Pratt)算法了,与暴力匹配(每次失配时,回到模式串开头重新匹配)不同,**KMP的核心思想就是每次失配时,根据模式串的特点,将模式串回退到适当的位置。**
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先来定义next数组:
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* `next[i]`表示模式串中前i个字符串(即P[0,...,i-1])中相同前缀后缀的最大长度,`next[0]`和`next[1]`固定为-1和0。
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举例:
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* 若`next[5] = 2`,则说明`P[0,1] == P[3,4]`
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* 又如`abcabd`的`next = {-1, 0, 0, 0, 1, 2}`
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若某个模式串P如下图所示,若匹配到`P[k]`与待匹配的字符串`S[i]`失配,即`P[k]!=S[i]`;对于暴力匹配来说,我们需要从头开始匹配P和S,即从`P[0]`开始匹配;但是由于我们知道了蓝色部分的子串是相等的,所以我们可以从`P[next[k]]`开始匹配。
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<div align=center>
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<img width="500" src="img/28/kmp.png"/>
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</div>
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<div align=center>一个模式串P的示意图,颜色相同的子串相等</div>
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所以问题就是如何求next数组,仔细分析一下下图也很简单,如果我们求得了`next[0,...,j]`,
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* 令`k = next[j]`, 如果`P[j] == P[k]`,那么`next[j+1] = k + 1`;
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* 否则,令`k = next[k]`,重复上述过程;
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此外,next还可以优化,因为如果`P[k] == P[next[k]]`,那么如果`P[k]`与待匹配的字符串`S[i]`失配,那么`P[next[k]]`肯定还是与`S[i]`失配,所以如果`P[k] == P[next[k]]`,我们可更新 `next[k] = next[next[k]]`。
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关于KMP比较详细的介绍可参考[从头到尾彻底理解KMP](https://blog.csdn.net/v_july_v/article/details/7041827)。
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KMP算法时间复杂度为O(m+n),空间复杂度为O(n),其中n为模式串的长度
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## 思路三、Sunday
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关于字符串匹配还有比KMP更好理解的算法,叫做Sunday算法。
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参考[字符串匹配——Sunday算法](https://blog.csdn.net/q547550831/article/details/51860017),举个例子来说明:
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* 刚开始时,把模式串与主串左边对齐:
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<div>
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<img width="500" src="img/28/sunday1.png"/>
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</div>
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* 结果发现在第2个字符处发现不匹配,不匹配时**关注主串中参加匹配的最末位字符的下一位字符**,即标粗的字符 i,因为模式串search中并不存在i,所以模式串直接跳过一大片,向右移动位数 = 匹配串长度 + 1 = 6 + 1 = 7,从 i 之后的那个字符(即字符n)开始下一步的匹配,如下图
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<div>
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<img width="500" src="img/28/sunday2.png"/>
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</div>
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* 结果第一个字符就不匹配,再看主串中参加匹配的最末位字符的下一位字符,是 r,它在模式串位于倒数第3位(如果模式串有多个 r 我们应该以最后一个为准,因为那样移动次数较少才不会错过),于是把模式串向右移动3位(m - 3 = 6 - 3 = r 到模式串末尾的距离 + 1 = 2 + 1 =3),使两个 r 对齐,如下
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<div>
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<img width="500" src="img/28/sunday3.png"/>
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</div>
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* 匹配成功。
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可见我们需要一个数组,记录了某个字符在模式串中最后一次出现的位置到末尾的距离,由于ASCII用0-127来编码字符,所以我们可以用一个长度为128的数组,即代码中的move数组。
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平均复杂度O(m+n),move数组的大小时固定的,所以可认为空间复杂度O(1)
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最坏情况下,时间复杂度为O(mn),例如主串为baaaabaaaabaaaabaaaa而模式串为aaaaa。
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## 思路四、Boyer-Moore
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实际应用最多字符串匹配算法貌似是Boyer-Moore算法,有兴趣的可以去看看:
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* [字符串匹配的Boyer-Moore算法](https://www.ruanyifeng.com/blog/2013/05/boyer-moore_string_search_algorithm.html);
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* [BM算法和Sunday快速字符串匹配算法](https://www.cnblogs.com/Philip-Tell-Truth/p/5185267.html)。
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# C++
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## 思路一
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``` C++
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class Solution {
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public:
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int strStr(string haystack, string needle) {
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if (needle.empty()) return 0;
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int m = haystack.size(), n = needle.size();
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if (m < n) return -1;
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for (int i = 0; i <= m - n; ++i) {
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int j = 0;
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for (j = 0; j < n; ++j) {
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if (haystack[i + j] != needle[j]) break;
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}
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if (j == n) return i;
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}
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return -1;
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}
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};
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```
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## 思路二
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``` C++
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class Solution {
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private:
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vector<int>compute_next(const string& pattern){
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int pn = pattern.size();
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vector<int>next(pn, 0); next[0] = -1;
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for(int i = 2; i < pn; i++){
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int j = next[i-1];
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while(j >= 0 && pattern[j] != pattern[i-1]) j = next[j];
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next[i] = j + 1;
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}
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// // next数组优化
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// for(int i = 2; i < pn; i++){
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// int t1 = i, t2 = next[i];
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// while(t2 >= 0 && pattern[t1] == pattern[t2]){
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// t1 = t2;
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// t2 = next[t2];
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// }
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// next[i] = t2;
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// }
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return next;
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}
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public:
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int strStr(string haystack, string needle) {
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int sn = haystack.size(), pn = needle.size();
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if(!pn) return 0;
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if(sn < pn) return -1;
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vector<int>next = compute_next(needle);
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int i = 0, j = 0;
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while(i < sn){
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if(j == -1 || haystack[i] == needle[j]){
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i++;
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j++;
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if(j == pn) return i - pn;
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}
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else j = next[j];
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}
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return -1;
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}
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};
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```
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## 思路三
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``` C++
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class Solution {
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public:
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int strStr(string haystack, string needle) {
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int sn = haystack.size(), pn = needle.size();
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if(!pn) return 0;
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if(sn < pn) return -1;
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vector<int>move(128, pn + 1);
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for(int i = 0; i < pn; i++)
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move[needle[i]] = pn - i;
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int i = 0;
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while(i <= sn - pn){
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int j = 0;
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while(haystack[i + j] == needle[j])
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if(++j == pn) return i;
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i += move[haystack[i + pn]];
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}
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return -1;
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}
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};
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```
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solutions/img/28/kmp.png
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solutions/img/28/kmp.png
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After Width: | Height: | Size: 25 KiB |
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solutions/img/28/sunday1.png
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solutions/img/28/sunday1.png
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After Width: | Height: | Size: 32 KiB |
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solutions/img/28/sunday2.png
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solutions/img/28/sunday2.png
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After Width: | Height: | Size: 34 KiB |
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solutions/img/28/sunday3.png
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solutions/img/28/sunday3.png
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After Width: | Height: | Size: 28 KiB |
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