Minimum Window Substring
Given a string S and a string T, find the minimum window in S which will contain all the characters in T in complexity O(n).
For example,
S = "ADOBECODEBANC"
T = "ABC"
Minimum window is "BANC".
Note:
If there is no such window in S that covers all characters in T, return the empty string "".
If there are multiple such windows, you are guaranteed that there will always be only one unique minimum window in S.
1. 使用start 和 end指针表示window的边界,count记录子串是否包含t中全部的char。2. 先向右移动end指针直至找到一个子串;然后向右移动start直至该有效子串的size最小。
3. 当start滑过t中的char后,count++表示当前子串不是有效的
4. unordered_map的中key如果不存在,map[key]++会赋值为1
5. 将unordered_map换成vector<int>(128,0)会更快
string minWindow(string s, string t) {
unordered_map<char, int> cmap;
for (char c: t) cmap[c]++;
int count = t.size(), start = 0, end = 0;
int minLen = INT_MAX, minStart = 0;
while (start <= end && end < s.size()){
if (cmap[s[end]]-- > 0) count--; //if exists in t,不在t中的char 或者 t中已经用光的char 的值为负
end++; //move end to right
while (count == 0){ //find a valid substr
if (cmap[s[start]]++ >= 0){ //if exists in t,
if (minLen > end - start){ //只有start滑过t中的char时,才有必要更新最小长度
minLen = end - start;
minStart = start;
}
count++;
}
start++; //move start to right
}
}
return minLen == INT_MAX ? "" : s.substr(minStart, minLen);
}
本文介绍了一种在字符串S中寻找包含字符串T所有字符的最小子串的算法,复杂度为O(n)。通过移动窗口的方式,利用start和end指针进行搜索,结合哈希表实现高效查找。
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