Substring with Concatenation of All Words leetcode java
题目:
You are given a string, S, and a list of words, L, that
are all of the same length. Find all starting indices of substring(s) in
S that is a concatenation of each word in L exactly once and without
any intervening characters.
For example, given:
S: "barfoothefoobarman"
L: ["foo", "bar"]
You should return the indices: [0,9]
.
(order does not matter).
题解:
我最开始做的是说把L里面给的串全排列放起来,看S包含不包含其中之一,包含的话反话其index。但是这个方法TLE了
代码:
1 public static void swap(String[] str, int i, int j){
2 String temp = new String();
3 temp = str[i];
4 str[i] = str[j];
5 str[j] = temp;
6 }
7
8 public static void arrange (String[] L, int st, ArrayList<String> re){
9 if (st == L.length - 1){
String temp = new String();
for (int i = 0; i < L.length; i ++){
temp +=L[i];
}
re.add(temp);
}else{
for (int i = st; i < L.length; i ++){
swap(L, st, i);
arrange(L, st + 1,re);
swap(L, st, i);
}
}
return ;
}
public static ArrayList<Integer> findSubstring(String S, String[] L) {
ArrayList<Integer> result = new ArrayList<Integer>();
ArrayList<String> possible = new ArrayList<String>();
arrange(L,0,possible);
for(int j= 0; j<possible.size();j++){
if(S.contains(possible.get(j)))
result.add(S.indexOf(possible.get(j)));
}
return result;
}
更好的解法就是一种滑动窗口式的。我是参照了http://blog.csdn.net/linhuanmars/article/details/20342851的写法,他的写法目前速度最快。
首先是先把所给的字典利用HashMap建一下,key存word,value存这个word出现的个数。
因为每个单词长度一样,外层循序只许循环wordLen次,每次指针挪一次,每一次循环遍历整个字符串。
内层循环每次遍历一个单词,把整个S字符串遍历检查。
需要在每次大循环维护一个count,看是不是达到了给的字典字符串数量,同时维护一个index,是每个符合条件的字符串的起始index,需要存到返回结果中。
为了能够检查是不是合格字符串,在这里维护一个curDict的HashMap。
首先检查一个单词是不是在原始字典中出现,没出现的话说明这个单词肯定不符合标准,index指针指向下一个单词的起始点,计数器和curDict都要清零。
如果这个单词在原始字典里出现过,用更新原始字典的方法更新curDict,如果这个单词出现的次数没有超过原始字典里记录的次数,那么count++,如果超过了,就需要挪动指针,并把超过的从curDict删掉。
最后,如果count达到了L的length,说明找到了一个合格的字符串,那么将index存入返回结果res中,再把index挪到下一个单词处,更新curDict即可。
code ganker的讲解是这样的:
“
这道题看似比较复杂,其实思路和Longest
Substring Without Repeating Characters差不多。因为那些单词是定长的,所以本质上和单一个字符一样。和Longest
Substring Without Repeating Characters的
区别只在于我们需要维护一个字典,然后保证目前的串包含字典里面的单词有且仅有一次。思路仍然是维护一个窗口,如果当前单词在字典中,则继续移动窗口右
端,否则窗口左端可以跳到字符串下一个单词了。假设源字符串的长度为n,字典中单词的长度为l。因为不是一个字符,所以我们需要对源字符串所有长度为l的
子串进行判断。做法是i从0到l-1个字符开始,得到开始index分别为i,
i+l, i+2*l,
...的长度为l的单词。这样就可以保证判断到所有的满足条件的串。因为每次扫描的时间复杂度是O(2*n/l)(每个单词不会被访问多于两次,一次是窗
口右端,一次是窗口左端),总共扫描l次(i=0, ...,
l-1),所以总复杂度是O(2*n/l*l)=O(n),是一个线性算法。空间复杂度是字典的大小,即O(m*l),其中m是字典的单词数量。
”
代码部分我自己稍作了修改,主题思想与code ganker相同。
代码如下:
1 public static ArrayList<Integer> findSubstring(String S, String[] L) {
2 ArrayList<Integer> res = new ArrayList<Integer>();
3 if(S==null||L==null||S.length()==0||L.length==0)
4 return res;
5 int wordLen = L[0].length();//same length for each word in dictionary
6
7 //put given dictionary into hashmap with each word's count
8 HashMap<String, Integer> dict = new HashMap<String, Integer>();
9 for(String word: L){
if(!dict.containsKey(word))
dict.put(word, 1);
else
dict.put(word, dict.get(word) + 1);
}
for(int i = 0; i < wordLen; i++){
int count = 0;
int index = i;//index of each startpoint
HashMap<String, Integer> curdict = new HashMap<String, Integer>();
//till the first letter of last word
for(int j = i; j <= S.length() - wordLen; j += wordLen){
String curWord = S.substring(j, j + wordLen);
//check each word to tell if it existes in give dictionary
if(!dict.containsKey(curWord)){
curdict.clear();
count = 0;
index = j + wordLen;
}else{
//form current dictionary
if(!curdict.containsKey(curWord))
curdict.put(curWord, 1);
else
curdict.put(curWord, curdict.get(curWord) + 1);
//count for current found word and check if it exceed given word count
if(curdict.get(curWord) <= dict.get(curWord)){
count++;
}else{
while(curdict.get(curWord) > dict.get(curWord)){
String temp = S.substring(index, index + wordLen);
curdict.put(temp, curdict.get(temp)-1);
index = index + wordLen;//make index move next
}
}
//put into res and move index point to nextword
//and update current dictionary as well as count num
if(count == L.length){
res.add(index);
String temp = S.substring(index, index + wordLen);
curdict.put(temp, curdict.get(temp)-1);
index = index + wordLen;
count--;
}
}
}//end for j
}//end for i
return res;
}
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