所有的循环只为寻找答案, 所有的判断只为选择正确答案
public List<Integer> findSubstring(String s, String[] words) {
List<Integer> res = new LinkedList<Integer>();
if(words == null || words.length == 0 || s == null || s.equals("")) return res;
HashMap<String, Integer> freq = new HashMap<String, Integer>();
// 统计数组中每个词出现的次数,放入哈希表中待用
for(String word : words){
freq.put(word, freq.containsKey(word) ? freq.get(word) + 1 : 1);
}
// 得到每个词的长度
int len = words[0].length();
// 错开位来统计
for(int i = 0; i < len; i++){ // 因为要一单词长度递增, 因此i < len
// 建一个新的哈希表,记录本轮搜索中窗口内单词出现次数
HashMap<String, Integer> currFreq = new HashMap<String, Integer>();
// start是窗口的开始,count表明窗口内有多少词
int start = i, count = 0;
for(int j = i; j <= s.length() - len; j += len){
String sub = s.substring(j, j + len);
// 看下一个词是否是给定数组中的
if(freq.containsKey(sub)){
// 窗口中单词出现次数加1
currFreq.put(sub, currFreq.containsKey(sub) ? currFreq.get(sub) + 1 : 1);
count++;
// 如果该单词出现次数已经超过给定数组中的次数了,说明多来了一个该单词,所以要把窗口中该单词上次出现的位置及之前所有单词给去掉
while(currFreq.get(sub) > freq.get(sub)){
String leftMost = s.substring(start, start + len);
currFreq.put(leftMost, currFreq.get(leftMost) - 1);
start = start + len;
count--;
}
// 如果窗口内单词数和总单词数一样,则找到结果
if(count == words.length){
String leftMost = s.substring(start, start + len);
currFreq.put(leftMost, currFreq.get(leftMost) - 1);
res.add(start);
start = start + len;
count--;
}
// 如果截出来的单词都不在数组中,前功尽弃,重新开始
} else {
currFreq.clear();
start = j + len;
count = 0;
}
}
}
return res;
}
30. Substring with Concatenation of All Words
原文:http://www.cnblogs.com/apanda009/p/7122674.html