Given s1, s2, s3, find whether s3 is formed by the interleaving of s1 and s2.
For example,
Given:
s1 = "aabcc"
,
s2 = "dbbca"
,
When s3 = "aadbbcbcac"
, return true.
When s3 = "aadbbbaccc"
, return false.
题目解析:
看s1和s2正序交替排列是否能得到目标串。
方案一:递归方法
由于两个子串是从前向后与目标串匹配的,那么可以一个一个去比较,当s1[index1] == s2[index2]的时候,就进行递归:先按照s1当前值与目标串s3相等,递归;如果不能匹配,则按照s2与s3当前值相等,递归;最后再进行一次判断。
由于递归耗时,造成时间超限……
class Solution {
public:
bool isInterleave(string s1, string s2, string s3) {
int len1 = s1.size();
int len2 = s2.size();
int len3 = s3.size();
if(len1+len2 != len3)
return false;
return Judge(s1,0,s2,0,s3,0);
}
bool Judge(string s1,int index1,string s2,int index2,string s3,int index3){
if(index3 == s3.size())
return true;
if(index1 == s1.size()){
while(index2 < s2.size()){
if(s2[index2] != s3[index3])
return false;
index2++;
index3++;
}
return true;
}
if(index2 == s2.size()){
while(index1 < s1.size()){
if(s1[index1] != s3[index3])
return false;
index1++;
index3++;
}
return true;
}
bool flag1 = false,flag2 = false;
if(s1[index1] == s3[index3]) //如果两个相等,就递归进去
flag1 = Judge(s1,index1+1,s2,index2,s3,index3+1);
if(flag1 == false){ //如果递归失败,或者s1[index1] != s3[index3]
if(s2[index2] == s3[index3])
flag2 = Judge(s1,index1,s2,index2+1,s3,index3+1);
else
return false;
}
return flag1 || flag2;
}
};
方案二:
时间超限问题,我们可以利用动态规划来解决。假设0…len1和0….len2已经于0…len3进行匹配了,然后增加一个值len3+1,那么要么满足0…len1+1且0….len2 要么满足0…len1和0….len2+1。基于这个思想,就定义一个二维数组。填写动态规划产生的中间值,以空间换取时间上的节省。——–因此,空间换时间不光用在提高时间复杂度上面,也用在动态规划中!要有这个思想。
class Solution {
private:
bool f[1000][1000];
public:
bool isInterleave(string s1, string s2, string s3) {
// Start typing your C/C++ solution below
// DO NOT write int main() function
if (s1.size() + s2.size() != s3.size())
return false;
f[0][0] = true;
for(int i = 1; i <= s1.size(); i++)
f[i][0] = f[i-1][0] && (s3[i-1] == s1[i-1]);
for(int j = 1; j <= s2.size(); j++)
f[0][j] = f[0][j-1] && (s3[j-1] == s2[j-1]);
for(int i = 1; i <= s1.size(); i++)
for(int j = 1; j <= s2.size(); j++)
f[i][j] = (f[i][j-1] && s2[j-1] == s3[i+j-1]) || (f[i-1][j] && s1[i-1] == s3[i+j-1]);
return f[s1.size()][s2.size()];
}
};