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Prashant Mishra

Posted on • Originally published at leetcode.com

# Longest Palindromic subsequence (Same as Lcs)

Given a string `s`, find the longest palindromic subsequence's length in `s`.

A subsequence is a sequence that can be derived from another sequence by deleting some or no elements without changing the order of the remaining elements.

Example 1:

``````Input: s = "bbbab"
Output: 4
Explanation: One possible longest palindromic subsequence is "bbbb".
``````

Solution:
Memoization approch:
Time complexity : o(n*m) and space complexity : o(n*m) + o(n) (o(n) is extra stack space utilized)

``````//intuition
/*
normal or brute force way: generate all possible subsequences and find the largest subsequence that is palindrome;
optimal approach :
Using Logic of longest common subsequence;
example : if s = bbbab, lets reverse it as r = babbb
now the we can perform longest common subsequence to get result as 3 (bbb) and that will be the required result;

*/
class Solution {
public int longestPalindromeSubseq(String s) {
//bottom up approach
StringBuilder sb = new StringBuilder();
sb.append(s);
String r= sb.reverse().toString();
int dp[][] = new int[s.length()][r.length()];
for(int row[]: dp){
Arrays.fill(row,-1);
}
return longestPalindromicSubsequence(s.length()-1,r.length()-1,s,r,dp);
}

//Memoization approach
public int longestPalindromicSubsequence(int i,int j, String a, String b,int dp[][]){
if(i<0 || j<0){
return 0;
}
if(dp[i][j]!=-1) return dp[i][j];
if(a.charAt(i)==b.charAt(j)){
return dp[i][j] = 1 + longestPalindromicSubsequence(i-1,j-1,a,b,dp);
}
return dp[i][j]= 0 + Integer.max(longestPalindromicSubsequence(i,j-1,a,b,dp),
longestPalindromicSubsequence(i-1,j,a,b,dp));
}
}
``````

Tabulation Approach:
Time complexity : o(n*m) and space complexity : o(n*m)

``````class Solution {
public int longestPalindromeSubseq(String s) {
//bottom up approach
StringBuilder sb = new StringBuilder();
sb.append(s);
String r= sb.reverse().toString();
int dp[][] = new int[s.length()+1][r.length()+1];

//base case
//its 1 base indexing
//lets put first row and first column as 0
for(int i = 0;i<=s.length();i++){
dp[i] = 0;
dp[i] = 0;
}
for(int i =1;i<=s.length();i++){
for(int j =1;j<=r.length();j++){
if(s.charAt(i-1)==r.charAt(j-1)){
dp[i][j] = 1 + dp[i-1][j-1];
}
else dp[i][j] = 0 + Integer.max(dp[i][j-1],dp[i-1][j]);
}
}
return dp[s.length()][r.length()];
}
}
``````