# Solving Leetcode Interviews in Seconds with AI: Maximize Palindrome Length From Subsequences


	# Introduction
	In this blog post, we will explore how to solve the LeetCode problem "1771" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like [Chatmagic](https://www.chatmagic.app), we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.

	# Problem Statement
	> You are given two strings, word1 and word2. You want to construct a string in the following manner:  Choose some non-empty subsequence subsequence1 from word1. Choose some non-empty subsequence subsequence2 from word2. Concatenate the subsequences: subsequence1 + subsequence2, to make the string.  Return the length of the longest palindrome that can be constructed in the described manner. If no palindromes can be constructed, return 0. A subsequence of a string s is a string that can be made by deleting some (possibly none) characters from s without changing the order of the remaining characters. A palindrome is a string that reads the same forward as well as backward.   Example 1:  Input: word1 = "cacb", word2 = "cbba" Output: 5 Explanation: Choose "ab" from word1 and "cba" from word2 to make "abcba", which is a palindrome. Example 2:  Input: word1 = "ab", word2 = "ab" Output: 3 Explanation: Choose "ab" from word1 and "a" from word2 to make "aba", which is a palindrome. Example 3:  Input: word1 = "aa", word2 = "bb" Output: 0 Explanation: You cannot construct a palindrome from the described method, so return 0.   Constraints:  1 <= word1.length, word2.length <= 1000 word1 and word2 consist of lowercase English letters.  

	# Explanation
	Here's the breakdown of the approach and the Python code:

*   **Key Idea:** Find the longest common palindromic subsequence that can be formed by combining subsequences from `word1` and `word2`. Focus on characters that match between the two words, and then find the longest palindromic subsequence around those matching characters.
*   **Optimization:** Use dynamic programming to efficiently calculate the lengths of palindromic subsequences. Start by considering the longest possible palindrome and work inward.
*   **Palindrome Center:** Matching characters between `word1` and `word2` will form the "center" of potential palindromes. Extend outward from these centers.

*   **Complexity:** Time: O(m\*n), where *m* and *n* are the lengths of `word1` and `word2` respectively. Space: O(m\*n).

	
	# Code
	```python
	def longestPalindrome(word1: str, word2: str) -> int:
    s = word1 + word2
    n1 = len(word1)
    n2 = len(word2)
    n = len(s)
    dp = [[0] * n for _ in range(n)]
    ans = 0

    for i in range(n - 1, -1, -1):
        dp[i][i] = 1
        for j in range(i + 1, n):
            if s[i] == s[j]:
                dp[i][j] = dp[i + 1][j - 1] + 2
                if i < n1 and j >= n1:
                    ans = max(ans, dp[i][j])
            else:
                dp[i][j] = max(dp[i + 1][j], dp[i][j - 1])

    return ans
	```