Dynamic Programming on string
Last updated: November 6, 2025
Quick Overview
Given a string, implement a dynamic programming solution to find the length of the longest palindromic subsequence. Your function should take a single string as input and return an integer representing the length of the longest subsequence that is a palindrome.
Salesforce
November 6, 20258
8
3,369 solved
Given a string, implement a dynamic programming solution to find the length of the longest palindromic subsequence. Your function should take a single string as input and return an integer representing the length of the longest subsequence that is a palindrome.
Coding interviews at Salesforce focus on problem-solving approach as much as the final solution. The interviewer wants to see you break down the problem, consider edge cases, and optimize iteratively. Communication throughout the process is key.
What the Interviewer Expects
- Recognize the underlying problem pattern (sliding window, two pointers, BFS/DFS, etc.)
- Discuss multiple approaches and trade-offs before coding
- Implement an optimal solution with clean, production-quality code
- Handle all edge cases including boundary conditions and invalid input
- Optimize both time and space complexity with clear justification
- Test your solution systematically with well-chosen examples
Key Topics to Cover
How to Approach This
- Clarify input constraints and edge cases before writing code.
- Walk through your approach verbally and confirm with the interviewer before coding.
- Start with a brute force solution, then optimize. Mention time and space complexity.
- Test your solution with examples, including edge cases like empty input or duplicates.
- Consider common patterns: sliding window, two pointers, hash map, BFS/DFS, dynamic programming.
Possible Follow-up Questions
- Can you optimize the space complexity of your solution?
- What happens if the input contains duplicates?
- How would you parallelize this solution?
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Practice DSA ProblemsSample Answer
Problem Analysis
To solve the problem of finding the length of the longest palindromic subsequence, we can recognize that this is a dynamic programming problem. The specific pattern here is that we can break the probl...
Approach
- Define the DP Table: Create a 2D array
dpwheredp[i][j]will represent the length of the longest palindromic subsequence in the substrings[i:j+1]. - Base Case: Initialize `dp[i][i...
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