Find longest subsequence in grid

Last updated: January 16, 2026

Quick Overview

Given a grid of characters, write a function to find the longest subsequence of characters that can be formed by moving horizontally or vertically through adjacent cells. The function should return the length of this longest subsequence. The input will be a 2D list of characters, and the output should be an integer representing the length of the longest subsequence found.

OpenAI
Coding & Algorithms
Software Engineer
OpenAI
January 16, 2026
Software Engineer
Technical Screen
Coding & Algorithms
Medium

12

11

1,166 solved


Given a grid of characters, write a function to find the longest subsequence of characters that can be formed by moving horizontally or vertically through adjacent cells. The function should return the length of this longest subsequence. The input will be a 2D list of characters, and the output should be an integer representing the length of the longest subsequence found.

Coding interviews at OpenAI 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
Hash maps and frequency counting
Time and space complexity analysis
Data structure selection and trade-offs
Tree structures and recursion
Edge cases and input validation
How to Approach This
  1. Clarify input constraints and edge cases before writing code.
  2. Walk through your approach verbally and confirm with the interviewer before coding.
  3. Start with a brute force solution, then optimize. Mention time and space complexity.
  4. Test your solution with examples, including edge cases like empty input or duplicates.
  5. Consider common patterns: sliding window, two pointers, hash map, BFS/DFS, dynamic programming.
Possible Follow-up Questions
  • Can you solve this in a single pass?
  • How would you test this solution thoroughly?
  • How would your solution change if the input was sorted?
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Sample Answer
Problem Analysis

To find the longest subsequence in a grid of characters, we can utilize Depth-First Search (DFS). This pattern is applicable here because we need to explore all possible paths through the grid to dete...

Approach
  1. Initialize a variable longest to keep track of the maximum length of the subsequence found.
  2. Create a helper function dfs(x, y, visited) that will perform the DFS:
    • Check if the curr...

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