Find longest subsequence in matrix
Last updated: August 3, 2025
Quick Overview
Given a matrix of integers, find the longest increasing subsequence that can be formed by moving in any direction (up, down, left, right) from any cell. The output should be the length of this longest subsequence. The solution should efficiently handle matrices of varying sizes and values.
Oracle
August 3, 2025133
12
3,303 solved
Given a matrix of integers, find the longest increasing subsequence that can be formed by moving in any direction (up, down, left, right) from any cell. The output should be the length of this longest subsequence. The solution should efficiently handle matrices of varying sizes and values.
Coding interviews at Oracle 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
- What happens if the input contains duplicates?
- How would you modify your solution to handle streaming input?
- What if the input doesn't fit in memory?
- How would you parallelize this solution?
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Practice DSA ProblemsSample Answer
Problem Analysis
To solve the problem of finding the longest increasing subsequence in a matrix, we can recognize that this problem can be viewed as a graph traversal where each cell can connect to its neighbors (up, ...
Approach
- Initialization: Start by defining the dimensions of the matrix and initializing a memoization table to store the length of the longest increasing subsequence for each cell.
- DFS Function:...
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