Find longest subsequence in array
Last updated: August 15, 2025
Quick Overview
Given a grid, find the minimum cost efficiently using Dynamic Programming.
SentinelOne
August 15, 20253
5
2,566 solved
Given a grid, find the minimum cost efficiently using Dynamic Programming.
Coding interviews at SentinelOne 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
- How would you parallelize this solution?
- Can you optimize the space complexity of your solution?
- What is the worst-case input for your solution?
- Can you solve this in a single pass?
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