Optimize flattening for in-place
Last updated: January 14, 2026
Quick Overview
Find an efficient solution for compression given the O(1) space constraint.
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Find an efficient solution for compression given the O(1) space constraint.
This coding problem is frequently asked during Onsite at LinkedIn. The interviewer is testing your ability to translate a problem into clean, working code while discussing time and space complexity. LinkedIn expects candidates to write production-quality code, not just solve the puzzle.
What the Interviewer Expects
- Identify the correct data structure and algorithm for the problem
- Write clean, bug-free code with proper variable naming
- Analyze time and space complexity correctly
- Handle basic edge cases (empty input, single element)
- Communicate your thought process while coding
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 your solution change if the input was sorted?
- Can you solve this iteratively instead of recursively (or vice versa)?
- What is the worst-case input for your solution?
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Practice DSA ProblemsSample Answer
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Brute Force Approach
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