Optimize traversal for without recursion

Last updated: April 25, 2026

Quick Overview

Find an efficient solution for compression given the O(n) time constraint.

DoorDash
Coding & Algorithms
Machine Learning Engineer
DoorDash
April 25, 2026
Machine Learning Engineer
Onsite
Coding & Algorithms
Easy

241

0

4,357 solved


Find an efficient solution for compression given the O(n) time constraint.

DoorDash uses this problem in the Onsite to evaluate your algorithmic thinking. They expect you to discuss multiple approaches, analyze trade-offs between them, and implement the optimal solution with clean, readable code.

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
Graph algorithms and traversal
Tree structures and recursion
Data structure selection and trade-offs
Binary search and divide and conquer
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
  • What is the worst-case input for your solution?
  • How would your solution change if the input was sorted?
  • How would you parallelize this solution?
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