Optimize compression for O(1) space

Last updated: September 28, 2025

Quick Overview

Given a string, implement a function that compresses the string using the counts of repeated characters while ensuring the solution uses O(1) space. The function should return the compressed string if it's shorter than the original; otherwise, return the original string. For example, the input "aabcccccaaa" should return "a2b1c5a3".

Stripe
Coding & Algorithms
Software Engineer
Stripe
September 28, 2025
Software Engineer
Phone Screen
Coding & Algorithms
Easy

2

4

1,470 solved


Given a string, implement a function that compresses the string using the counts of repeated characters while ensuring the solution uses O(1) space. The function should return the compressed string if it's shorter than the original; otherwise, return the original string. For example, the input "aabcccccaaa" should return "a2b1c5a3".

Coding interviews at Stripe 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
  • 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
Common algorithm patterns (sliding window, two pointers, BFS/DFS)
Tree structures and recursion
Graph algorithms and traversal
Dynamic programming and memoization
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
  • What if the input doesn't fit in memory?
  • What happens if the input contains duplicates?
  • Can you optimize the space complexity of your solution?
  • What is the worst-case input for your solution?
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Sample Answer
Problem Analysis

The problem requires us to compress a string by counting consecutive repeated characters. The key constraints are that we need to ensure that our solution uses O(1) space, which implies that we cannot...

Approach
  1. Initialize a pointer i to traverse the string and a variable count to count occurrences of each character.
  2. Use a list compressed to build the compressed string.
  3. Loop through the str...

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