Optimize partitioning for O(1) space

Last updated: December 15, 2025

Quick Overview

Given an array of integers, implement a function to partition the array in-place such that all elements less than a specified pivot are moved to the left, and all elements greater than or equal to the pivot are moved to the right, while using O(1) additional space. The function should return the modified array.

Lyft
Coding & Algorithms
Software Engineer
Lyft
December 15, 2025
Software Engineer
Phone Screen
Coding & Algorithms
Medium

81

3

614 solved


Given an array of integers, implement a function to partition the array in-place such that all elements less than a specified pivot are moved to the left, and all elements greater than or equal to the pivot are moved to the right, while using O(1) additional space. The function should return the modified array.

This coding problem is frequently asked during Phone Screen at Lyft. The interviewer is testing your ability to translate a problem into clean, working code while discussing time and space complexity. Lyft expects candidates to write production-quality code, not just solve the puzzle.

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
Sorting and searching
Data structure selection and trade-offs
Time and space complexity analysis
Graph algorithms and traversal
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
  • How would you parallelize this solution?
  • Can you solve this iteratively instead of recursively (or vice versa)?
  • How would you test this solution thoroughly?
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Problem Analysis

The problem at hand requires partitioning an array into two segments based on a pivot value. This is a classic use case for the two-pointer technique, where we maintain two pointers: one for traversin...

Approach
  1. Initialize two pointers: left at the beginning of the array and right at the end.
  2. Iterate through the array using the left pointer.
    • If the element at left is less than the pivot, i...

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