Optimize partitioning for in-place

Last updated: April 16, 2026

Quick Overview

Given an array of integers, implement an in-place algorithm to optimize the partitioning of the array such that all elements less than a given pivot are on one side and all elements greater than or equal to the pivot are on the other side. The function should modify the array directly and return the final partitioned array.

Bloomberg
Coding & Algorithms
Software Engineer
Bloomberg
April 16, 2026
Software Engineer
Take-home Project
Coding & Algorithms
Medium

28

8

2,488 solved


Given an array of integers, implement an in-place algorithm to optimize the partitioning of the array such that all elements less than a given pivot are on one side and all elements greater than or equal to the pivot are on the other side. The function should modify the array directly and return the final partitioned array.

Bloomberg uses this problem in the Take-home Project 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
  • 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
Time and space complexity analysis
Data structure selection and trade-offs
Sorting and searching
Edge cases and input validation
Common algorithm patterns (sliding window, two pointers, BFS/DFS)
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
  • Can you solve this iteratively instead of recursively (or vice versa)?
  • Can you solve this in a single pass?
  • What happens if the input contains duplicates?
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Problem Analysis

The problem at hand is a partitioning problem, which can be effectively solved using the two pointers technique. This technique is particularly suitable here as we need to rearrange elements based...

Approach
  1. Initialize two pointers: Start with two pointers, left initialized to the beginning of the array (index 0) and right initialized to the end (index len(array) - 1).
  2. **Iterate through the ...

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