Optimize inversion for O(n) time
Last updated: November 19, 2025
Quick Overview
Given an array of integers, your task is to count the number of inversions in the array in O(n) time. An inversion is defined as a pair of indices (i, j) such that i < j and arr[i] > arr[j]. Return the total count of such inversions.
Netflix
November 19, 20258
13
3,439 solved
Given an array of integers, your task is to count the number of inversions in the array in O(n) time. An inversion is defined as a pair of indices (i, j) such that i < j and arr[i] > arr[j]. Return the total count of such inversions.
This coding problem is frequently asked during Technical Screen at Netflix. The interviewer is testing your ability to translate a problem into clean, working code while discussing time and space complexity. Netflix 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 if the input doesn't fit in memory?
- Can you solve this in a single pass?
- How would you modify your solution to handle streaming input?
- Can you solve this iteratively instead of recursively (or vice versa)?
Sharpen Your Skills on Codemia
Practice similar problems with our interactive workspace, get AI feedback, and track your progress.
Practice DSA ProblemsSample Answer
Problem Analysis
To solve the problem of counting inversions in an array in O(n) time, we need to note that the traditional methods (like merge sort) have a time complexity of O(n log n). Therefore, we must consider a...
Approach
The algorithm involves the following steps: 1. Coordinate Compression: Since the Fenwick Tree works best with a smaller range of indices, we first compress the values in the array to a range from ...
Submit Your Answer
