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Facebook Coding Interview: Array Partition I (Leetcode)

Matt Upham
Web Developer (JavaScript, React, Python)
Updated on ・2 min read

Why should you practice coding problems?

Want a job at companies like Google, Facebook, Amazon, and more? Software engineering interviews mainly consist of data structures and algorithm problems.

You need to do a lot of these problems in order to succeed in these interviews. Below I’ll be going through an approach to a popular problem: Array Partition I.

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Problem Statement & Approaach

The problem statement is:
“Given an array of 2n integers, your task is to group these integers into n pairs of integer, say (a1, b1), (a2, b2), ..., (an, bn) which makes the sum of min(ai, bi) for all i from 1 to n as large as possible.”

This basically says group an array of integers into pairs, take the minimum of those pairs, add them up. You should produce the largest sum possible, with these constraints. Below I have a full overview of the problem, with a solution.

If you want a better sense visually of how this is done, check out my in-depth explanation on YouTube below.

LeetCode: Array Partition I (Overview and Solution)

We want to make as many large numbers the minimums, and the general approach is to first sort the array. Once sorted, you’ll notice that we have forced as many large numbers to be the smallest of each pair.

Since we first need to sort the array, then loop through again, our time complexity is O(n log n) time (sorting is O(n log n), looping is O(n), so the sorting overpowers the second loop. Our space complexity is O(1), since we’re sorting in place, and creating a final sum in the end.


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