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HomeLeetCode ProblemsMinimum Sum of Squared Difference
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How to Solve Minimum Sum of Squared Difference Problem

Master the Minimum Sum of Squared Difference LeetCode problem with undetectable real-time assistance. Get instant solutions and explanations during your coding interviews.

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Medium#2333
LeetCode Problem

Minimum Sum of Squared Difference

You are given two positive 0-indexed integer arrays nums1 and nums2, both of length n. The sum of squared difference of arrays nums1 and nums2 is defined as the sum of (nums1[i] - nums2[i])2 for each 0 <= i < n. You are also given two positive integers k1 and k2. You can modify any of the elements of nums1 by +1 or -1 at most k1 times. Similarly, you can modify any of the elements of nums2 by +1 or -1 at most k2 times. Return the minimum sum of squared difference after modifying array nums1 at most k1 times and modifying array nums2 at most k2 times. Note: You are allowed to modify the array elements to become negative integers.

ArrayBinary SearchGreedySortingHeap (Priority Queue)

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Problem Breakdown

Understanding the Minimum Sum of Squared Difference Problem

Let's break down this LeetCode problem and understand what makes it challenging in interview settings.

Problem Statement

You are given two positive 0-indexed integer arrays nums1 and nums2, both of length n. The sum of squared difference of arrays nums1 and nums2 is defined as the sum of (nums1[i] - nums2[i])2 for each 0 <= i < n. You are also given two positive integers k1 and k2. You can modify any of the elements of nums1 by +1 or -1 at most k1 times. Similarly, you can modify any of the elements of nums2 by +1 or -1 at most k2 times. Return the minimum sum of squared difference after modifying array nums1 at most k1 times and modifying array nums2 at most k2 times. Note: You are allowed to modify the array elements to become negative integers.

MediumProblem #2333
LeetCode

Minimum Sum of Squared Difference

Related Topics

ArrayBinary SearchGreedySortingHeap (Priority Queue)

How PhantomCodeAI Helps

Get real-time assistance for Minimum Sum of Squared Difference problems during coding interviews. PhantomCodeAI provides instant solutions and explanations.

Examples

# Example 1

Input
nums1 = [1,2,3,4], nums2 = [2,10,20,19], k1 = 0, k2 = 0
Output
579

# Example 2

Input
nums1 = [1,4,10,12], nums2 = [5,8,6,9], k1 = 1, k2 = 1
Output
43

Constraints

n == nums1.length == nums2.length
1 <= n <= 105
0 <= nums1[i], nums2[i] <= 105
0 <= k1, k2 <= 109

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Solve Minimum Sum of Squared Difference — You are given two positive 0-indexed integer arrays nums1 and nums2, both of len...

Here's the optimal approach using Array:

def solve(input):
# Optimal O(n) solution
return result

Time: O(n)  |  Space: O(n)

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Frequently Asked Questions

Common questions about solving Minimum Sum of Squared Difference and using PhantomCodeAI during coding interviews.

How does PhantomCodeAI help with LeetCode problems during a coding interview?
PhantomCodeAI reads the problem from a screenshot or listens to it via audio, then generates a complete solution with a step-by-step approach and time/space complexity, so you can focus on explaining your reasoning rather than getting stuck on implementation.
Which programming languages does PhantomCodeAI support?
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Does PhantomCodeAI work with HackerRank, CodeSignal, and CoderPad?
Yes — it works alongside LeetCode, HackerRank, CodeSignal, CoderPad, and HackerEarth, plus any browser-based coding environment.
Can PhantomCodeAI handle follow-up questions and modifications?
Yes. Capture the modified problem by screenshot or audio and get an updated solution within seconds, including new edge cases and optimizations.
Is PhantomCodeAI detectable during live interviews?
PhantomCodeAI runs as a native desktop overlay that does not appear in screen shares, recordings, or proctoring software, and works with Zoom, Google Meet, Microsoft Teams, and major coding platforms.
Should I still practice these problems on my own first?
Yes. The most durable preparation is solving problems unaided first, then using AI afterward to review your approach, complexity, and missed edge cases — use it to debrief and learn, not to skip the reps.

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