Is Minimum Pair Removal to Sort Array I easy or hard?

The problem is classified as Easy, but the optimal implementation introduces concepts like heaps and linked list simulation. The core logic is straightforward once the dynamic adjacency updates are handled correctly.

Minimum Pair Removal to Sort Array I Python/Java solution

Python, Java, C++, Go, TypeScript, and Rust implementations follow the same idea: maintain adjacent pairs in a priority queue and update neighbors using a linked structure after each removal. Each language uses its standard priority queue and array or node representation.

How to solve Minimum Pair Removal to Sort Array I in O(n)?

An exact O(n) approach is generally not practical because selecting the next pair requires ordering candidates by priority. Using a heap introduces the O(log n) factor. The closest practical solution uses a priority queue with a doubly linked list, resulting in O(n log n) time.

What is the best approach for Minimum Pair Removal to Sort Array I?

The most efficient solution uses simulation with a min‑heap and a doubly linked list. The heap quickly selects the next candidate adjacent pair, while the linked list allows constant‑time removals and neighbor updates. This combination keeps the total complexity around O(n log n) with O(n) space.

Is Minimum Pair Removal to Sort Array I asked at Google/Amazon/Meta?

Problems that combine heaps, simulation, and dynamic adjacency structures appear frequently in interviews at companies like Amazon, Google, and Meta. Variants involving priority queues and linked list updates are common because they test data structure integration and careful implementation.

What data structure is used in Minimum Pair Removal to Sort Array I?

The typical solution uses a min‑heap (priority queue) to choose the next pair efficiently and a doubly linked list to manage element removals and neighbor updates. Arrays track node status, and lazy deletion handles outdated heap entries.

What is the time complexity of Minimum Pair Removal to Sort Array I?

The optimized simulation runs in O(n log n) time because each pair insertion or extraction from the priority queue costs O(log n). Every element participates in a limited number of updates, so the total heap operations remain proportional to the array size. Space complexity is O(n).

Description Hints 1 Solution Video 11:36

3507. Minimum Pair Removal to Sort Array I

Easy65.3% acceptance5 companies

Given an array nums, you can perform the following operation any number of times:

Select the adjacent pair with the minimum sum in nums. If multiple such pairs exist, choose the leftmost one.
Replace the pair with their sum.

Return the minimum number of operations needed to make the array non-decreasing.

An array is said to be non-decreasing if each element is greater than or equal to its previous element (if it exists).

Example 1:

Input: nums = [5,2,3,1]

Output: 2

Explanation:

The pair (3,1) has the minimum sum of 4. After replacement, nums = [5,2,4].
The pair (2,4) has the minimum sum of 6. After replacement, nums = [5,6].

The array nums became non-decreasing in two operations.

Example 2:

Input: nums = [1,2,2]

Output: 0

Explanation:

The array nums is already sorted.

Constraints:

1 <= nums.length <= 50
-1000 <= nums[i] <= 1000

Asked at 5 companies

Meta Microsoft

Google Amazon Bloomberg

Topics

Hints open one at a time

Hint 1

Simulate the operations

11:36

Still stuck?Read the written solution, or watch a walkthrough.

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1class Solution:
2    def minimumPairRemoval(self, nums: List[int]) -> int:
3        

Starter codePython 3Spaces: 4

Examples

Case 1Case 2

Input

[5,2,3,1]

Input

[1,2,2]

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