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Leetcode #2919: Minimum Increment Operations to Make Array Beautiful

In this guide, we solve Leetcode #2919 Minimum Increment Operations to Make Array Beautiful in Python and focus on the core idea that makes the solution efficient.

You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.

Leetcode

Problem Statement

You are given a 0-indexed integer array nums having length n, and an integer k. You can perform the following increment operation any number of times (including zero): Choose an index i in the range [0, n - 1], and increase nums[i] by 1.

Quick Facts

  • Difficulty: Medium
  • Premium: No
  • Tags: Array, Dynamic Programming

Intuition

The problem breaks into overlapping subproblems, so caching results prevents exponential repetition.

A carefully chosen DP state captures exactly what we need to build the final answer.

Approach

Define the DP state and recurrence, then compute states in the correct order.

Optionally compress space once the recurrence is clear.

Steps:

  • Choose a DP state definition.
  • Write the recurrence and base cases.
  • Compute states in the correct order.

Example

Input: nums = [2,3,0,0,2], k = 4 Output: 3 Explanation: We can perform the following increment operations to make nums beautiful: Choose index i = 1 and increase nums[1] by 1 -> [2,4,0,0,2]. Choose index i = 4 and increase nums[4] by 1 -> [2,4,0,0,3]. Choose index i = 4 and increase nums[4] by 1 -> [2,4,0,0,4]. The subarrays with a size of 3 or more are: [2,4,0], [4,0,0], [0,0,4], [2,4,0,0], [4,0,0,4], [2,4,0,0,4]. In all the subarrays, the maximum element is equal to k = 4, so nums is now beautiful. It can be shown that nums cannot be made beautiful with fewer than 3 increment operations. Hence, the answer is 3.

Python Solution

class Solution: def minIncrementOperations(self, nums: List[int], k: int) -> int: f = g = h = 0 for x in nums: f, g, h = g, h, min(f, g, h) + max(k - x, 0) return min(f, g, h)

Complexity

The time complexity is O(n)O(n)O(n), where nnn is the length of the array. The space complexity is O(1)O(1)O(1).

Edge Cases and Pitfalls

Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.

Summary

This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.


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