{ "data": { "question": { "questionId": "3178", "questionFrontendId": "2919", "boundTopicId": null, "title": "Minimum Increment Operations to Make Array Beautiful", "titleSlug": "minimum-increment-operations-to-make-array-beautiful", "content": "

You are given a 0-indexed integer array nums having length n, and an integer k.

\n\n

You can perform the following increment operation any number of times (including zero):

\n\n\n\n

An array is considered beautiful if, for any subarray with a size of 3 or more, its maximum element is greater than or equal to k.

\n\n

Return an integer denoting the minimum number of increment operations needed to make nums beautiful.

\n\n

A subarray is a contiguous non-empty sequence of elements within an array.

\n\n

 

\n

Example 1:

\n\n
\nInput: nums = [2,3,0,0,2], k = 4\nOutput: 3\nExplanation: We can perform the following increment operations to make nums beautiful:\nChoose index i = 1 and increase nums[1] by 1 -> [2,4,0,0,2].\nChoose index i = 4 and increase nums[4] by 1 -> [2,4,0,0,3].\nChoose index i = 4 and increase nums[4] by 1 -> [2,4,0,0,4].\nThe 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].\nIn all the subarrays, the maximum element is equal to k = 4, so nums is now beautiful.\nIt can be shown that nums cannot be made beautiful with fewer than 3 increment operations.\nHence, the answer is 3.\n
\n\n

Example 2:

\n\n
\nInput: nums = [0,1,3,3], k = 5\nOutput: 2\nExplanation: We can perform the following increment operations to make nums beautiful:\nChoose index i = 2 and increase nums[2] by 1 -> [0,1,4,3].\nChoose index i = 2 and increase nums[2] by 1 -> [0,1,5,3].\nThe subarrays with a size of 3 or more are: [0,1,5], [1,5,3], [0,1,5,3].\nIn all the subarrays, the maximum element is equal to k = 5, so nums is now beautiful.\nIt can be shown that nums cannot be made beautiful with fewer than 2 increment operations.\nHence, the answer is 2.\n
\n\n

Example 3:

\n\n
\nInput: nums = [1,1,2], k = 1\nOutput: 0\nExplanation: The only subarray with a size of 3 or more in this example is [1,1,2].\nThe maximum element, 2, is already greater than k = 1, so we don't need any increment operation.\nHence, the answer is 0.\n
\n\n

 

\n

Constraints:

\n\n\n", "translatedTitle": null, "translatedContent": null, "isPaidOnly": false, "difficulty": "Medium", "likes": 260, "dislikes": 16, "isLiked": null, "similarQuestions": "[]", "exampleTestcases": "[2,3,0,0,2]\n4\n[0,1,3,3]\n5\n[1,1,2]\n1", "categoryTitle": "Algorithms", "contributors": [], "topicTags": [ { "name": "Array", "slug": "array", "translatedName": null, "__typename": "TopicTagNode" }, { "name": "Dynamic Programming", "slug": "dynamic-programming", "translatedName": null, "__typename": "TopicTagNode" } ], "companyTagStats": null, "codeSnippets": [ { "lang": "C++", "langSlug": "cpp", "code": "class Solution {\npublic:\n long long minIncrementOperations(vector& nums, int k) {\n \n }\n};", "__typename": "CodeSnippetNode" }, { "lang": "Java", "langSlug": "java", "code": "class Solution {\n public long minIncrementOperations(int[] nums, int k) {\n \n }\n}", "__typename": "CodeSnippetNode" }, { "lang": "Python", "langSlug": "python", "code": "class Solution(object):\n def minIncrementOperations(self, nums, k):\n \"\"\"\n :type nums: List[int]\n :type k: int\n :rtype: int\n \"\"\"\n ", "__typename": "CodeSnippetNode" }, { "lang": "Python3", "langSlug": "python3", "code": "class Solution:\n def minIncrementOperations(self, nums: List[int], k: int) -> int:\n ", "__typename": "CodeSnippetNode" }, { "lang": "C", "langSlug": "c", "code": "long long minIncrementOperations(int* nums, int numsSize, int k) {\n \n}", "__typename": "CodeSnippetNode" }, { "lang": "C#", "langSlug": "csharp", "code": "public class Solution {\n public long MinIncrementOperations(int[] nums, int k) {\n \n }\n}", "__typename": "CodeSnippetNode" }, { "lang": "JavaScript", "langSlug": "javascript", "code": "/**\n * @param {number[]} nums\n * @param {number} k\n * @return {number}\n */\nvar minIncrementOperations = function(nums, k) {\n \n};", "__typename": "CodeSnippetNode" }, { "lang": "TypeScript", "langSlug": "typescript", "code": "function minIncrementOperations(nums: number[], k: number): number {\n \n};", "__typename": "CodeSnippetNode" }, { "lang": "PHP", "langSlug": "php", "code": "class Solution {\n\n /**\n * @param Integer[] $nums\n * @param Integer $k\n * @return Integer\n */\n function minIncrementOperations($nums, $k) {\n \n }\n}", "__typename": "CodeSnippetNode" }, { "lang": "Swift", "langSlug": "swift", "code": "class Solution {\n func minIncrementOperations(_ nums: [Int], _ k: Int) -> Int {\n \n }\n}", "__typename": "CodeSnippetNode" }, { "lang": "Kotlin", "langSlug": "kotlin", "code": "class Solution {\n fun minIncrementOperations(nums: IntArray, k: Int): Long {\n \n }\n}", "__typename": "CodeSnippetNode" }, { "lang": "Dart", "langSlug": "dart", "code": "class Solution {\n int minIncrementOperations(List nums, int k) {\n \n }\n}", "__typename": "CodeSnippetNode" }, { "lang": "Go", "langSlug": "golang", "code": "func minIncrementOperations(nums []int, k int) int64 {\n \n}", "__typename": "CodeSnippetNode" }, { "lang": "Ruby", "langSlug": "ruby", "code": "# @param {Integer[]} nums\n# @param {Integer} k\n# @return {Integer}\ndef min_increment_operations(nums, k)\n \nend", "__typename": "CodeSnippetNode" }, { "lang": "Scala", "langSlug": "scala", "code": "object Solution {\n def minIncrementOperations(nums: Array[Int], k: Int): Long = {\n \n }\n}", "__typename": "CodeSnippetNode" }, { "lang": "Rust", "langSlug": "rust", "code": "impl Solution {\n pub fn min_increment_operations(nums: Vec, k: i32) -> i64 {\n \n }\n}", "__typename": "CodeSnippetNode" }, { "lang": "Racket", "langSlug": "racket", "code": "(define/contract (min-increment-operations nums k)\n (-> (listof exact-integer?) exact-integer? exact-integer?)\n )", "__typename": "CodeSnippetNode" }, { "lang": "Erlang", "langSlug": "erlang", "code": "-spec min_increment_operations(Nums :: [integer()], K :: integer()) -> integer().\nmin_increment_operations(Nums, K) ->\n .", "__typename": "CodeSnippetNode" }, { "lang": "Elixir", "langSlug": "elixir", "code": "defmodule Solution do\n @spec min_increment_operations(nums :: [integer], k :: integer) :: integer\n def min_increment_operations(nums, k) do\n \n end\nend", "__typename": "CodeSnippetNode" } ], "stats": "{\"totalAccepted\": \"11.1K\", \"totalSubmission\": \"33.5K\", \"totalAcceptedRaw\": 11143, \"totalSubmissionRaw\": 33520, \"acRate\": \"33.2%\"}", "hints": [ "There needs to be at least one value among 3 consecutive values in the array that is greater than or equal to k.", "The problem can be solved using dynamic programming.", "Let dp[i] be the minimum number of increment operations required to make the subarray consisting of the first i values beautiful, while also having the value at nums[i] >= k.", "dp[0] = max(0, k - nums[0]), dp[1] = max(0, k - nums[1]), and dp[2] = max(0, k - nums[2]).", "dp[i] = max(0, k - nums[i]) + min(dp[i - 1], dp[i - 2], dp[i - 3]) for i in the range [3, n - 1].", "The answer to the problem is min(dp[n - 1], dp[n - 2], dp[n - 3])." ], "solution": null, "status": null, "sampleTestCase": "[2,3,0,0,2]\n4", "metaData": "{\n \"name\": \"minIncrementOperations\",\n \"params\": [\n {\n \"name\": \"nums\",\n \"type\": \"integer[]\"\n },\n {\n \"type\": \"integer\",\n \"name\": \"k\"\n }\n ],\n \"return\": {\n \"type\": \"long\"\n }\n}", "judgerAvailable": true, "judgeType": "large", "mysqlSchemas": [], "enableRunCode": true, "enableTestMode": false, "enableDebugger": true, "envInfo": "{\"cpp\": [\"C++\", \"

Compiled with clang 11 using the latest C++ 20 standard.

\\r\\n\\r\\n

Your code is compiled with level two optimization (-O2). AddressSanitizer is also enabled to help detect out-of-bounds and use-after-free bugs.

\\r\\n\\r\\n

Most standard library headers are already included automatically for your convenience.

\"], \"java\": [\"Java\", \"

OpenJDK 17. Java 8 features such as lambda expressions and stream API can be used.

\\r\\n\\r\\n

Most standard library headers are already included automatically for your convenience.

\\r\\n

Includes Pair class from https://docs.oracle.com/javase/8/javafx/api/javafx/util/Pair.html.

\"], \"python\": [\"Python\", \"

Python 2.7.12.

\\r\\n\\r\\n

Most libraries are already imported automatically for your convenience, such as array, bisect, collections. If you need more libraries, you can import it yourself.

\\r\\n\\r\\n

For Map/TreeMap data structure, you may use sortedcontainers library.

\\r\\n\\r\\n

Note that Python 2.7 will not be maintained past 2020. For the latest Python, please choose Python3 instead.

\"], \"c\": [\"C\", \"

Compiled with gcc 8.2 using the gnu11 standard.

\\r\\n\\r\\n

Your code is compiled with level one optimization (-O1). AddressSanitizer is also enabled to help detect out-of-bounds and use-after-free bugs.

\\r\\n\\r\\n

Most standard library headers are already included automatically for your convenience.

\\r\\n\\r\\n

For hash table operations, you may use uthash. \\\"uthash.h\\\" is included by default. Below are some examples:

\\r\\n\\r\\n

1. Adding an item to a hash.\\r\\n

\\r\\nstruct hash_entry {\\r\\n    int id;            /* we'll use this field as the key */\\r\\n    char name[10];\\r\\n    UT_hash_handle hh; /* makes this structure hashable */\\r\\n};\\r\\n\\r\\nstruct hash_entry *users = NULL;\\r\\n\\r\\nvoid add_user(struct hash_entry *s) {\\r\\n    HASH_ADD_INT(users, id, s);\\r\\n}\\r\\n
\\r\\n

\\r\\n\\r\\n

2. Looking up an item in a hash:\\r\\n

\\r\\nstruct hash_entry *find_user(int user_id) {\\r\\n    struct hash_entry *s;\\r\\n    HASH_FIND_INT(users, &user_id, s);\\r\\n    return s;\\r\\n}\\r\\n
\\r\\n

\\r\\n\\r\\n

3. Deleting an item in a hash:\\r\\n

\\r\\nvoid delete_user(struct hash_entry *user) {\\r\\n    HASH_DEL(users, user);  \\r\\n}\\r\\n
\\r\\n

\"], \"csharp\": [\"C#\", \"

C# 10 with .NET 6 runtime

\"], \"javascript\": [\"JavaScript\", \"

Node.js 16.13.2.

\\r\\n\\r\\n

Your code is run with --harmony flag, enabling new ES6 features.

\\r\\n\\r\\n

lodash.js library is included by default.

\\r\\n\\r\\n

For Priority Queue / Queue data structures, you may use 5.3.0 version of datastructures-js/priority-queue and 4.2.1 version of datastructures-js/queue.

\"], \"ruby\": [\"Ruby\", \"

Ruby 3.1

\\r\\n\\r\\n

Some common data structure implementations are provided in the Algorithms module: https://www.rubydoc.info/github/kanwei/algorithms/Algorithms

\"], \"swift\": [\"Swift\", \"

Swift 5.5.2.

\"], \"golang\": [\"Go\", \"

Go 1.21

\\r\\n

Support https://godoc.org/github.com/emirpasic/gods@v1.18.1 library.

\"], \"python3\": [\"Python3\", \"

Python 3.10.

\\r\\n\\r\\n

Most libraries are already imported automatically for your convenience, such as array, bisect, collections. If you need more libraries, you can import it yourself.

\\r\\n\\r\\n

For Map/TreeMap data structure, you may use sortedcontainers library.

\"], \"scala\": [\"Scala\", \"

Scala 2.13.7.

\"], \"kotlin\": [\"Kotlin\", \"

Kotlin 1.9.0.

\"], \"rust\": [\"Rust\", \"

Rust 1.58.1

\\r\\n\\r\\n

Supports rand v0.6\\u00a0from crates.io

\"], \"php\": [\"PHP\", \"

PHP 8.1.

\\r\\n

With bcmath module

\"], \"typescript\": [\"Typescript\", \"

TypeScript 5.1.6, Node.js 16.13.2.

\\r\\n\\r\\n

Your code is run with --harmony flag, enabling new ES2022 features.

\\r\\n\\r\\n

lodash.js library is included by default.

\"], \"racket\": [\"Racket\", \"

Run with Racket 8.3.

\"], \"erlang\": [\"Erlang\", \"Erlang/OTP 25.0\"], \"elixir\": [\"Elixir\", \"Elixir 1.13.4 with Erlang/OTP 25.0\"], \"dart\": [\"Dart\", \"

Dart 2.17.3

\\r\\n\\r\\n

Your code will be run directly without compiling

\"]}", "libraryUrl": null, "adminUrl": null, "challengeQuestion": null, "__typename": "QuestionNode" } } }