{ "data": { "question": { "questionId": "3088", "questionFrontendId": "2832", "boundTopicId": null, "title": "Maximal Range That Each Element Is Maximum in It", "titleSlug": "maximal-range-that-each-element-is-maximum-in-it", "content": null, "translatedTitle": null, "translatedContent": null, "isPaidOnly": true, "difficulty": "Medium", "likes": 24, "dislikes": 0, "isLiked": null, "similarQuestions": "[]", "exampleTestcases": "[1,5,4,3,6]\n[1,2,3,4,5]", "categoryTitle": "Algorithms", "contributors": [], "topicTags": [ { "name": "Array", "slug": "array", "translatedName": null, "__typename": "TopicTagNode" }, { "name": "Stack", "slug": "stack", "translatedName": null, "__typename": "TopicTagNode" }, { "name": "Monotonic Stack", "slug": "monotonic-stack", "translatedName": null, "__typename": "TopicTagNode" } ], "companyTagStats": null, "codeSnippets": null, "stats": "{\"totalAccepted\": \"707\", \"totalSubmission\": \"965\", \"totalAcceptedRaw\": 707, \"totalSubmissionRaw\": 965, \"acRate\": \"73.3%\"}", "hints": [ "For each index, we must find the nearest bigger element on both its left and right sides.", "First, find the nearest bigger element on the left side of each element. To do that, use a stack of pairs (value, index).", "Start iterating from the beginning of the array.", "Whenever we reach an element nums[index], while the top of the stack is smaller than nums[index], we pop from the stack.", "If there is an element left in the stack, top.index + 1 would be the answer. Otherwise, 0 is the answer.", "After that, we push (nums[index], index) to the stack and go for the next element." ], "solution": null, "status": null, "sampleTestCase": "[1,5,4,3,6]", "metaData": "{\n \"name\": \"maximumLengthOfRanges\",\n \"params\": [\n {\n \"name\": \"nums\",\n \"type\": \"integer[]\"\n }\n ],\n \"return\": {\n \"type\": \"integer[]\"\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.

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

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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.

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

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

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Python 2.7.12.

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

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

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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.

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

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

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

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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

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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

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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.

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

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lodash.js library is included by default.

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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

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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

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

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

Python 3.10.

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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.

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Kotlin 1.9.0.

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Rust 1.58.1

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Supports rand v0.6\\u00a0from crates.io

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

PHP 8.1.

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With bcmath module

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

TypeScript 5.1.6, Node.js 16.13.2.

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

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lodash.js library is included by default.

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

Run with Racket 8.3.

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Dart 2.17.3

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Your code will be run directly without compiling

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