{ "data": { "question": { "questionId": "3177", "questionFrontendId": "2892", "boundTopicId": null, "title": "Minimizing Array After Replacing Pairs With Their Product", "titleSlug": "minimizing-array-after-replacing-pairs-with-their-product", "content": null, "translatedTitle": null, "translatedContent": null, "isPaidOnly": true, "difficulty": "Medium", "likes": 4, "dislikes": 0, "isLiked": null, "similarQuestions": "[]", "exampleTestcases": "[2,3,3,7,3,5]\n20\n[3,3,3,3]\n6", "categoryTitle": "Algorithms", "contributors": [], "topicTags": [], "companyTagStats": null, "codeSnippets": null, "stats": "{\"totalAccepted\": \"21\", \"totalSubmission\": \"39\", \"totalAcceptedRaw\": 21, \"totalSubmissionRaw\": 39, \"acRate\": \"53.8%\"}", "hints": [ "If there is a zero in the array, then the answer would be 1.", "Merge all adjacent ones (since 1 * 1 = 1 and k >= 1).", "Let dp[i] be the answer to the problem for the first i elements.", "To calculate dp[i], try to brute-force all indices j such that elements from j to i are merged together to create a new element.", "For a fixed i, you could go backward from ith elements and multiply them together until the product is at most k. Now if you are currently on index j and you've merged all elements from jth element to ith element, dp[i] = min(dp[i], dp[j - 1] + 1).", "The above backward moving can be done at most 2 * log2(k) times. Since we've merged adjacent ones, every two adjacent elements have a product of at least 2.", "So the total time complexity would be n * 2 * log2(k)." ], "solution": null, "status": null, "sampleTestCase": "[2,3,3,7,3,5]\n20", "metaData": "{\n \"name\": \"minArrayLength\",\n \"params\": [\n {\n \"name\": \"nums\",\n \"type\": \"integer[]\"\n },\n {\n \"type\": \"integer\",\n \"name\": \"k\"\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.

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

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
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\"], \"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 1.18

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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.

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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

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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.

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

Dart 2.17.3

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Your code will be run directly without compiling

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