{"id":34250,"date":"2024-11-01T09:26:02","date_gmt":"2024-11-01T09:26:02","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=34250"},"modified":"2024-11-01T10:57:59","modified_gmt":"2024-11-01T10:57:59","slug":"c-coding-test-course-utilizing-time-complexity-2","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/34250\/","title":{"rendered":"C++ Coding Test Course, Utilizing Time Complexity"},"content":{"rendered":"
\n

One of the most important things when preparing for coding tests is understanding and optimizing problem-solving skills along with time complexity. This article will detail the process of solving problems considering time complexity using C++.<\/p>\n

Problem: Longest Increasing Subsequence<\/h2>\n

This problem involves finding the length of the longest increasing subsequence in a given integer array.<\/p>\n

Problem Description<\/h3>\n

Given an integer array nums<\/code>, return the length of the longest increasing subsequence. A subsequence is formed by selected elements from the array that maintain their original order but do not need to be contiguous.<\/p>\n

Example<\/h3>\n
\n    Input: nums = [10, 9, 2, 5, 3, 7, 101, 18]\n    Output: 4\n    Explanation: The longest increasing subsequence is [2, 3, 7, 101], with a length of 4.\n    <\/pre>\n
Approach<\/h3>\n
This problem can be solved using a combination of Dynamic Programming and Binary Search. Considering time complexity, the following approaches can be utilized:<\/p>\n
1. Approach using Dynamic Programming<\/h4>\n
First, we record the length of the increasing subsequence that ends with each element. Then, we can iterate through each element and compare it with all previous elements to update the length of the subsequence if possible.<\/p>\n
2. Combined with Binary Search<\/h4>\n
Ultimately, we use an array to record the end elements of subsequences and apply binary search on this array to find the position to insert the current element. This method allows us to achieve more optimized performance.<\/p>\n
Implementation<\/h3>\n
Below is the code to solve this problem using C++:<\/p>\n
\n#include <iostream>\n#include <vector>\n#include <algorithm>\n\nusing namespace std;\n\nint lengthOfLIS(vector<int>& nums) {\n    if (nums.empty()) return 0;\n\n    vector<int> dp;\n    for (int num : nums) {\n        auto it = lower_bound(dp.begin(), dp.end(), num);\n        if (it == dp.end()) {\n            dp.push_back(num);\n        } else {\n            *it = num;\n        }\n    }\n    return dp.size();\n}\n\nint main() {\n    vector<int> nums = {10, 9, 2, 5, 3, 7, 101, 18};\n    cout << \"Length of Longest Increasing Subsequence: \" << lengthOfLIS(nums) << endl;\n    return 0;\n}\n    <\/code><\/pre>\n
Time Complexity Analysis<\/h3>\n
The time complexity of this problem is O(n log n). A binary search is performed for each element to find the appropriate position, and the time complexity of binary search is log n. Therefore, the overall time complexity is O(n log n), and the space complexity is O(n).<\/p>\n
Conclusion<\/h3>\n
For problems like finding the longest increasing subsequence in an array, it is important to combine Dynamic Programming and Binary Search to reduce time complexity. Utilizing useful functions and data structures provided by C++’s STL can help write more efficient code.<\/p>\n
This article explained time complexity analysis and algorithm problem-solving methods using C++. I hope it will be helpful in your future coding test preparation!<\/p>\n<\/article>\n","protected":false},"excerpt":{"rendered":"
One of the most important things when preparing for coding tests is understanding and optimizing problem-solving skills along with time complexity. This article will detail the process of solving problems considering time complexity using C++. Problem: Longest Increasing Subsequence This problem involves finding the length of the longest increasing subsequence in a given integer array. … \ub354 \ubcf4\uae30 “C++ Coding Test Course, Utilizing Time Complexity”<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[111],"tags":[],"class_list":["post-34250","post","type-post","status-publish","format-standard","hentry","category-c-coding-test-tutorials-2"],"yoast_head":"\nC++ Coding Test Course, Utilizing Time Complexity - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/34250\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"C++ Coding Test Course, Utilizing Time Complexity - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"One of the most important things when preparing for coding tests is understanding and optimizing problem-solving skills along with time complexity. 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