time-complexity

问题 I have been trying to solve this problem in an efficient way. The problem is: Problem Statement Given a list of tuples in the form [(start1, end1), (start2, end2), (start3, end3)....(startn, endn)] where start and end are positive integers. Each tuple is to represent a time window, for example: [(1, 3), (73, 80)...] . Find the time (integer) where max concurrency occurs and get the tuples where max concurrency occurs. Constraints: start and end are integers of time and are between 0 to n For

问题 I have been trying to solve this problem in an efficient way. The problem is: Problem Statement Given a list of tuples in the form [(start1, end1), (start2, end2), (start3, end3)....(startn, endn)] where start and end are positive integers. Each tuple is to represent a time window, for example: [(1, 3), (73, 80)...] . Find the time (integer) where max concurrency occurs and get the tuples where max concurrency occurs. Constraints: start and end are integers of time and are between 0 to n For

问题 I'm working on the problem stated in the question statement. I know my solution is correct (ran the program) but I'm curious as to whether or not I'm analyzing my code (below) correctly. def parens(num) return ["()"] if num == 1 paren_arr = [] parens(num-1).each do |paren| paren_arr << paren + "()" unless "()#{paren}" == "#{paren}()" paren_arr << "()#{paren}" paren_arr << "(#{paren})" end paren_arr end parens(3), as an example, will output the following: ["()()()", "(()())", "(())()", "()(())

问题 I'm looking for an efficient JavaScript utility method that in O(n) will remove a set of items from an array in place . You can assume equality with the === operator will work correctly. Here is an example signature (written in TypeScript for type clarity) function deleteItemsFromArray<T>(array: T[], itemsToDelete: T[]) { ... } My thought is to do this in two passes. The first pass gets the indexes that need to be removed. The second pass then compacts the array by copying backwards from the

问题 This is the pseudo code I used for Kruskal's algorithm. The data structure I have used here is an adjacency matrix. I got the order of growth as n^2 . I want to know whether it is correct or not. Kruskal’s Pseudo code 1. Kruskal (n, m, E) 2. // Purpose to compute the minimum spanning tree using Kruskal's algorithm 3. // Inputs 4. n - Number of vertices in the graph 5. m - Number of edges in the graph 6. E - Edge list consisting of set of edges along with equivalent weight w - cost adjacency

问题 This is the pseudo code I used for Kruskal's algorithm. The data structure I have used here is an adjacency matrix. I got the order of growth as n^2 . I want to know whether it is correct or not. Kruskal’s Pseudo code 1. Kruskal (n, m, E) 2. // Purpose to compute the minimum spanning tree using Kruskal's algorithm 3. // Inputs 4. n - Number of vertices in the graph 5. m - Number of edges in the graph 6. E - Edge list consisting of set of edges along with equivalent weight w - cost adjacency

问题 I have to find time complexity of quick sort for BEST CASE INPUT in a c program & i have selected the last element of array as pivot. Now i know what input values i have to enter for best case, i.e., keep 1st middle element at the last place(pivot) & next pivot should be the next middle element. But i have to generate this kind of best case input array of very big sizes like 1000, 5000, 100000.., for quick sort. I can code, but can anyone please help me understand how to generate that kind of

问题 I am looking for a least time-complex algorithm that would solve a variant of the perfect sum problem (initially: finding all variable size subset combinations from an array [*] of integers of size n that sum to a specific number x ) where the subset combination size is of a fixed size k and return the possible combinations without direct and also indirect (when there's a combination containing the exact same elements from another in another order) duplicates. I'm aware this problem is NP

问题 I am trying to write the sublist search algorithm using Python. For reference : https://www.geeksforgeeks.org/sublist-search-search-a-linked-list-in-another-list/ Here is my code: def sublist(arr1,arr2): i = 0 j = 0 k = 0 if len(arr1) == 0: print('List1 Empty') if len(arr2) == 0: print('List 2 Empty') for j in range(0,len(arr2)): for i in range(0,len(arr1)): if arr1[i] != arr2[j]: break while arr1[i] == arr2 [j]: if i == len(arr1) - 1: return True i = i + 1 j = j + 1 if i == len(arr1): return

问题 I implemented Merge Sort and Quick Sort in C++, and I wanna get the execution times using each of two with many of cases those are already Sorted or not & has different size. #include <iostream> #include <ctime> #include <vector> #include <algorithm> using namespace std; void Merge(vector<int>& s, int low, int mid, int high) { int i = low; int j = mid + 1; int k = low; vector<int> u(s); while (i <= mid && j <= high) { if (s.at(i) < s.at(j)) { u.at(k) = s.at(i); i++; } else { u.at(k) = s.at(j)