If we represent a priority queue using asorted LinkList in decreasing order?what is the time complexity for1) add O (n)2) peekMin O (n/2 )3) removeMin operations O ( log n) V

Since in a priority queue the most priority elemnts is at the front so in linkedlist which is in…

Answered: If we represent a priority queue using…

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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In the worst case, the number of comparisons needed to search a singly linked list of length n for a given element is?a) log2 nb) n⁄2c) log2 n – 1d) n
java code will need to return the traversal of the nodes in DFS order, wherethe traversal starts from Node/Vertex 0.When you follow the traversal process as specified - the complexity of the solution will be linear as shown below.Time Complexity: O(V + E), where V is the number of Vertices andE is the number of Edges respectively.Space Complexity: O(V )The linear space complexity would come from the recursion (AKA ”recursionstack”) you employ to traverse the Graph.
Inserting a value in an unsorted linked list has the following big-O running time a. O (1) b. O (log n) c. None of the above d. O (n) e. O (n2)
The removeMin operation for both the linked and array implementation of a Minheap is: O O(1) O O(logn) O O(n?) O O(n) O O(nlogn)
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A set is a container that stores a collection of sorted unique elements. When we use a sorted linked structure to implement Set ADT, the time complexity of find(x), insert(x) and remove(x) are all O(n). Group of answer choices True False
Even when employing a self-balancing binary search tree to construct binary tree sort, the worst-case time required is O(n log n), making it slower than merge sort.

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If we represent a priority queue using a sorted LinkList in decreasing order? what is the time complexity for 1) add O (n) 2) peekMin O (n/2 ) 3) removeMin operations O (log n )