Consider the array with elements: 18, 10, 20, 5, 8, 9, 3. Applying the heapify() to convert the list to a minimum heap rearranges the elements to: 18 10 3 58 9 20 3 10 9 5 8 18 20 359 10 8 18 20 3 10 18 58 9 20 Consider DFS in the graph below starting form node E. The next node visited in the partial traversal EHGCF will be node A. A E H. True False Consider the following maximum heap: 20 10 18 5 8 9 4. After inserting node 15, the heap elements will rearrange to 15 20 18 10 8945 15 18 20 4 98 10 5 20 15 18 10 8945 20 10 18 158945

Consider the array with elements: 18, 10, 20, 5, 8, 9, 3. Applying the heapify() to convert the list to a minimum heap rearranges the elements to: 18 10 3 58 9 20 3 10 9 5 8 18 20 359 10 8 18 20 3 10 18 58 9 20 Consider DFS in the graph below starting form node E. The next node visited in the partial traversal EHGCF will be node A. A E H. True False Consider the following maximum heap: 20 10 18 5 8 9 4. After inserting node 15, the heap elements will rearrange to 15 20 18 10 8945 15 18 20 4 98 10 5 20 15 18 10 8945 20 10 18 158945

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Create two singly linked lists A and B to represents elements in the following set A and B respectively. 3. A = { 5, 6, 8, 9, 10, 11} B = { 1, 6, 2, 9, 3, 11, 4} Develop an algorithm and implement the same to represent only intersection of two lists A and B and print the same.
The list that follows is a maximum-heap. What will the array look like after removing the node with the highest key? Prior to extraction: 30 50 16 60 59 95 77 61 72 63 30 50 16 60 59 Following extraction:
: Implement an algorithm to delete a node in the middle (i.e., any node butthe first and last node, not necessarily the exact middle) of a singly linked list, given only access tothat node.EXAMPLElnput:the node c from the linked lista->b->c->d->e->fResult: nothing is returned, but the new linked list looks like a->b->d->e->f
30. In the implementation for a breadth-first search we studied, a queue was used. The code below replaces the queue with a stack. List the pre-order enumeration that the vertices in the graph below are visited using this modified method, starting from vertex 0. } 3 /** stack-based search */ static void modSearch (Graph G, int start) { Stack S new AStack (G.n()); S.push(start); } 6 G.setMark (start, VISITED); while (S.length) > 0) { } modSearch: intv S.pop(); PreVisit (G, v); for (int w = G.first (v); w < G.n(); w = G.next(v, w)) if (G.getMark (w) == UNVISITED) { G.setMark (w, VISITED); S.push(w);
: Implement an algorithm to delete a node in the middle (i.e., any node butthe first and last node, not necessarily the exact middle) of a singly linked list, given only access tothat node.EXAMPLElnput:the node c from the linked list a->b->c->d->e->fResult: nothing is returned, but the new linked list looks like a ->b->d->e->f
Beginning with a singly linked list composed of 5 nodes, draw step-by-step the process of removing index 3 from the list.
Execute the Depth First Search algorithm for the depicted graph. When bypassing, consider the order of numbering. In response, write the sequence of queue / stack states. Your answer 3 2 6 5 4 8 7 (10) 9
2 3 4 5 6 7 8 9 Merge k sorted linked lists and return it as one sorted list. Analyze and describe its complexity. 61 62 63 64 65 66 67 68 69 70 71 72 from heapq import heappop, heapreplace, heapify from queue import PriorityQueue 10 11 class ListNode (object): 12 """ ListNode Class""" 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 def merge_k_lists (lists): 37 """ Merge List """ 38 dummy = ListNode (None) 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 # Definition for singly-linked list. def __init__(self, val): self.val = val self.next = None def merge_k_lists (lists): """ Merge Lists """ dummy = node = ListNode (0) list_h= [(n.val, n) for n in lists if n] heapify(list_h) while list_h: _n_val = list_h[0] if n_val.next is None: heappop (list_h) #only change heap size when necessary else: heapreplace(list_h, (n_val.next.val, n_val.next)) node.next = n_val node = node.next return dummy.next curr = dummy q = PriorityQueue () for node in lists:…
Consider the Queue ADT: Queue: enqueue(x) adds x to the back of the queue dequeue () removes element at the front of the queue size() returns number of elements in queue Select all options that allow for an efficient implementation based on the discussions from class. For any array implementation, you can assume the array is large enough so that making a larger one is not needed when pushing an item to the stack. You can assume that a linked list will have both a head and tail reference. Using an array with the front of the queue at the front of the array. Using an array with the front of the queue at the back of the array. Using a singly linked list with the front of the queue at the head of the list. Using a singly linked list with the front of the queue at the tail of the list. None of these choices allows for an efficient implementation of all methods.
Graphs implement the BFS and DFS graph traversal algorithms as a part of the code below (graph.cpp). The code reads in a graph from the sample_edges.txt file (to be put in the same directory as your code), and returns an adjacency list. The adjacency list is a vector, where each element is in turn a vector of (adjacent vertex, edge weight) pairs. Typedef is used to enhance readability. You are to use the adjacency list returned to implement the BFS and DFS algorithms. A header for the helper function is also included to implement DFS recursively. A utility function that prints the queue is provided to help you with the BFS implementation. Note that the BFS an DFS order the vertices are printed could be different from that shown in the test comments. graph.cpp /* Graph read from file, and represnted as adjacency list. To implement DFS and BFS on the graph */ #include <iostream> #include <sstream> #include <fstream> #include <vector> #include…
Prob 2 Given a list of x objects, create a program that performs the following operation: -Get the first and last object and place them both at the start of the list. Example: QWERT becomes QTWER Find the worst case time complexity if the solution will be implemented using a single linked list. Give both the EQUATION AND THE BIG-O NOTATION.
O(N) is the order of growth execution time of the enqueue operation when using the ArrayBoundedQueue class, assuming a queue size of N. T or F