1)
If heap is in an array, then to find left child of any index will be (root node index)*2
To find right child of any index will be (root node index)*2 + 1
To find parent node of any index will be (index)/2
For all these, it will take constant time with some computation.
But in linked list every node is pointing to it’s left side node address and right side node address and parent address.
So to find left child and right child and parent node for any node is
Left child = Given node->next
Right child = Given node->prev
Parent = given node->parent
It is also constant time but no computation like in array.
2)
In array, Insertion will take O(log n). because we can insert the key in right position by binary search. Where in linked list, we search the key in sequential order, so it will take O(n) time
In array, find max will take constant time (i.e O(1)). Because the first index it self is a root node, so no need to search. Where in linked list, find max will also take constant time, because the head node will point to the root node which is max in the heap.
In array, extract max will take O(log n), after deleting max node, we need replace that position with max number in the array, so we need to search, we follow binary search which will take O(log n). where in linked list, to find max also we need search, searching is sequential. So it will take O(n).
Originally we stored our heap in an array. Consider instead storing our heap as a doubly...
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Write a C program insertion and deletion functions for a max heap represented as a linked binary tree. Assume that each node has a parent field as well as the usual left child, right child, and key fields. -Condition : Do not use Array representation. Use the following structure. typedef struct node *treePointer; typedef struct node { int key; treePointer parent; treePointer leftChild, rightChild; }; - INPUT i k : Insert the node with the key value of k in...
Write a C program insertion and deletion functions for a max heap represented as a linked binary tree. Assume that each node has a parent field as well as the usual left child, right child, and key fields. -Condition : Do not use Array representation. Use the following structure. typedef struct node *treePointer; typedef struct node { int key; treePointer parent; treePointer leftChild, rightChild; }; - INPUT i k : Insert the node with the key value of k in...
Consider the following complete binary tree is stored in an array the way we learned during heap lecture. The root node is stored at index 1. The last node (47) is stored at index heapsize. If you want to build a heap from the array using the heapify(), what position of the array you start doing percolate Down in heapify()? Answer: What is the run-time to build a heap from an array of size n using heapify() process ? OC...
Assume that a heap is implemented using an array called items where the root of the heap is stored in items[0]. Provide the mathematical proof of the following formulas that calculate the indices of the children and parent of any node items[i]. Left child of items[i] is items [2xi + 1] - Right child of items[i] is items [2xi + 2] Parent of items[i] is items[[(i-1)/2]]
Instead of using Union to perform an Insert into a binomial heap H, we can write code that directly does the insert. Note that we keep the list of roots of H sorted by degree. Insert(H, item) let x be a pointer to a new node x with Nil in its parent, child and sibling pointers x.key = item x.degree = 0 loop let y be a pointer to the rst root in H's list of roots exit when y...
This class implements a doubly linked list in which the nodes are of the class DLNode. This class must implement the interface DLListADT.java that specifies the public methods in this class. The header for this class will then be public class DLList implements DLListADT This class will have three private instance variables: • private DLNode front. This is a reference to the first node of the doubly linked list. • private DLNode rear. This is a reference to the last...
In class, we discussed the priority queue (PQ) ADT implemented using min-heap. In a min-heap, the element of the heap with the smallest key is the root of the binary tree. On the other hand, a max-heap has as root the element with the biggest key, and the relationship between the keys of a node and its parent is reversed of that of a min-heap. We also discussed an array-based implementation of heaps. In this assignment, your task is to...
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must be coded in c++ without any STL libraries sadly :( so im struggling on this problem, any help would be greatly appreciated, thanks in advance! :) assignment is due tomorrow and im really struggling on this last question :( a. Begin by implementing a BST for integers. The underlying structure is a linked list. You need these methods: i. BST(); -- Constructor ii. void put (int) – Inserts a value into the BST. iii. Void put(int[] a) – Inserts...