Suppose we have an ArrayHeap that uses the array representation from class (also called "tree representation 3B" in lecture). Recall that in this representation that the leftmost item is unused.Consider a heap with the following underlying array:-8-29.1101012Suppose we perform an in-order traversal of the heap represented by this array. What will be the last value in the in-order traversal?O -8O 5O-2O 9O 8O 1O 10O 12

Heap Sort for decreasing order using min heap,heap sort for increasing order using max heap:-

Suppose we have an Arrayieap that uses the array representation from class (also called "tree representation 3B" Consider a heap with the following underlying array: -8 5 -2 9 8 01 10 10 12 Suppose we perform an in-order traversal of the heap represented by this array. What will be the last value in the in-orde -8 -2

Suppose we have an Arrayieap that uses the array representation from class (also called "tree representation 3B" Consider a heap with the following underlying array: -8 5 -2 9 8 01 10 10 12 Suppose we perform an in-order traversal of the heap represented by this array. What will be the last value in the in-orde -8 -2

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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The Min-priority Queue is an abstract data type (ADT) for maintaining a collection of elements,each with an associated value called a key. The ADT supports the following operations:• INSERT(Q,x): insert the element x into the queue Q.• MIN(Q): returns the element of Q with the smallest key.• EXTRACT-MIN (Q): removes and returns the element of Q with the smallest key.Implement in Java the Min-priority Queue ADT defined above using a) an array based binary heap b) a binary search tree. Observe that the ADT implementation operations should be in the form q.insert(x),q.min(), etc. Explain in the report your implementation, noting the running time (using bigOh notation) of each operation in both implementations. c) What are the worst-case running times of the three ADT operations when theunderlying BST is self-balancing? Briefly explain your answer. d) Implement an extension of BST that allows MIN and EXTRACT-MIN operations in O(1). Briefly describe your implementation in the report. Hint:…
Heap Given a maxheap (keeps the largest value at the root), which has 4 functions push(h,v), v<-pop(h), new(h), and b<-isNotEmpty(h), where h is a heap, v is the value pushed/popped on the heap, new creates a new empty heap, isNotEmpty tests the heap, and b is a Boolean. What will the pseudocode below print? new(h); push(h, 10); push(h, 200); push(h, 0); push(h, 999); push(h, 5); while (isNotEmpty(h)) do {print(pop(h),” “);} print(“\n”);
Implement a priority queue using a heapordered binary tree, but use a triply linked structure instead of an array. You will needthree links per node: two to traverse down the tree and one to traverse up the tree. Yourimplementation should guarantee logarithmic running time per operation, even if nomaximum priority-queue size is known ahead of time.
Is there a heap, denoted by T, that can store seven different components and yet produce the elements of T in sorted order when preorder traversal is performed on T? Why not try an inorder traversal instead? A postorder traversal could be an option.
Implement a priority queue using a heapordered binary tree, but instead of an array, use a triply linked structure. Each node will require three links: two to traverse down the tree and one to traverse up the tree. Even if no maximum priority-queue size is known ahead of time, your implementation should guarantee logarithmic running time per operation.
Use a triply linked structure as opposed to an array for implementing a priority queue using a heapordered binary tree. Each node will require three links: two to move up the tree and one to move down it. Even if the maximum size of the priority queue is unknown at the outset, your solution should nonetheless provide logarithmic running times for each operation.
Implement a priority list using a heapordered binary tree, but instead of an array, use a triply linked structure. Each node will require three links: two to travel down the tree and one to traverse up the tree. Even if no maximum priority-queue size is known ahead of time, your implementation should ensure logarithmic running time per operation.
Construct a priority queue using a heapordered binary tree, but instead of an array, use a triply linked structure. Each node will require three links: two to go down the tree and one to traverse up the tree. Even if no maximum priority-queue size is specified ahead of time, your solution should ensure logarithmic running time per operation.
What happens to the array mentioned below after Build-Max-Heap has been applied on it? You can illustrate with a tree structure as demonstrated during class. 4 1 3 2 16 9 10 14 8 7
Create a birthday reminder system using a minheap such that theordering on the heap is done each day according to days remaining until the individual’s birthday. Keep in mind that when abirthday passes, the heap must be reordered.
Using the simulated link technique, create an array version of a binary search tree based on an array implementation of a binary tree. Each array element must keep a reference to the data element put there as well as the array locations of the left and right children. You must also keep a list of accessible array positions where elements have been deleted so that you may reuse those slots.code in java
Let's assume that a binary heap is represented using a binary tree such that each node may have a left child node and a right child node. For this type of representation, we can still label the nodes of the tree in the same way as we label the nodes for an array representation. That is, the root node has a label 1. In general, for a node with label i, its left child node will have a label 2i and the right child has a label 2i+1. For any i with 1 <= I <= n , Terry says that the following easy algorithm will walk you from the root node to the node with label i: First find the binary representation P of i. Start with the rightmost bit (least significant bit) of P, walk down from the root as follow: For a 0 bit, walk to the left child, for a 1 bit walk to the right child. At the end, you’ll reach the node with label i. Which of the following is the most appropriate? A. Terry’s algorithm is wrong and not fixable. B. Terry’s algorithm is right. C. Terry's algorithm can be…