Starting Out with Java: From Control Structures through Data Structures (4th Edition) (What's New in Computer Science)
4th Edition
ISBN: 9780134787961
Author: Tony Gaddis, Godfrey Muganda
Publisher: PEARSON
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Chapter 21, Problem 6SA
Program Plan Intro
Complete binary tree:
A complete binary tree is a binary tree in which all levels are completely filled except possibly the last level and the last level has all keys as left as possible.
Example:
Explanation:
The above complete binary tree has “6” nodes and “5” edges. All the levels are completely filled except the last level of the tree.
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In the worst-case situation, binary tree sort using a self-balancing binary search tree requires O(n log n) time, which is slower than merge sort.
A worst-case scenario for a binary tree sort that uses a self-balancing binary search tree is O(n log n) time. The merge sort method is much faster than this one.
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Chapter 21 Solutions
Starting Out with Java: From Control Structures through Data Structures (4th Edition) (What's New in Computer Science)
Ch. 21.1 - Prob. 21.2CPCh. 21.1 - Prob. 21.3CPCh. 21 - Prob. 1MCCh. 21 - Prob. 2MCCh. 21 - Prob. 3MCCh. 21 - Prob. 4MCCh. 21 - Prob. 5MCCh. 21 - Prob. 6MCCh. 21 - Prob. 7MCCh. 21 - Prob. 8MC
Ch. 21 - Prob. 9MCCh. 21 - Prob. 10MCCh. 21 - Prob. 11TFCh. 21 - Prob. 12TFCh. 21 - Prob. 13TFCh. 21 - Prob. 14TFCh. 21 - Prob. 15TFCh. 21 - Prob. 16TFCh. 21 - Prob. 17TFCh. 21 - Prob. 18TFCh. 21 - Prob. 19TFCh. 21 - Prob. 20TFCh. 21 - Prob. 21TFCh. 21 - Prob. 1FTECh. 21 - Prob. 2FTECh. 21 - Prob. 3FTECh. 21 - Prob. 1SACh. 21 - Prob. 2SACh. 21 - Prob. 3SACh. 21 - Prob. 4SACh. 21 - What is a priority queue?Ch. 21 - Prob. 6SACh. 21 - Prob. 7SACh. 21 - Prob. 1AWCh. 21 - Prob. 2AWCh. 21 - Prob. 3AWCh. 21 - Prob. 4AWCh. 21 - Prob. 5AWCh. 21 - Prob. 6AWCh. 21 - Prob. 7AWCh. 21 - Prob. 4PCCh. 21 - Prob. 6PC
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- In the worst situation, binary tree sort using a self-balancing binary search tree takes O(n log n) time, slower than merge sort.arrow_forwardEven in the worst case, a self-balancing binary search tree takes O(n log n) time to sort a binary tree, substantially longer than merge sort.arrow_forwardSome implementations of binary search trees allow for duplicates by introducing the following rule: for each node n. the left subtree of n contains only nodes smaller than n, and the right subtree of n contains only nodes greater or equal to n. Implement a successor and predecessor operation on such a tree. Discuss their time complexity as a function of the height of the tree.arrow_forward
- The height of a full binary tree is at most (N: number of nodes): O O(1) O(log n) O O(n) O O(n?) O None of the abovearrow_forwardGiven the following Binary Tree, what is the result of a post-order traversal? What is the height of node N?arrow_forwardIn which order would one have to insert the keys 1 to n for an n ∈ N in a binary search tree,in order to minimize the number of comparisons during construction?arrow_forward
- From the below array representation of a binary tree, find the father of node Q? z E xY A N Node H 5 7 8 9 10 | 11 12 13 Index 1 4 6 O a. Y O b. Z O c. E O d. X 3. 2.arrow_forwardWhat is the best-case scenario in terms of search complexity for binary search trees? O(N-1). N is number of nodes in the tree O(log N). N is height of the tree O(log N). N is number of nodes in the tree O(N). N is number of nodes in the tree O(N+1). N is number of nodes in the treearrow_forwardA worst-case binary tree sort using a self-balancing binary search tree takes O(n log n) time. Merge sort is substantially faster.arrow_forward
- Given a binary tree, design an algorithm which creates a linked list of all the nodesat each depth (e.g., if you have a tree with depth D, you'll have D linked lists).arrow_forwardDraw separate trees with 8 nodes that are either: balanced; binary tree; neither of these. As per the tree, write a pseudo code in python to carry out a breadth first search the binary tree. Explain the answer brieflyarrow_forwardChoose the correct answerarrow_forward
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