### Binary Search Tree Diagram#### Diagram Explanation:The diagram illustrates a binary search tree structure, which is a data structure used to maintain a sorted sequence of elements, allowing for efficient insertion, deletion, and lookup operations.- **Nodes:** - E (root) - C, H (children of E) - B, D (children of C) - A (child of B) - F (child of H) - G (child of F)- **Levels of Nodes:** - Level 1: Node E - Level 2: Nodes C, H - Level 3: Nodes B, D, F - Level 4: Nodes A, GEach node in the tree has 0, 1, or 2 children. In this structure, left children are typically smaller than their parent nodes, while right children are larger.### Text:2. In the binary search tree above, finding node E requires one comparison and finding node A requires four comparisons. What is the expected number of comparisons required to find a node chosen at random?

Answered: D 2. In the binary search tree above,…

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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Similar questions

If a binary search tree has n nodes, what are the lowest and highest nodes? Your answer should be supported by mathematical logic.
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.
In a binary search tree, to remove a node N that has left child C1 and right child C2, we do the following: Group of answer choices We make C1 the left child of N’s parent and C2 the right child of N’s parent We make C1 the right child of N’s parent and C2 the left child of N’s parent We find the largest item L in N’s left subtree, copy the contents of L to N, and remove L We find the smallest item S in N’s right subtree, copy the contents of S to N, and remove N We find the largest item L in N's right subtree, copy the contents of L to N, and remove L
TREE C: 1. Is tree Ca binary search tree? 2. If tree C is a binary search tree, is it balanced or skewed? If it is not a binary search tree, why not?
BACKTRACKING
Question in image. No need for the code. Please explain the algorithm in a simple way with the answer. Thank you
In the binary search tree, write a function that takes in a root, p, and checks whether the tree rooted in p is a binary search tree or not. What is the time complexity of your function? def is_bst(self, p: Node):
Let T be a binary search tree with n nodes, in which n > 0. When T is linear, the search algorithm makes key comparisons, in the unsuccassful case.
The minimum height of a binary search tree win n keys is log2 n. Select one: True or False
In a binary search tree, to remove a node N that has parent P and one child C, we do the following: Group of answer choices If C is the right child of N, we make C the right child of P, and if C is the left child of N, we make C the left child of P If C is the right child of N, we make C the left child of P, and if C is the left child of N, we make C the right child of P If N is the left child of P, we make C the left child of P and if N is the right child of P, we make C the right child of P If N is the left child of P, we make C the right child of P and if N is the right child of P, we make C the left child of P none of the above
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.

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D 2. In the binary search tree above, finding node E requires one comparison and finding node A requires four comparisons. What is the expected number of comparisons required to find a node chosen at random?