One can build a max-heap of n elements in O(n) time. True False Given a binary search tree of n nodes, one can sort the keys therein in O(n) time. True False Consider a comparison based sorting algorithm and its decision tree on n elements. Then, the path from the root to every leaf node in the tree must have N(n log n) edges. True False

One can build a max-heap of n elements in O(n) time. True False Given a binary search tree of n nodes, one can sort the keys therein in O(n) time. True False Consider a comparison based sorting algorithm and its decision tree on n elements. Then, the path from the root to every leaf node in the tree must have N(n log n) edges. True False

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

Using a self-balancing binary search tree, binary tree sort is nevertheless slower than merge sort, taking O(n log n) time in the worst case.
Binary tree sort employing a self-balancing binary search tree takes O(n log n) time in the worst scenario, slower than merge sort.
Even when employing a self-balancing binary search tree to construct binary tree sort, the worst-case time required is O(n log n), making it slower than merge sort.
You are given an array A[1, ..., n]. Describe an algorithm (proper/efficient pseudocode required) that checks whether the given array is a Heap, and outputs 'yes/no'.
Given a sorted array of n comparable items A, create a binary search tree from the items in A which has height h <= log: n. Your algorithm must create the tree in O(n) time.