Answered: A worst-case binary tree sort using a…

A worst-case binary tree sort using a self-balancing binary search tree takes O(n log n) time. Merge sort is substantially faster.

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Concept explainers

Merge sort

Merge Sort recursively sorts a given collection of numbers or elements by using the divide and conquer strategy in less time. It is one of the most used algorithms, with the worst-case time complexity of O (n log n). It was invented by John Von Neumann. The algorithm continuously divides an array into sub-arrays until each sub-array consists of a single element. It then merges those sub-arrays to produce a sorted array.

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A worst-case binary tree sort using a self-balancing binary search tree takes O(n log n) time. Merge sort is substantially faster.

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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.
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
Binary tree sort employing a self-balancing binary search tree takes O(n log n) time in the worst scenario, slower than merge sort.
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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