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.

Sort the array using insertion sort algorithm list ={18,57,8,89,7}

Python: Written without libraries method find_ansestors , that takes in an index i and returns all ancestors of node located at index i. What is the time complexity of your function? class ArrayBinaryTree: def __init__(self): self._heap = [] def find_ancestors(self, i: int): if(i==0): return;

Heapsort uses a heap to sort different elements. The use of a heap makes this algorithm the most efficient in the worst case for sorting.

Performing sequential search for an item that is not present in an unsorted list has Best-Case running time equals to: 1 log(n) n n2

Trace the execution of Bubble-sort on the list: 30, 7, 21, 42, 57, 90, 3, 11

Write Algorithm procedure code to illustrates the procedure for Fibonacci search. Here n, the number of data elements is such that:i) Fk+1 > (n+1); andii) Fk + m = (n +1) for some m ≥ 0, where Fk+1 and Fk are two consecutiveFibonacci numbers.