Table of Contents
Why is the use of binary search to find a value in a sorted linked list of values is not a good idea?
Binary Search is divide and conquer approach to search an element from the list of sorted element. In Linked List we can do binary search but it has time complexity O(n) that is same as what we have for linear search which makes Binary Search inefficient to use in Linked List.
Why binary search technique Cannot be used in singly linked list?
Explanation of using Binary Search In arrays, binary search takes O(1) time to access middle element. But memory allocation for the singly linked list is non-contiguous, which makes finding the middle element difficult and time consuming.
Is there any difference between binary tree and binary search tree?
A Binary Tree is a non-linear data structure in which a node can have 0, 1 or 2 nodes. Individually, each node consists of a left pointer, right pointer and data element. A Binary Search Tree is an organized binary tree with a structured organization of nodes.
What is the main reason to use binary search trees?
The main reason to use a binary search tree is the fact that it extends the capability of a normal array. An array is a data type that stores data points contiguously in sequence.
What is the base 2 log of a binary search?
Eight times the nodes gives three extra steps. Sixteen times the nodes gives four extra steps. And so on. The base 2 log of the first number in these pairs is the second number in these pairs. It’s base 2 log because this is a binary search (you halve the problem space each step).
How many types of traversals are there in binary search tree?
There are 3 kinds of traversals that are done typically over a binary search tree. All these traversals have a somewhat common way of going over the nodes of the tree. This traversal first goes over the left subtree of the root node, then accesses the current node, followed by the right subtree of the current node.
How do you find the number of nodes in a binary tree?
For me the easiest way was to look at a graph of log2(n), where n is the number of nodes in the binary tree. As a table this looks like: log2(n) = d log2(1) = 0 log2(2) = 1 log2(4) = 2 log2(8) = 3 log2(16)= 4 log2(32)= 5 log2(64)= 6