Binary Search Tree

Binary Search Tree:

Binary Search Tree Traversal Methods

How are they different from Binary Trees?:

How are they different from Binary Trees? In computer science , a binary tree is a tree data structure in which each node has at most two children . Typically the child nodes are called left and right . Binary trees are commonly used to implement binary search trees and binary heaps .

Slide 3:

Size? Height Root Leaves 9 2 4 1,4,7,13 Highlight below To reveal answers Note : The above tree is neither a sorted nor a balanced binary tree

Binary Search Tree:

Binary Search Tree In computer science , a binary search tree ( BST ) is a binary tree data structure which has the following properties: Each node (item in the tree) has a distinct value. Both the left and right subtrees must also be binary search trees. The left subtree of a node contains only values less than the node's value. The right subtree of a node contains only values greater than or equal to the node's value.

Diagram of a Binary Search Tree:

Diagram of a Binary Search Tree Size? Depth Root Leaves 9 8 3 1,4,7,13 Highlight below To reveal answers

Major advantage of Binary Search Trees?:

Major advantage of Binary Search Trees? The major advantage of binary search trees over other data structures is that the related sorting algorithms and search algorithms such as in-order traversal can be very efficient.

Which two programming processes are used when searching a Binary Search tree?:

Which two programming processes are used when searching a Binary Search tree? Recursive Process or Iterative Process In an ordinary Binary tree, you Have three iterative Procedures that can Be used. Preorder Postorder inorder

Recursive or Iterative?:

Recursive or Iterative? The above code was written in Python (wikipedia example) We begin by examining the root node . If the tree is null, the value we are searching for does not exist in the tree. Otherwise, if the value equals the root, the search is successful. If the value is less than the root, search the left subtree. Similarly, if it is greater than the root, search the right subtree. This process is repeated until the value is found or the indicated subtree is null. If the searched value is not found before a null subtree is reached, then the item must not be present in the tree

Insertion in a Binary Search Tree:

Insertion in a Binary Search Tree True or false Insertion Insertion begins as a search would begin

Insertion:

Insertion Insertion Insertion begins as a search would begin; if the root is not equal to the value, we search the left or right subtrees as before. Eventually, we will reach an external node and add the value as its right or left child, depending on the node's value. In other words, we examine the root and recursively insert the new node to the left subtree if the new value is less than the root, or the right subtree if the new value is greater than or equal to the root.

Example in C++ (insertion):

Example in C++ (insertion)

Deletion:

Deletion What are the ‘rules’ for deleting. Leaf Node with one child c) Node with two children

Deletion:

Deletion Deleting a leaf (leaf with no children is easy –just remove it) Deleting a node with one child –how? Deleting a node with two children –how do we do it?