![BINARY SEARCH TREE ALGORITHM
SearchElement (TREE,VAL)
Step 1: If Tree-> DATA=VAL OR TREE=NULL
RETURN TREE
ELSE
IF VAL < TREE -> DATA
RETURN SearchElement(TREE->LEFT,VAL)
ELSE
RETURN SearchElement(TREE->RIGHT,VAL)
[END OF IF]
[END OF IF]
Step 2 : EXIT](https://image.slidesharecdn.com/07taruntiwari-200413102918/85/Binary-Search-Tree-in-Data-Structure-7-320.jpg)
![BINARY SEARCH TREE INSERTION
ALGORITHM
INSERT (TREE,VAL)
Step 1: IF TREE= NULL
Allocate memory for TREE
SET TREE -> DATA=VAL
SET TREE ->LEFT = TREE->RIGHT =NULL
ELSE
IF VAL < TREE->DATA
INSERT (TREE->LEFT , VAL)
ELSE
INSERT (TREE->RIGHT , VAL)
[END OF IF]
[END OF IF]
Step 2: EXIT](https://image.slidesharecdn.com/07taruntiwari-200413102918/85/Binary-Search-Tree-in-Data-Structure-10-320.jpg)
Binary Search Tree in Data Structure
- 1. BIRLA INSTITUTE OF TECHNOLOGY MESRA, JAIPUR CAMPUS TOPIC:- BINARY SEARCH TREE NAME:- TARUN TIWARI ROLL NO.:- MCA/25007/18 CLASS:- MCA 2ND SEM.
- 2. BINARY SEARCH TREE • In Binary Search Tree, all the left subtree elements should be less than root data and all the right subtree elements should be greater than root data. This is called binary search tree property. • This property should be satisfied at every node in the tree.
- 3. Examples Binary search trees Not a binary search tree 5 10 30 2 25 45 5 10 45 2 25 30 5 10 30 2 25 45
- 4. Data NODE LEFT CHILD RIGHT CHILD Struct node { int data; struct node *leftChild; struct node *rightChild; }; STRUCTURE OF TREE NODE
- 5. SEARCHING BINARY SEARCH TREE Example: Suppose T is the tree being searched: • If we are searching for 15, then we are done. • If we are searching for a key < 15, then we should search in the left subtree. • If we are searching for a key > 15, then we should search in the right subtree.
- 7. BINARY SEARCH TREE ALGORITHM SearchElement (TREE,VAL) Step 1: If Tree-> DATA=VAL OR TREE=NULL RETURN TREE ELSE IF VAL < TREE -> DATA RETURN SearchElement(TREE->LEFT,VAL) ELSE RETURN SearchElement(TREE->RIGHT,VAL) [END OF IF] [END OF IF] Step 2 : EXIT
- 8. INSERTION BINARY SEARCH TREE
- 9. • IMPLEMENTING INSERTION RECURSIVELY
- 10. BINARY SEARCH TREE INSERTION ALGORITHM INSERT (TREE,VAL) Step 1: IF TREE= NULL Allocate memory for TREE SET TREE -> DATA=VAL SET TREE ->LEFT = TREE->RIGHT =NULL ELSE IF VAL < TREE->DATA INSERT (TREE->LEFT , VAL) ELSE INSERT (TREE->RIGHT , VAL) [END OF IF] [END OF IF] Step 2: EXIT
- 11. DELETION BINARY SEARCH TREE Case 1: the node is a leaf Delete it immediately Case 2: the node has one child Adjust a pointer from the parent to bypass that node
- 12. Case 3: the node has 2 children Replace the key of that node with the minimum element at the right subtree
- 13. COMPLEXITY IN BST Operation Average Worst Case Best Case Search O(log n) O(n) O(1) Insertion O(log n) O(n) O(1) Deletion O(log n) O(n) O(1)
- 14. APPLICATIONS OF BST • Used in many search applications where data is constantly entering/leaving, such as the map and set objects in many languages' libraries. • Storing a set of names, and being able to lookup based on a prefix of the name. (Used in internet routers.) • Storing a path in a graph, and being able to reverse any subsection of the path in O(log n) time. (Useful in travelling salesman problems). • Finding square root of given number • allows you to do range searches efficiently.
- 15. THANK YOU