If it is an unbalanced binary tree, O( ln( n ) / ln( 2 ) ) is best-case. Worst case is O( n ).
If it is balanced, worst case is O( ln( n ) / ln( 2 ) ).
By using Depth First Search or Breadth First search Tree traversal algorithm we can print data in Binary search tree.
A binary search tree is already ordered. An in order traversal will give you a sorted list of nodes.
Binary Search Tree and AVL Tree are dictionary data structures. They are used for many search operations and also those operations where data is constantly inserted and deleted. AVL trees provide a better efficiency than BST as they maintain their upper bound of O(n*log n) through rotations.Eg: the map and set library in c++ isimplementedusing trees.
Yes because there is no real practical use for a binary tree other than something to teach in computer science classes. A binary tree is not used in the real world, a "B tree" is.
A strictly binary tree is one where every node other than the leaves has exactly 2 child nodes. Such trees are also known as 2-trees or full binary trees. An extended binary tree is a tree that has been transformed into a full binary tree. This transformation is achieved by inserting special "external" nodes such that every "internal" node has exactly two children.
An AVL tree is a self-balancing binary search tree where the heights of the two child subtrees of any node differ by at most one. This ensures that the tree remains balanced, leading to faster search operations. In contrast, a binary search tree does not have this balancing property, which can result in an unbalanced tree and slower search times. Overall, AVL trees are more efficient for search operations due to their balanced nature, while binary search trees may require additional operations to maintain balance and optimize performance.
Yes, an AVL tree is a type of binary search tree (BST) that is balanced to ensure efficient searching and insertion operations.
The time complexity of operations on a balanced binary search tree, such as insertion, deletion, and search, is O(log n), where n is the number of nodes in the tree. This means that these operations can be performed efficiently and quickly, even as the size of the tree grows.
no they are not same
A heap is a complete binary tree where each node has a value greater than or equal to its children, and it is typically used for priority queue operations like inserting and removing the maximum element. On the other hand, a binary search tree is a binary tree where each node has a value greater than all nodes in its left subtree and less than all nodes in its right subtree, and it is used for efficient searching, insertion, and deletion operations.
No, binary search trees are not always balanced. Balancing a binary search tree involves ensuring that the height difference between the left and right subtrees of each node is at most 1. Unbalanced binary search trees can lead to inefficient search and insertion operations.
To merge two binary search trees into a single binary search tree, you can perform an in-order traversal on each tree to extract their elements, combine the elements into a single sorted list, and then construct a new binary search tree from the sorted list. This process ensures that the resulting tree maintains the binary search tree property.
Performing a binary search tree inorder traversal helps to visit all nodes in the tree in ascending order, making it easier to search for specific values or perform operations like sorting and printing the elements in a sorted order.
The complexity of binary search tree : Search , Insertion and Deletion is O(h) . and the Height can be of O(n) ( if the tree is a skew tree). For Balanced Binary Trees , the Order is O(log n).
By using Depth First Search or Breadth First search Tree traversal algorithm we can print data in Binary search tree.
To balance a binary search tree and optimize its performance, you can use techniques like rotations, reordering nodes, and maintaining a balance factor. These methods help ensure that the tree is evenly distributed, reducing the time complexity of operations like searching and inserting.
self depend friend"s............