O(log n)
At each step of insertion you are either going to the left child or the right child. In a balanced tree, this will effectively cut the number of possible comparisons in half each time.
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).
Advantages:BST is fast in insertion and deletion etc when balanced.Very efficient and its code is easier than link lists.Disadvantages:Shape of the tree depends upon order of insertion and it can be degenerated.Searching takes long time.
A complete binary tree is a binary tree in which every level, except possibly the last, is completely filled, and all nodes are as far left as possible.
yes, why not,
In a binary tree, each level can have a maximum of (2^n) nodes, where (n) is the level number starting from 0. For a binary tree with 3 levels (0, 1, 2), the minimum number of nodes occurs when each level has at least one node. Therefore, the minimum number of nodes is 1 (at level 0) + 1 (at level 1) + 1 (at level 2) = 3 nodes.
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).
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.
The time complexity of searching a binary search tree is O(log n), where n is the number of nodes in the tree.
The time complexity for finding an element in a binary search tree is O(log n), where n is the number of nodes in the tree.
Yes, an AVL tree is a type of binary search tree (BST) that is balanced to ensure efficient searching and insertion operations.
A binary search tree is a data structure where each node has at most two children, and the left child is less than the parent while the right child is greater. 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. The key difference between a binary search tree and an AVL tree is that AVL trees are balanced, meaning that the heights of the subtrees are kept in check to ensure faster search times. This balancing comes at the cost of additional overhead in terms of memory and time complexity for insertion and deletion operations. Overall, AVL trees provide faster search times compared to binary search trees, but with increased complexity in terms of maintenance.
O(h)
The time complexity of binary tree traversal is O(n), where n is the number of nodes in the tree.
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.
The time complexity of inorder traversal in a binary tree is O(n), where n is the number of nodes in the tree.
A binary search tree is a data structure that organizes data in a hierarchical manner, where each node has at most two children. It allows for efficient searching, insertion, and deletion operations with a time complexity of O(log n) on average. On the other hand, a hashtable is a data structure that uses a hash function to map keys to values, providing constant time complexity O(1) for operations like insertion, deletion, and retrieval. However, hash tables do not maintain any specific order of elements, unlike binary search trees which are ordered based on their keys.
Advantages:BST is fast in insertion and deletion etc when balanced.Very efficient and its code is easier than link lists.Disadvantages:Shape of the tree depends upon order of insertion and it can be degenerated.Searching takes long time.