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What is complexity of insertion in binary search tree?
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.
Definition of almost complete binary tree?
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.
What is the concept used in binary sort?
The concept used in binary sort, often referred to as binary search, is based on dividing a sorted array into halves to efficiently locate a target value. It works by comparing the target with the middle element of the array; if they match, the search is complete. If the target is less than the middle element, the search continues in the lower half; if greater, it proceeds to the upper half. This process repeats, halving the search space with each iteration, leading to a time complexity of O(log n).
Can a binary tree be empty?
yes, why not,
Advantages and disadvantages of binary search tree?
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.
What is the time complexity of searching a binary search tree?
The time complexity of searching a binary search tree is O(log n), where n is the number of nodes in the tree.
What is the time complexity for finding an element in a binary search 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.
What is the time complexity of operations on a balanced binary search tree?
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.
In binary search tree n equals nodes h equals height of tree what is time complexity?
O(h)
What is the time complexity of binary tree traversal?
The time complexity of binary tree traversal is O(n), where n is the number of nodes in the tree.
What is the time complexity of inorder traversal in a binary tree?
The time complexity of inorder traversal in a binary tree is O(n), where n is the number of nodes in the tree.
what is the complexity of binary search?
Deezzzz Nutzzzz
Does binary tree and binary search tree same?
no they are not same
What are the key differences between a binary search tree and an AVL tree in terms of their structure and performance?
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.
How can you merge two binary search trees into a single binary search tree?
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.
What is the time complexity of a binary search algorithm?
The time complexity of a binary search algorithm is O(log n), where n is the number of elements in the sorted array being searched.
How can you balance a binary search tree to optimize its performance?
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.
