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Q: What are the advantages and disadvantages of AVL trees?
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Advantages of AVL TREE?

not much memory wastage.


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How many rotations during deletion in avl trees?

2


IS AVL-Tree IS binary tree?

An AVL tree is another balanced binary search tree. Named after their inventors, Adelson-Velskii and Landis, they were the first dynamically balanced trees to be proposed. Like red-black trees, they are not perfectly balanced, but pairs of sub-trees differ in height by at most 1, maintaining an O(logn) search time. Addition and deletion operations also take O(logn) time.Definition of an AVL treeAn AVL tree is a binary search tree which has the following properties: The sub-trees of every node differ in height by at most one.Every sub-tree is an AVL tree.


Write A program to implement insertion using AVL trees?

yes


What is the complexity of AVL tree?

The time complexity of operations in an AVL tree is O(log n), where n is the number of nodes in the tree. This is because AVL trees are balanced, ensuring that the height of the tree remains logarithmic with respect to the number of nodes.


What are the applications of avl tree?

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.


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Which is better - AVL or Red Black Trees?

It depends on what the tree is being used for. If the tree is being used to store data that is not going to be modified very much, than AVL trees are probably better. In most other cases, I'd say Red-Black trees are better.


What are disadvantages of AVL tree?

Some disadvantages of AVL trees include the complexity of insertion and deletion operations due to the need for maintaining balance, which can affect performance. Additionally, the overhead of storing balance factors or heights for each node can increase memory usage. Balancing operations can also be more costly compared to simpler binary search trees.


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