avl trees. avl node structure the avl node structure follows the same structure as the binary search...
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AVL Node Structure The AVL node structure follows the
same structure as the binary search tree, with the addition of a term to store the balance factor.
Node { int data; Node *left; Node *right; int balanceFactor;}
AVL Insert Now that we have seen how to
balance a tree, we are ready to look at the algorithms.
The search and retrieval algorithms are the same as for any binary tree.
However, because the AVL tree is a special case of a binary search tree, you will want to use an inorder traversal method.
AVL Insert As with the BST, all inserts take place at
a leaf (or leaf-like) node. To find the appropriate leaf node, we
follow the path from the root, going left when the new data node’s key is less than the root node’s key and right when it’s greater.
Once we have found the leaf, we connect the new node to the leaf and begin to back out of the tree.
AVL Insert It is at this point that the AVL
insert differs from the BST insert. As we back out of the tree, we
constantly check the balance of each node.
When we find that a node is out of balance, we balance it and then continue up the tree.
Note that not all inserts will produce an out-of-balance tree.
AVL Delete The delete logic is similar to the
BST delete logic. Again, however, we must make
sure that we include the logic to keep the tree balanced.
Relationship to Fibonacci Let N be the fewest number of
nodes in an AVL tree of height H It is straightforward to show thatN = F(H+3) - 1,where F(k) is the kth Fibonacci number
For large values of k, Fk 1
5
1 52
k
Solving for H if we solve this near equality for H,
we getH 1.44 log2 N
This means that the height of an AVL tree with N nodes is no more than 44% larger than the optimal height of a binary search tree with N nodes