In the field of data structures, an AA tree is a type of balanced search tree that offers efficient operations for insertion, deletion, and searching. It is named after its inventors Arne Andersson and Kathleen Meagher. The AA tree maintains a specific property that ensures its balance.

## Structure of an AA Tree

An AA tree is composed of nodes that contain key-value pairs. Each node has a left child, a right child, and a level field.

The level field indicates the level of the node in the tree, with leaf nodes having a level of 1. The levels are used to enforce the balancing property of the AA tree.

### The Balancing Property

The balancing property of an AA tree states that for any node, its left child’s level is either equal to or one less than its own level, and its right child’s level is strictly less than its own level.

This balancing property ensures that the height difference between any two subtrees in an AA tree is at most one. As a result, operations such as insertion and deletion can be performed efficiently without causing significant imbalances.

## Operations on an AA Tree

1. **Insertion:** When inserting a new key-value pair into an AA tree, it follows a similar process as in other binary search trees. However, after insertion, the tree may violate the balancing property.

To restore balance after insertion, we perform __restructuring__ operations called skewing and splitting:

**Skewing:**If a newly inserted node violates the balancing property by having two consecutive right children with the same level, we perform a right rotation on the parent node to fix it.**Splitting:**If a newly inserted node violates the balancing property by having a right child with the same level, we perform a left rotation on the grandparent node followed by a right rotation on the parent node to fix it.

2. **Deletion:** Similar to insertion, deletion in an AA tree initially follows the process of other binary search trees. However, after deletion, we may need to perform restructuring operations to maintain balance.

To restore balance after deletion, we perform __restructuring__ operations called *deminotion*:

**Deminotion:**If a node has only one child and it does not violate the balancing property, we simply decrement its level.**Deminotion + Balancing:**If a node has only one child and it violates the balancing property, we perform skewing and splitting operations as necessary before demoting it.

## Advantages of AA Trees

The use of AA trees offers several advantages:

**Balanced Structure:**The balancing property ensures that an AA tree remains balanced throughout various insertions and deletions. This guarantees efficient search operations with optimal time complexity.**Ease of Implementation:**AA trees are relatively simple to implement compared to other self-balancing tree structures such as red-black trees or AVL trees.**Efficient Operations:**The restructuring operations performed during insertion and deletion are straightforward and can be completed in constant time (O(1)). This makes AA trees efficient for dynamic data sets.

## In Conclusion

An AA tree is a balanced search tree that maintains its balance through the use of levels. It offers efficient insertion, deletion, and searching operations while maintaining a balanced structure. With their ease of implementation and efficient operations, AA trees are a valuable tool in managing dynamic data sets.