AVL Tree
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, ensuring logarithmic time complexity for operations like insertion, deletion, and lookup. It maintains balance through rotations (single or double) after updates to preserve the height invariant, making it efficient for dynamic datasets requiring frequent modifications. Named after its inventors Adelson-Velsky and Landis, it is a foundational data structure in computer science for ordered data management.
Developers should learn AVL trees when implementing systems that need guaranteed O(log n) performance for search, insert, and delete operations in memory-constrained or real-time applications, such as in-memory databases, caching layers, or algorithm libraries. It is particularly useful in scenarios where data changes frequently and balanced tree properties are critical to avoid performance degradation, unlike simpler binary search trees that can become unbalanced. Mastery of AVL trees also builds essential skills for understanding more advanced balanced trees like red-black trees or B-trees.