Author: Denis Kondratev

I've recently had the pleasure of immersing myself in Harrison Ferrone's Learning C# by Developing Games with Unity. I'd heard it was a great primer for those of us eager to get our feet wet in the gaming industry, and I can now confirm it's a game changer.

This book wasn't just written for tech-savvy gamers. It was written for the curious beginner, the coding newbie, and the Unity novice. Ferrone breaks down intimidating coding concepts into bite-sized, digestible chunks, making this complex world not only accessible but actually enjoyable.

Welcome back to the final article in our series on binary search trees in C#. In our previous articles, we explored the fundamentals of binary search trees and the self-balancing AVL trees. We learned that while AVL trees guarantee a balanced tree structure, they require significant computational overhead to maintain balance factors and execute multiple rotations.

In this article, we will delve into another self-balancing binary search tree, the red-black tree. Red-black trees are designed to strike a balance between the efficiency of operations and the maintenance of a balanced tree structure. Unlike AVL trees, red-black trees use a color coding scheme to balance the tree, making it a more efficient alternative in certain scenarios.

In my previous article, we discussed the binary search tree and its implementation in C#. We learned that this data structure allows for fast searching, insertion, and deletion of elements in logarithmic time. Still, if the tree is not balanced properly, its performance can suffer greatly. We also noted that there is a more advanced tree called AVL with self-balancing, which guarantees logarithmic time complexity for all operations, regardless of the incoming data.

In this article, we will continue our exploration of binary search trees by diving deeper into AVL Trees. We will discuss their structure, properties, and implementation details and compare them to other self-balancing trees. We will also provide examples of AVL Trees in action and demonstrate how they solve the problem of unbalanced trees. By the end of this article, you will have a solid understanding of AVL Trees and be equipped with the knowledge to use them effectively in your own code.