Project: Binary Tree Demonstration using OpenGL Synopsis: This project focuses on the visual demonstration of binary trees, particularly those used in decision-making processes. Binary trees are essential in many computer science applications, including search algorithms and decision-making structures. In machine learning, decision trees are used to create binary splits of data, helping to distill complex datasets into understandable rules. This visualization tool allows users to observe the structure of a binary tree, understand its balance, and see how subtrees can be manipulated.

Objectives:

• Binary Tree Creation and Visualization: Construct and visually demonstrate binary trees, highlighting their structure and characteristics.
• Tree Balancing Demonstration: Show the effects of tree balancing, optimizing both the tree’s structure and search performance.
• Tree Mask and Map Matrices: Illustrate the internal structure of the tree using matrix representations.
• Node Deletion and Subtree Insertion: Demonstrate dynamic operations such as deleting nodes and reinserting subtrees.

Technologies Used:

• Languages: C, C++ (Data Structures & Algorithms)
• API: OpenGL for graphical rendering
• IDE: Microsoft Visual Studio

Usage Instructions: The entry point for the tree demonstration is bsTree.cpp. Within this file, use the populateTree() function to create and populate your BinarySearchTree class. After building your tree, compile and run the application to visualize the structure. If you want to explore how balancing affects the tree, press 'v' to balance the tree and observe the changes in the visualization.