Efficiency Through the Balance of Trees

This week’s material focused on data structures like AVL trees, heaps, and hash tables. It reinforced my understanding of self-balancing binary search trees and their properties. I learned how an AVL tree maintains balance by ensuring the height difference between left and right subtrees never exceeds one. The material introduced 2-3 trees and heaps and helped me visualize how structural properties influence data organization and retrieval speed. 

In the lab, I implemented heap operations such as building a max heap, inserting new elements, deleting the maximum value, and verifying if a given array satisfies the heap property. The assignment showed how a binary heap can efficiently support priority-based operations. In another part of the lab, I developed a hash table using linear probing with rehashing. It showed how functions can distribute data across an array and how collisions are resolved through probing.