Project Abstract

This project investigates the optimization of Binary Search Trees (BSTs) to enhance the efficiency and scalability of computational algorithms and real-world applications. With the increasing demand for rapid data access and processing in various domains such as database management systems and information retrieval, optimizing BSTs is very important. The research aims to explore advanced balancing techniques and algorithmic optimizations to solve performance problems inherent in BST operations while testing whether optimized BSTs, such as AVL trees and Red-black trees, exhibit superior algorithmic operation performance compared to non-optimized BSTs when subjected to identical datasets. Employing a comprehensive literature review and experimental methodology, the study seeks to analyze and implement existing libraries. We anticipate that optimization techniques such as AVL trees and Red-black trees will demonstrate improved performance compared to non-optimized BSTs, particularly in scenarios involving large and dynamic datasets. We expect to observe significant differences in performance across varying ranges of dataset sizes and test cases, highlighting the importance of optimization techniques in addressing scalability challenges in BST data structure.

Keywords: Data Structures, Algorithms, Binary Search Trees

 Conference Details

Session: Presentation Stream 21 at Presentation Slot 7

Location: GH022 at Wednesday 8th 09:00 – 12:30

Markers: C�cilia Pradic, Joe Macinnes

Course: MSc Advanced Computer Science, Masters PG

Future Plans: I’m looking for an industry placement