Hybrid Data Structures: Analyzing Novel Implementations for Enhanced Computational Efficiency

Title: Hybrid Data Structures: Analyzing Novel Implementations for Enhanced Computational Efficiency Authors: Sagnik Sen, Maulana Abul Kalam Azad University of Technology Abstract:This research explores novel data structure implementations, including Red-Black Trees with Circular Linked Lists, Decision Trees with LIFO Nodes, and N-ary Trees with Hash Maps. The study provides theoretical and experimental analysis, including time complexity calculations and performance benchmarks. The paper also proposes an optimized linked list structure with lower theoretical complexity than binary search trees and a stack-based implementation using binary search trees. These hybrid structures are analyzed in terms of computational efficiency, storage trade-offs, and real-world applications. Keywords: Data Structures, Algorithm Optimization, Computational Complexity, Hybrid Trees, Machine Learning, Hash Maps, Linked Lists. License: Creative Commons Attribution 4.0 (CC BY 4.0)