Visualization and Comparative Simulation of Pathfinding, Searching and Sorting Algorithms

Abstract

This study addresses the need for enhanced algorithms learning through the utilization of comparative simulation and visualization. Motivated by the challenge of comprehending complex algorithms, we emphasize the efficacy of visualization tools. Our research explores the real-time rendering of algorithms in a visual format, facilitating a deeper understanding of their underlying mechanisms. In addition, we introduce a novel comparative simulation feature within our Algorithm Visualizer e-learning application, enabling learners to contrast the performance of diverse algorithms, discern their strengths and weaknesses, and evaluate their applicability to different data sets. Specifically, this application accommodates various algorithms, including Dijkstra's algorithm, DFS, BFS, Binary Search, and more. Learners can employ this tool to scrutinize algorithmic differences and efficiency, exemplified through scenarios like comparing Dijkstra's algorithm and A* algorithm for pathfinding on a map. Furthermore, this feature extends to the evaluation of sorting algorithms, such as Quick Sort and Merge Sort, allowing users to visualize their performance on large data sets. In conclusion, the Algorithm Visualizer e-learning application serves as a valuable resource for learners, enhancing algorithmic comprehension through comparative simulation and visualization techniques.