Debugging Tool to Learn Algorithms: A Case Study Minimal Spanning Tree

Authors

  • Ahmed Y Khedr College of Computer Science and Engineering, Hail University, Hail, KSA. Faculty of Engineering, AlAzhar University, Cairo, Egypt
  • Hazem M. Bahig College of Computer Science and Engineering, Hail University, Hail, KSA. Faculty of Science, Ain Shams University, Cairo, Egypt.

DOI:

https://doi.org/10.3991/ijet.v12i04.6442

Keywords:

minimal spanning tree, education tool, debuging tool, Kruskal’s algorithm, Prim’s algorithm

Abstract


This paper presents a visualization tool that works as a debugger to learn the minimal spanning tree. The tool allows the user to enter the graph as a matrix and then allow the user to visualize the execution of the algorithm step by step. During the visualization, the tool can handle and debug the errors that occurred by the user. Also the tool gives the user a feedback from the execution of the algorithm by storing the errors that occurred by the user. The tool can be used by the teacher and students inside and outside the class. The tool was evaluated by the students and the results show that the tool enhances the understanding of algorithms.

Author Biography

Hazem M. Bahig, College of Computer Science and Engineering, Hail University, Hail, KSA. Faculty of Science, Ain Shams University, Cairo, Egypt.

Hazem Bahig received the B.Sc. degree in Pure Mathematics and Computer Science from Ain Shams University, Faculty of Science in 1990. He also received M.Sc. and Ph. D. degrees in Computer Science in 1997 and 2003 respectively from Computer Science Division, Ain Sham University, Cairo, Egypt. Also, he is currently worked in College of Computer Science and Engineering, Hail University, KSA. His current research interests include high performance computing, algorithm, bioinformatics and e-learning systems for algorithms.

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Published

2017-04-28

How to Cite

Khedr, A. Y., & Bahig, H. M. (2017). Debugging Tool to Learn Algorithms: A Case Study Minimal Spanning Tree. International Journal of Emerging Technologies in Learning (iJET), 12(04), pp. 90–100. https://doi.org/10.3991/ijet.v12i04.6442

Issue

Vol. 12 No. 04 (2017)

Section

Papers