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DOI: 10.14569/IJACSA.2017.080401
PDF

Teaching Software Testing using Data Structures

Author 1: Ingrid A. Buckley
Author 2: Winston S. Buckley

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 4, 2017.

  • Abstract and Keywords
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Abstract: Software testing is typically a rushed and neglected activity that is done at the final stages of software development. In particular, most students tend to test their programs manually and very seldom perform adequate testing. In this paper, two basic data structures are utilized to highlight the importance of writing effective test cases by testing their fundamental properties. The paper also includes performance testing at the unit level, of a classic recursive problem called the Towers of Hanoi. This teaching approach accomplishes two important pedagogical objectives: (1) it allows students to think about how to find hidden bugs and defects in their programs and (2) it encourages them to test more effectively by leveraging data structures that are already familiar to them.

Keywords: Software Testing; Data Structures; Abstract Data Type (ADT); Unit Testing; Performance Testing; Stacks; Binary Search Tree; Towers of Hanoi

Ingrid A. Buckley and Winston S. Buckley, “Teaching Software Testing using Data Structures” International Journal of Advanced Computer Science and Applications(IJACSA), 8(4), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080401

@article{Buckley2017,
title = {Teaching Software Testing using Data Structures},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080401},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080401},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {4},
author = {Ingrid A. Buckley and Winston S. Buckley}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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