Article

T-way Test Suite Generation Based on Hybrid Flower Pollination Algorithm and Hill Climbing

Authors:

Abdullah B. Nasser,

Kamal Z. Zamli,

Nor Wardah Binti Mohd Nasir,

Waheed Ali H.M. Ghanem,

Fakhrud DinAuthors Info & Claims

ICSCA '21: Proceedings of the 2021 10th International Conference on Software and Computer Applications

Pages 244 - 250

https://doi.org/10.1145/3457784.3457822

Published: 30 July 2021 Publication History

Abstract

One of the common application of search-based software testing (SBST) is generating test cases for all objectives characterized by a scope model (e.g. articulations, mutants, branches). The application of meta-heuristic algorithms in t-way tests generation, as an example of SBST, has as of late gotten to be predominant. Thus, numerous valuable meta-heuristic algorithms have been created on the premise of the usage of t-way techniques (where t shows the interaction quality). T-way testing technique is a sampling technique to produce an optimum test suite in a systematic manner. In other words, is to generate a smaller test suite size that can be used for testing the software in less time and coast. Here, all t-way techniques generate the test suite with the aim to cover every possible combination produced by the interacting inputs or parameters. All possible t-combinations of the system's components must be covered at least once. Besides, the purpose of the t-way testing technique is to overcome exhaustive testing. Studies reported that there is no single strategy that appears to be superior in all configurations considered. In this research paper, we propose a new software t-way testing tool based on hybrid Flower Pollination Algorithm and Hill Climbing for generating test suite generation, called FPA-HC strategy can be used for generating smaller test suite size. The FPA-HC evaluated against the existing t-way strategies including the original FPA. Experimental results have shown promising results as FPA-HC can produce very competitive results comparing with existing t-way strategies.

References

[1]

W. E. Lewis, Software testing and continuous quality improvement: CRC press, 2016.

[2]

R. Brownlie, J. Prowse, and M. S. Phadke, “Robust Testing of AT&T PMX/StarMAIL Using OATS,” AT&T Technical Journal, vol. 71, no. 3, pp. 41-47, 1992.

[3]

M. Harman, Y. Jia, and Y. Zhang, "Achievements, open problems and challenges for search based software testing." pp. 1-12.

[4]

A. B. Nasser, K. Z. Zamli, A. A. Alsewari, and B. S. Ahmed, “Hybrid flower pollination algorithm strategies for t-way test suite generation,” PloS one, vol. 13, no. 5, pp. e0195187, 2018.

[5]

D. R. Kuhn, R. N. Kacker, and Y. Lei, “Practical combinatorial testing,” National Institute of Standards and Technology (NIST) Special Publication, vol. 800, pp. 142, 2010.

[6]

K. Z. Zamli, B. Y. Alkazemi, and G. Kendall, “A tabu search hyper-heuristic strategy for t-way test suite generation,” Applied Soft Computing, vol. 44, pp. 57-74, 2016.

Digital Library

[7]

Y. A. Alsariera, H. A. S. Ahmed, H. S. Alamri, M. A. Majid, and K. Z. Zamli, “A Bat-Inspired Testing Strategy for Generating Constraints Pairwise Test Suite,” Advanced Science Letters, vol. 24, no. 10, pp. 7245-7250, 2018.

[8]

B. S. Ahmed, T. S. Abdulsamad, and M. Y. Potrus, “Achievement of minimized combinatorial test suite for configuration-aware software functional testing using the cuckoo search algorithm,” Information and Software Technology, vol. 66, no. C, pp. 13-29, Oct, 2015.

Digital Library

[9]

A. R. A. Alsewari, and K. Z. Zamli, “A Harmony search based pairwise sampling strategy for combinatorial testing,” International Journal of Physical Sciences, vol. 7, no. 7, pp. 1062-1072, 2012.

[10]

B. S. Ahmed, and K. Z. Zamli, “A review of covering arrays and their application to software testing,” Journal of Computer Science, vol. 7, no. 9, pp. 1375-1385, 2011.

[11]

B. Jenkins. "Jenny tool," 5-Dec-2017; http://www.burtleburtle.net/bob/math.

[12]

J. Stardom, Metaheuristics and the search for covering and packing arrays, Canada: Simon Fraser University, 2001.

[13]

T. Shiba, T. Tsuchiya, and T. Kikuno, "Using artificial life techniques to generate test cases for combinatorial testing." pp. 72-77.

[14]

B. S. Ahmed, K. Z. Zamli, and C. P. Lim, “Application of particle swarm optimization to uniform and variable strength covering array construction,” Applied Soft Computing, vol. 12, no. 4, pp. 1330-1347, 2012.

Digital Library

[15]

A. R. A. Alsewari, and K. Z. Zamli, “Design and implementation of a harmony-search-based variable-strength t-way testing strategy with constraints support,” Information and Software Technology, vol. 54, no. 6, pp. 553-568, Jun, 2012.

Digital Library

[16]

A. B. Nasser, A. A. Alsewari, N. M. Tairan, and K. Z. Zamli, “Pairwise Test Data Generation Based On Flower Pollination Algorithm,” Malaysian Journal of Computer Science, vol. 30, no. 3, pp. 242-257, 2017.

[17]

A. B. Nasser, and K. Z. Zamli, "A New Variable Strength t-way Strategy based on the Cuckoo Search Algorithm."

[18]

A. B. Nasser, A. Alsewari, and K. Z. Zamli, "Learning cuckoo search strategy for t-way test generation." pp. 97-110.

[19]

A. A. Alomoush, A. A. Alsewari, H. S. Alamri, K. Aloufi, and K. Z. Zamli, “Hybrid harmony search algorithm with grey wolf optimizer and modified opposition-based learning,” IEEE Access, vol. 7, pp. 68764-68785, 2019.

[20]

A. K. Alazzawi, H. M. Rais, and S. Basri, “Parameters tuning of hybrid artificial bee colony search based strategy for t-way testing,” Int. J. Innov. Technol. Exploring Eng., vol. 8, no. 5S, pp. 204-212, 2019.

[21]

K. Z. Zamli, “An Improved Jaya Algorithm-Based Strategy for T-Way Test Suite Generation,” Emerging Trends in Intelligent Computing and Informatics: Data Science, Intelligent Information Systems and Smart Computing, vol. 1073, pp. 352, 2019.

[22]

B. Selman, and C. P. Gomes, “Hill‐climbing Search,” Encyclopedia of Cognitive Science.

Cited By

Muazu AHashim AAudi UMaiwada U(2024)Refining a One-Parameter-at-a-Time Approach Using Harmony Search for Optimizing Test Suite Size in Combinatorial T-Way TestingIEEE Access10.1109/ACCESS.2024.346395312(137373-137398)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3463953
Mohammed Fadhil HNajm Abdullah MIssam Younis M(2024)Dynamic TWGH: Client-Server Optimization for Scalable Combinatorial Test Suite GenerationBIO Web of Conferences10.1051/bioconf/2024970011597(00115)Online publication date: 5-Apr-2024
https://doi.org/10.1051/bioconf/20249700115
Muazu AHashim ASarlan AMaiwada U(2022)Proposed Method of Seeding and Constraint in One-Parameter-At-a- Time Approach for t-way Testing2022 International Conference on Digital Transformation and Intelligence (ICDI)10.1109/ICDI57181.2022.10007210(39-45)Online publication date: 1-Dec-2022
https://doi.org/10.1109/ICDI57181.2022.10007210
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ICSCA '21: Proceedings of the 2021 10th International Conference on Software and Computer Applications

February 2021

325 pages

ISBN:9781450388825

DOI:10.1145/3457784

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 30 July 2021

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Ministry of Higher education (MOHE) - Malaysia

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ICSCA 2021

ICSCA 2021: 2021 10th International Conference on Software and Computer Applications

February 23 - 26, 2021

Kuala Lumpur, Malaysia

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Cited By

Muazu AHashim AAudi UMaiwada U(2024)Refining a One-Parameter-at-a-Time Approach Using Harmony Search for Optimizing Test Suite Size in Combinatorial T-Way TestingIEEE Access10.1109/ACCESS.2024.346395312(137373-137398)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3463953
Mohammed Fadhil HNajm Abdullah MIssam Younis M(2024)Dynamic TWGH: Client-Server Optimization for Scalable Combinatorial Test Suite GenerationBIO Web of Conferences10.1051/bioconf/2024970011597(00115)Online publication date: 5-Apr-2024
https://doi.org/10.1051/bioconf/20249700115
Muazu AHashim ASarlan AMaiwada U(2022)Proposed Method of Seeding and Constraint in One-Parameter-At-a- Time Approach for t-way Testing2022 International Conference on Digital Transformation and Intelligence (ICDI)10.1109/ICDI57181.2022.10007210(39-45)Online publication date: 1-Dec-2022
https://doi.org/10.1109/ICDI57181.2022.10007210
Muazu AHashim ASarlan A(2022)Review of Nature Inspired Metaheuristic Algorithm Selection for Combinatorial t-Way TestingIEEE Access10.1109/ACCESS.2022.315740010(27404-27431)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3157400

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