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Advances in Electronics Engineering pp 137–145Cite as

Pairwise Test Suite Generation Based on Hybrid Artificial Bee Colony Algorithm

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 619))

Abstract

Software plays an important part of our daily life in order to aid and facilitate our routine tasks, especially a household one. However, the failure of software is a major threat to our lives, particularly the critical applications that employed daily. Due to the large number of inputs as well as time consumption for a test and cost, it is becoming hard to get exhaustive testing for any software in order to fault detection. For this reason, Combinatorial Testing Technique (CTT) is one of the famous techniques that have been used in fault detection of the software systems. Pairwise testing is one of the efficient CTT that used widely for fault detection based on the caused failures by two interactions parameters. There are many researchers that have been developed a pairwise testing strategy. Complementing to the earlier researches, this paper proposes a new pairwise test suite generation called Pairwise Hybrid Artificial Bee Colony (PhABC) strategy based on hybridize of an Artificial Bee Colony (ABC) algorithm with a Particle Swarm Optimization (PSO) algorithm. Empirical results shows that PhABC strategy outperforms other strategies in some cases and provides competitive results in other cases by generating the final test suite.

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References

  1. Yilmaz C, Fouche S, Cohen MB, Porter A, Demiroz G, Koc U (2014) Moving forward with combinatorial interaction testing. Computer 47:37–45

    Article  Google Scholar 

  2. Hervieu A, Marijan D, Gotlieb A, Baudry B (2016) Practical minimization of pairwise-covering test configurations using constraint programming. Inf Softw Technol 71:129–146

    Article  Google Scholar 

  3. Kuhn DR, Bryce R, Duan F, Ghandehari LS, Lei Y, Kacker RN (2015) Combinatorial testing: theory and practice. Adv Comput 99:1–66

    Google Scholar 

  4. Nasser AB, Sariera YA, Alsewari ARA, Zamli KZ (2015) A cuckoo search based pairwise strategy for combinatorial testing problem. J Theor Appl Inf Technol 82:154

    Google Scholar 

  5. Kuhn DR, Reilly MJ (2002) An investigation of the applicability of design of experiments to software testing. In: Proceedings of 27th annual NASA goddard/IEEE software engineering workshop. IEEE, pp 91–95

    Google Scholar 

  6. Kuhn DR, Wallace DR, Gallo AM (2004) Software fault interactions and implications for software testing. IEEE Trans Software Eng 30:418–421

    Article  Google Scholar 

  7. Colbourn CJ, Cohen MB, Turban R (2004) A deterministic density algorithm for pairwise interaction coverage. In: IASTED conference on software engineering, pp 345–352

    Google Scholar 

  8. Khalsa SK, Labiche Y (2004) An orchestrated survey of available algorithms and tools for combinatorial testing. In: 2014 IEEE 25th international symposium on software reliability engineering (ISSRE). IEEE, pp 323–334

    Google Scholar 

  9. Al-Sewari AA, Zamli KZ (2014) An orchestrated survey on t-way test case generation strategies based on optimization algorithms. In: The 8th international conference on robotic, vision, signal processing & power applications. Springer, pp 255–263

    Google Scholar 

  10. Nie C, Leung H (2011) A survey of combinatorial testing. ACM Comput Surv (CSUR) 43:11

    Article  Google Scholar 

  11. Alsariera YA, Alamri HS, Zamli KZ (2017) A bat-inspired testing strategy for generating constraints pairwise test suite. In: The 5th international conference on software engineering & computer systems (ICSECS), vol. 5

    Google Scholar 

  12. Alsariera YA, Nasser A, Zamli KZ (2016) Benchmarking of Bat-inspired interaction testing strategy. Int J Comput Sci Inf Eng (IJCSIE) 7:71–79

    Google Scholar 

  13. Alsariera YA, Zamli KZ (2015) A bat-inspired strategy for t-way interaction testing. Adv Sci Lett 21:2281–2284

    Article  Google Scholar 

  14. Alsariera YA, Majid MA, Zamli KZ (2015) Adopting the bat-inspired algorithm for interaction testing. In: The 8th edition of annual conference for software testing, pp 14

    Google Scholar 

  15. Alsariera YA, Majid MA, Zamli KZ (2015) A bat-inspired strategy for pairwise testing. ARPN J Eng Appl Sci 10:8500–8506

    Google Scholar 

  16. Flores P, Cheon Y (2011) PWiseGen: Generating test cases for pairwise testing using genetic algorithms. In: 2011 IEEE International Conference on Computer Science and Automation Engineering (CSAE). IEEE, pp 747–752

    Google Scholar 

  17. Shiba T, Tsuchiya T, Kikuno T (2004) Using artificial life techniques to generate test cases for combinatorial testing. In: Proceedings of the 28th annual international computer software and applications conference, 2004. COMPSAC 2004. IEEE, pp 72–77

    Google Scholar 

  18. Alsewari ARA, Zamli KZ (2012) Design and implementation of a harmony-search-based variable-strength t-way testing strategy with constraints support. Inf Softw Technol 54:553–568

    Article  Google Scholar 

  19. Cohen MB, Gibbons PB, Mugridge WB, Colbourn CJ, Collofello JS (2003) A variable strength interaction testing of components. In: Proceedings of 27th annual international computer software and applications conference. COMPSAC 2003. IEEE, pp 413–418

    Google Scholar 

  20. Ahmed BS, Abdulsamad TS, Potrus MY (2015) Achievement of minimized combinatorial test suite for configuration-aware software functional testing using the Cuckoo Search algorithm. Inf Softw Technol 66:13–29

    Article  Google Scholar 

  21. Rabbi K, Mamun Q, Islam MR (2015) An efficient particle swarm intelligence based strategy to generate optimum test data in t-way testing. In: 2015 IEEE 10th conference on industrial electronics and applications (ICIEA). IEEE, pp. 123–128

    Google Scholar 

  22. Alazzawi AK, Rais HM, Basri S (2018) Artificial bee colony algorithm for t-way test suite generation. In: 2018 4th international conference on computer and information sciences (ICCOINS). IEEE, pp. 1–6

    Google Scholar 

  23. Alsewari AA, Alazzawi AK, Rassem TH, Kabir MN, Homaid AAB, Alsariera YA, Tairan NM, Zamli KZ (2017) ABC algorithm for combinatorial testing problem. J Telecommun, Electron Comput Eng (JTEC) 9:85–88

    Google Scholar 

  24. Alazzawi AK, Homaid AAB, Alomoush AA, Alsewari AA (2017) Artificial bee colony algorithm for pairwise test generation. J Telecommun, Electron Comput Eng (JTEC) 9:103–108

    Google Scholar 

  25. Homaid AAB, Alsewari AA, Alazzawi AK, Zamli KZ (2018) A kidney algorithm for pairwise test suite generation. Adv Sci Lett 24:7284–7289

    Article  Google Scholar 

  26. Nasser AB, Alsewari AA, Tairan NM, Zamli KZ (2017) Pairwise test data generation based on flower pollination algorithm. Malays J Comput Sci 30:242–257

    Article  Google Scholar 

  27. Zamli KZ, Din F, Baharom S, Ahmed BS (2017) Fuzzy adaptive teaching learning-based optimization strategy for the problem of generating mixed strength t-way test suites. Eng Appl Artif Intell 59:35–50

    Article  Google Scholar 

  28. Karaboga D (2005) An idea based on honey bee swarm for numerical optimization. Technical report-tr06, Erciyes University, engineering Faculty, Computer Engineering Department

    Google Scholar 

  29. Karaboga D, Akay B (2009) A survey: algorithms simulating bee swarm intelligence. Artif Intell Rev 31:61–85

    Article  Google Scholar 

  30. Kıran MS, Gündüz M (2012) A novel artificial bee colony-based algorithm for solving the numerical optimization problems. Int J Innov Comput Inf Control 8:6107–6121

    Google Scholar 

  31. Yan X, Zhu Y, Zou W (2011) A hybrid artificial bee colony algorithm for numerical function optimization. In: 11th international conference on hybrid Intelligent Systems (HIS), 2011. IEEE, pp 127–132

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, 32610, Bandar Seri Iskandar, Perak, Malaysia

    Ammar K. Alazzawi, Helmi Md Rais & Shuib Basri

  2. Department of Computer Sciences, Northern Border University, Arar, 73222, Saudi Arabia

    Yazan A. Alsariera

Authors
  1. Ammar K. Alazzawi
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  2. Helmi Md Rais
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  3. Shuib Basri
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  4. Yazan A. Alsariera
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Corresponding author

Correspondence to Ammar K. Alazzawi .

Editor information

Editors and Affiliations

  1. Melaka, Malaysia

    Zahriladha Zakaria

  2. Melaka, Malaysia

    Rabiah Ahmad

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© 2020 Springer Nature Singapore Pte Ltd.

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Cite this paper

Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A. (2020). Pairwise Test Suite Generation Based on Hybrid Artificial Bee Colony Algorithm. In: Zakaria, Z., Ahmad, R. (eds) Advances in Electronics Engineering. Lecture Notes in Electrical Engineering, vol 619. Springer, Singapore. https://doi.org/10.1007/978-981-15-1289-6_13

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  • DOI: https://doi.org/10.1007/978-981-15-1289-6_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1288-9

  • Online ISBN: 978-981-15-1289-6

  • eBook Packages: EngineeringEngineering (R0)

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