EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 140 (2017) MATEC Web Conf., 140 (2017) 01016 References
Open Access
Issue
MATEC Web Conf.
Volume 140, 2017
2017 International Conference on Emerging Electronic Solutions for IoT (ICEESI 2017)
Article Number 01016
Number of page(s) 6
DOI https://doi.org/10.1051/matecconf/201714001016
Published online 11 December 2017
  1. R. C. Bryce, Y. Lei, D. R. Kuhn, and R. N. Kacker, “Combinatorial Testing,” Handb. Res. Softw. Eng. Product. Technol. Implic. Glob.,196–208 (2010). [CrossRef] [Google Scholar]
  2. M. I. Younis, K. Z. Zamli, and R. R. Othman, “Effectiveness of the Cumulative vs . Normal Mode of Operation for Combinatorial Testing,” in IEEE Symposium on Industrial Electronics and Applications (ISIEA 2010), 350–354 (2010). [CrossRef] [Google Scholar]
  3. R. Kuhn, R. Kacker, Y. Lei, and J. Hunter, “Combinatorial Software Testing,” Computers, 42, 8, 94–96, (2009). [CrossRef] [Google Scholar]
  4. C. Nie and H. Leung, “A survey of combinatorial testing,” ACM Comput. Surv., 43, 2, 1–29 (2011). [CrossRef] [Google Scholar]
  5. X. Chen, Q. Gu, A. Li, and D. Chen, “Variable strength interaction testing with an ant colony system approach,” in Asia-Pacific Softw. Eng. Conf. APSEC, 160–167 (2009). [Google Scholar]
  6. M. Rahman, R. R. Othman, R. B. Ahmad, and M. Rahman, “Event Driven Input Sequence T-way Test Strategy Using Simulated Annealing,” in Fifth Int. Conf. on Intelligent Systems, Modelling and Simulation, 663–667 (2014). [Google Scholar]
  7. D. M. Cohen, S. R. Dalal, M. L. Fredman, and G. C. Patton, “The AETG system: an approach to testing based on combinatorial design,” IEEE Trans. Softw. Eng., 23,7, 437–444 (1997). [CrossRef] [Google Scholar]
  8. Y. Lei, R. Kacker, D. R. Kuhn, V. Okun, and J. Lawrence, “IPOG: A general strategy for T-way software testing,” in Proceedings of the Int. Symp and Workshop on Eng. of Comp. Based Systems, 549–556 (2007). [Google Scholar]
  9. L. Y. Xiang, A. A. Alsewari, and K. Z. Zamli, “Pairwise Test Suite Generator Tool Based On Harmony Search Algorithm (HS-PTSGT),” NNGT Int. J. Artif. Intell.,2, 62–65 (2015). [Google Scholar]
  10. H. Wu, C. Nie, F. Kuo, H. Leung, and C. J. Colbourn, “A Discrete Particle Swarm Optimization for Covering Array Generation,” IEEE Trans. Evol. Comput.,19,4,575–591, (2015). [CrossRef] [Google Scholar]
  11. J. Torres-jimenez, C. V. Tamps, and C. V. Tamps, “Survey of Covering Arrays,” in 15th Int. Symp. on Symbolic and Numeric Algorithms for Scientific Computing, 20–27 (2013). [Google Scholar]
  12. M. Rahman, R. R. Othman, R. B. Ahmad, and M. Rahman, “A Meta Heuristic Search based T-way Event Driven Input Sequence Test Case Generator,” Int. J. Simul. Syst. Sci. Technol., 15, 3, 65–71(2014). [Google Scholar]
  13. R. Kuhn, Y. Lei, and R. Kacker, “Practical Combinatorial Testing : Beyond Pairwise,” IEEE IT Professional,10, 3,19–23 (2008). [CrossRef] [Google Scholar]
  14. 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,” Inf. Softw. Technol., 54, 6, 553–568 (2012). [CrossRef] [Google Scholar]
  15. M. B. Cohen, P. B. Gibbons, W. B. Mugridge, C. J. Colbourn, and J. S. Collofello, “A variable strength interaction testing of components,” in 27th Annual Int. Comp. Software and Applications Conf. (2003). [Google Scholar]
  16. P. J. Schroeder and B. Korel, “Black-box test reduction using input-output analysis,” ACM SIGSOFT Softw. Eng. Notes, 25, 5,173–177, (2000). [CrossRef] [Google Scholar]
  17. R. R. Othman and K. Z. Zamli, “ITTDG : Integrated T-way test data generation strategy for interaction testing,” Sci. Res. Essays, 6,17, 3638–3648 (2011). [CrossRef] [Google Scholar]
  18. R. Othman and K. Zamli, “T-Way Strategies and Its Applications for Combinatorial Testing,” Int. J. New Comput. Archit. Their Appl., 1,2,459–473 (2011). [Google Scholar]
  19. X. Chen, Q. Gu, J. Qi, and D. Chen, “Applying particle swarm optimization to pairwise testing,” in IEEE 34th Annual Computer Software and Applications Conference, 107–116 (2010). [CrossRef] [Google Scholar]
  20. B. S. Ahmed and K. Z. Zamli, “PSTG : A T-Way Strategy Adopting Particle Swarm Optimization,” in 2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation, 1–5 (2010). [Google Scholar]
  21. B. S. Ahmed and K. Z. Zamli, “A variable strength interaction test suites generation strategy using Particle Swarm Optimization,” J. Syst. Softw., vol. 84, pp. 2171–2185, 2011. [CrossRef] [Google Scholar]
  22. K. Rabbi, Q. Mamun, and R. Islam, “An Efficient Particle Swarm Intelligence Based Strategy to Generate Optimum Test Data in T-way Testing,” in IEEE 10th Conf. on Industrial Electronics and App. (ICIEA), 123–128 (2015). [Google Scholar]
  23. K. Z. Zamli, M. F. J. Klaib, M. I. Younis, N. Ashidi, M. Isa, and R. Abdullah, “Design and implementation of a t-way test data generation strategy with automated execution tool support,” Inf. Sci. (Ny)., 181,9, 1741–1758 (2011). [CrossRef] [Google Scholar]
  24. H. Y. Ong and K. Z. Zamli, “Development of interaction test suite generation strategy with input-output mapping supports,” Sci. Res. Essays, 6,16, 3418–3430 (2011). [CrossRef] [Google Scholar]
  25. Z. Wang and H. He, “Generating Variable Strength Covering Array for Combinatorial Software Testing with Greedy Strategy,” J. Softw.,8, 12, 3173–3181 (2013). [Google Scholar]
  26. R. R. Othman, N. Khamis, and K. Z. Zamli, “Variable Strength t-way Test Suite Generator with Constraints Support,” Malaysian J. Comput. Sci.,27, 3, 204–217 (2014). [Google Scholar]
  27. J. Lin, C. Luo, S. Cai, K. Su, D. Hao, and L. Zhang, “TCA : An Efficient Two-Mode Meta-Heuristic Algorithm for Combinatorial Test Generation,” in 30th IEEE/ACM International Conference on Automated Software Engineering 494–505 (2015). [Google Scholar]
  28. 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,” Inf. Softw. Technol., 66,13–29 (2015). [CrossRef] [Google Scholar]
  29. X. S. Yang and S. Deb, “Cuckoo search via Levy flights,” in World Congress on Nature and Biologically Inspired Computing,210–214 (2009). [Google Scholar]
  30. A. B. Nasser, Y. A. Sariera, A. A. Alsewari, and K. Z. Zamli, “Assessing Optimization Based Strategies for t-way Test Suite Generation : The Case for Flower-based Strategy,” in IEEE Int. Conf. on Control System, Computing and Eng, 150–155 (2015). [Google Scholar]
  31. K. Z. Zamli, B. Y. Alkazemi, and G. Kendall, “A Tabu Search hyper-heuristic strategy for t-way test suite generation,” Appl. Soft Comput. J.,44, 57–74 (2016). [CrossRef] [Google Scholar]
  32. M. Shaiful, A. Rashid, R. R. Othman, Z. R. Yahya, M. Zamri, and Z. Ahmad, “Implementation of Artificial Bee Colony Algorithm for T-way Testing,” in 3rd Int. Conf. on Electronic Design (ICED), 591–594 (2016). [Google Scholar]
  33. N. Ramli, R. R. Othman, M. Shaiful, and A. Rashid, “Optimizing Combinatorial Input-Output Based Relations Testing using Ant Colony Algorithm,” in 3rd Int. Conf. on Electronic Design (ICED), 586–590 (2016) [Google Scholar]
  34. T. Shiba, T. Tsuchiya, and T. Kikuno, “Using artificial life techniques to generate test cases for combinatorial testing,” in Proceedings of the 28th Annual Int. Comp. Soft. and App. Conf, (2004). [Google Scholar]
  35. K. Z. Zamli, F. Din, S. Baharom, and B. S. Ahmed, “Engineering Applications of Arti fi cial Intelligence 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 (2017). [CrossRef] [Google Scholar]
  36. M. Harman, Y. Jia, J. Krinke, W. B. Langdon, J. Petke, and Y. Zhang, “Search based software engineering for software product line engineering : a survey and directions for future work,” in 15th Soft. Product Line Conference, 5–18 (2014) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.