[1] Ahmed, B.S. Test case minimization approach using fault detection and combinatorial optimization techniques for configuration-aware structural testing, Eng. Sci. Technol. an Int. J. 19(2) (2016), 737–753.
[2] Akour, M., Abuwardih, L., Alhindawi, N. and Alshboul, A. Test case minimization using genetic algorithm: pilot study, In: 2018 8th Inter-national Conference on Computer Science and Information Technology (CSIT), 66 –70. IEEE (2018).
[3] Al-Betar, M.A., Alyasseri, Z.A.A., Awadallah, M.A. and Abu Doush, I. Coronavirus herd immunity optimizer (chio), Neural Comput. Appl. 33 (2021), 5011–5042.
[4] Arasteh, B., Gharehchopogh, F.S., Gunes, P., Kiani, F. and Torka-manian Afshar, M. A novel metaheuristic based method for software mutation test using the discretized and modified forrest optimization al-gorithm, J. Electron. Test. (2023), 1–24.
[5] Ayyarao, T.S., Ramakrishna, N., Elavarasan, R.M., Polumahanthi, N., Rambabu, M., Saini, G., Khan, B. and Alatas, B. War strategy opti-mization algorithm: a new effective metaheuristic algorithm for global optimization, IEEE Access 10, (2022), 25073–25105.
[6] Bajaj, A. and Sangwan, O.P. Discrete and combinatorial gravitational search algorithms for test case prioritization and minimization, Int. J. Inf. Technol. 13 (2021), 817–823.
[7] Bajaj, A., Sangwan, O.P. and Abraham, A. Improved novel bat algo-rithm for test case prioritization and minimization, Soft Comput. 26(22) (2022), 12393–12419.
[8] Bajaj, A., Abraham, A., Ratnoo, S. and Gabralla, L.A. Test case pri-oritization, selection, and reduction using improved quantum-behaved particle swarm optimization, Sensors 22(12) (2022), 4374.
[9] Bharathi, M. Hybrid particle swarm and ranked firefly metaheuristic optimization-based software test case minimization, Int. J. Appl. Meta-heuristic Comput. (IJAMC) 13(1) (2022), 1–20.
[10] Bhatia, P.K. Test case minimization in cots methodology using genetic al-gorithm: a modified approach, In: Proceedings of ICETIT 2019: Emerg-ing Trends in Information Technology, 219 –228. Springer, 2020.
[11] Bian, Y., Li, Z., Zhao, R. and Gong, D. Epistasis based aco for regression test case prioritization, IEEE Trans. Emerg. Top. Comput. Intell. 1(3) (2017), 213–223.
[12] Boukhlif, M., Hanine, M. and Kharmoum, N. A decade of intelligent soft-ware testing research: A bibliometric analysis, Electronics 12(9) (2023), 2109.
[13] Dehghani, M. and Trojovsk‘y, P. Teamwork optimization algorithm: A new optimization approach for function minimization/maximization, Sensors 21(13) (2021), 4567.
[14] Deneke, A., Assefa, B.G. and Mohapatra, S.K. Test suite minimization using particle swarm optimization, Mater. Today: Proc. 60 (2022), 229–233.
[15] Geetha, U. and Sankar, S. Multi-objective modified particle swarm op-timization for test suite reduction (mompso), Comput. Syst. Sci. Eng. 42(3) (2022), 899–917.
[16] Guizzo, G., Califano, F., Sarro, F., Ferrucci, F. and Harman, M. In-ferring test models from user bug reports using multi-objective search, Empir. Softw. Eng. 28(4) (2023), 95.
[17] Habib, A.S., Khan, S.U.R. and Felix, E.A. A systematic review on searchbased test suite reduction: State-of-the-art, taxonomy, and future directions, IET Software 17(2) (2023), 93–136.
[18] Hashim, N.L. and Dawood, Y.S. Test case minimization applying firefly algorithm, Int. J. Adv. Sci. Eng. Inf. Technol. 8(4-2) (2018), 1777–1783.
[19] Joseph, A. and Radhamani, G. Hybrid test case optimization approach using genetic algorithm with adaptive neuro fuzzy inference system for regression testing, J. Test. Eval. 45(6) (2017), 2283–2293.
[20] Khatibsyarbini, M., Isa, M.A. and Abang Jawawu, D.N. A hybrid weight-based and string distances using particle swarm optimization for priori-tizing test cases, J. Theor. Appl. Inf. Technol. 95(12) (2017).
[21] Khoshniat, N., Jamarani, A., Ahmadzadeh, A., Haghi Kashani, M. and Mahdipour, E. Nature-inspired metaheuristic methods in software test-ing, Soft Comput. (2023), 1–42.
[22] Kocher, D.C. Radioactive decay data tables, Tech. rep., Oak Ridge Na-tional Lab., TN (USA), 1981.
[23] Mohamed, A.W., Hadi, A.A. and Mohamed, A.K. Gaining-sharing knowledge based algorithm for solving optimization problems: a novel na-tureinspired algorithm, Int. J. Mach. Learn. Cybern. 11(7)(2020), 1501–1529.
[24] Mohanty, S., Mohapatra, S.K. and Meko, S.F. Ant colony optimization (aco-min) algorithm for test suite minimization, In: Progress in Com-puting, Analytics and Networking: Proceedings of ICCAN 2019, 55 –63. Springer, 2020.
[25] Nayak, G. and Ray, M. Modified condition decision coverage criteria for test suite prioritization using particle swarm optimization, Int. J. Intell. Comput. Cybern. 12(4) (2019), 425–443.
[26] Pachariya, M.K. Building ant system for multi-faceted test case prior-itization: An empirical study, Int. J. Softw. Innov. (IJSI) 8(2)(2020), 23–37.
[27] Pan, R., Ghaleb, T.A. and Briand, L. Atm: Black-box test case min-imization based on test code similarity and evolutionary search, 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE). IEEE, 2023.
[28] Sahin, O. and Akay, B. Comparisons of metaheuristic algorithms and fitness functions on software test data generation, Appl. Soft Comput. 49 (2016), 1202–1214.
[29] Sahoo, R.R. and Ray, M. Pso based test case generation for critical path using improved combined fitness function, J. King Saud Univ. - Comput. Inf. Sci. 32(4) (2020), 479–490.
[30] Sheikh, R., Babar, M.I., Butt, R., Abdelmaboud, A. and Eisa, T.A.E. An optimized test case minimization technique using genetic algorithm for regression testing, Comput. Mater. Contin. 74(3) (2023), 6789–6806.
[31] Sun, J., Chen, J. and Wang, G. Multi-objective test case prioritization based on epistatic particle swarm optimization, Int. J. Performability Eng. 14(10) (2018), 2441.
[32] Suri, B. and Singhal, S. Analyzing test case selection & prioritization using ACO, ACM SIGSOFT Software Engineering Notes 36(6) (2011), 1–5.
[33] Tyagi, M. and Malhotra, S. Test case prioritization using multi objective particle swarm optimizer, In: 2014 International Conference on Signal Propagation and Computer Technology (ICSPCT 2014), 390–395. IEEE, 2014.
[34] Verma, A.S., Choudhary, A. and Tiwari, S. Regression test case selection: A comparative analysis of metaheuristic algorithms, In: Proceedings of Second Doctoral Symposium on Computational Intelligence: DoSCI 2021, 605–615. Springer, 2022.
Send comment about this article