Abstract
Automatic test case generation is an optimization problem in software testing process. With the use of genetic algorithm we can generate the test cases automatically. Genetic algorithm alone does not give 100% accurate optimized test cases. Hence merging of genetic algorithm with Cuckoo search optimization technique produces better optimized test cases. The main aim of this paper is to customize the cost and time for the Testing process after the generation of test cases automatically. The two optimization techniques namely Cuckoo Search and genetic algorithm produce better result as compared to single one.
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References
Jorgensen, Paul C. Software Testing: a craftsman’s approach. CRC press, 2013.
Parthiban, M., and M. R. Sumalatha. “GASE-an input domain reduction and branch coverage system based on Genetic Algorithm and Symbolic Execution.” Information Communication and Embedded Systems (ICICES), 2013 International Conference on. IEEE, 2013.
Sivanandam, S. N., and S. N. Deepa. Introduction to Genetic Algorithms. Springer Science & Business Media, 2007.
Khan, Rijwan, and Mohd Amjad. “Automatic Generation of Test Cases for Data Flow Test Paths Using K-Means Clustering and Generic Algorithm.” International Journal of Applied Engineering Research 11.1 (2016): 473–478.
Mahajan, Manish, Sumit Kumar, and Rabins Porwal. “Applying Genetic Algorithm to increase the efficiency of a data flow-based test data generation approach.” ACM SIGSOFT Software Engineering Notes 37.5 (2012): 1–5.
Srivastava, Praveen Ranjan, and Tai-hoon Kim. “Application of Genetic Algorithm in Software Testing.” International Journal of Software Engineering and its Applications 3.4 (2009): 87–96.
Ghiduk, Ahmed S., and Moheb R. Girgis. “Using Genetic Algorithms and dominance concepts for generating reduced test data.” Informatica 34.3 (2010).
Yang, Xin-She, and Suash Deb. “Engineering optimisation by Cuckoo search.” International Journal of Mathematical Modelling and Numerical Optimisation 1.4 (2010): 330–343.
Andreou, Andreas S., Kypros Economides, and Anastasis Sofokleous. “An automatic Software test-data generation scheme based on data flow criteria and Genetic Algorithms.” Computer and Information Technology, 2007. CIT 2007. 7th IEEE International Conference on. IEEE, 2007.
Liu, Dan, X. U. E. J. U. N. Wang, and J. I. A. N. M. I. N. Wang. “Automatic test case generation based on Genetic Algorithm‖.” Journal of Theoretical and Applied Information Technology 48.1 (2013): 411–416.
Dong, Yuehua, and Jidong Peng. “Automatic generation of Software test cases based on improved Genetic Algorithm.” Multimedia Technology (ICMT), 2011 International Conference on. IEEE, 2011.
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Khan, R., Amjad, M., Srivastava, A.K. (2018). Optimization of Automatic Test Case Generation with Cuckoo Search and Genetic Algorithm Approaches. In: Bhatia, S., Mishra, K., Tiwari, S., Singh, V. (eds) Advances in Computer and Computational Sciences. Advances in Intelligent Systems and Computing, vol 554. Springer, Singapore. https://doi.org/10.1007/978-981-10-3773-3_40
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DOI: https://doi.org/10.1007/978-981-10-3773-3_40
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