Input Domain Reduction of Search-based Structural Test Data Generation using Interval Arithmetic

doi:10.23940/ijpe.18.06.p25.13301340

Abstract

Abstract:

The size of search space has an impact on the efficiency of test data generation by meta-heuristic algorithms. To enhance the efficiency of test data generation, a method that reduces search space utilizing interval arithmetic is proposed. Firstly, all input variables of the program are presented as interval variables. Then, the interval of each variable is gradually reduced by many constraint conditions in the target path. Finally, meta-heuristic algorithm with reduced search space is carried out to generate test data. Experimental results show the proposed method has advantages in the number of generations, running time, and success rate, which can significantly enhance the efficiency of test data by using meta-heuristic algorithms.

Submitted on March 7, 2018; Revised on April 4, 2018; Accepted on May 8, 2018
References: 14

Xuewei Lv, Song Huang, and Haijin Ji. Input Domain Reduction of Search-based Structural Test Data Generation using Interval Arithmetic [J]. Int J Performability Eng, 2018, 14(6): 1330-1340.

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

References 0

	G. Tassey, “The economic impacts of inadequate infrastructure for software testing,” National Institute of Standards and Technology, RTI Project, vol.7007, no.011, 2002.
	R. C. Eberchart, J. Kennedy, “particle swarm optimization,” in Proceeding of IEEE International Conference on Neural Networks, pp.1942–1948, Perth, Australia, 1995.
	R. E. Moore, R.B. Kearfott, and M.J. Cloud, “Introduction to interval analysis,” Siam, 2009.
	J. Mei, S. Y. Wang, “An improved genetic algorithm for test cases generation oriented paths,” Chinese journal of electronics, vol. 23, no. 3, pp. 494-498, 2014.
	S. Biswas, M. S. Kaiser and S. A. Mamun, “Applying Ant Colony Optimization in software testing to generate prioritized optimal path and test data,” in Proceeding of Electrical Engineering and Information Communication Technology (ICEEICT), pp. 1-6, IEEE, Khulna, Bangladesh, May 2015.
	Li, Y. Zhang, “Automatic generating all-path test data of a program based on PSO,” in Proceeding of Software Engineering, pp. 189-193, IEEE, Xiamen, China, May 2009.
	S. M. Mohi-Aldeen, R. Mohamad, and S. Deris, “Automated path testing using the negative selection algorithm, ” International Journal of Computational Vision and Robotics, vol. 7, no. 1, pp. 160-171, 2017.
	R. Sharma, A. Saha, “Optimization of object-oriented testing using firefly algorithm, ” Journal of Information and Optimization Sciences, vol. 38, no. 6, pp. 873-893, 2017.
	P. McMinn, M. Harman, K. Lakhotia, Y. Hassoun, and J. Wegener, “Input domain reduction through irrelevant variable removal and its effect on local, global, and hybrid search-based structural test data generation,” IEEE Transactions on Software Engineering, vol. 38, no. 2, pp.453–477, 2012.
	Arcuri, X. A.Yao, “ A memetic algorithm for test data generation of object oriented software,” in Proceedings of the 2007 IEEE Congress on Evolutionary Computation (CEC), pp. 2048–2055, IEEE, Singapore, 2007.
	J.C. B. Ribeiro, M.A. Zenha-Rela, and F.F. Vega, “Test case evaluation and input domain reduction strategies for the evolutionary testing of object-oriented software,” Information and Software Technology, vol. 51, no. 11, pp. 1534–1548, 2009.
	Y. Zhang, D. Gong, X. Yao, and Q. Lu, “ Generating Test Data Covering Multiple Paths Using Genetic Algorithm Incorporating with Reducing Input Domain,” in Proceeding of Chinese Intelligent Systems Conference, pp. 739-747, Springer, Singapore, October 2017.
	N. Tracey, J. Clark, K. Mander, and J. McDermid , “An automated framework for structural test-data generation,” in Proceeding of Automated Software Engineering, pp. 285-288, Hawaii, USA, 1998.
	S. Jiang, J. Shi, Y. Zhang, and H. Han, “Automatic test data generation based on reduced adaptive particle swarm optimization algorithm, ” Neurocomputing, vol. 158, pp. 109-116, 2015.