Parallel Mutant Execution Techniques in Mutation Testing Process for Simulink Models

• Autorzy: Hanh L. T. M. , Binh N. T. , Tung K. T.

Identyfikatory

DOI

10.26636/jtit.2017.113617

• Języki publikacji: EN

Abstrakty

EN

Mutation testing – a fault-based technique for software testing – is a computationally expensive approach. One of the powerful methods to improve the performance of mutation without reducing effectiveness is to employ parallel processing, where mutants and tests are executed in parallel. This approach reduces the total time needed to accomplish the mutation analysis. This paper proposes three strategies for parallel execution of mutants on multicore machines using the Parallel Computing Toolbox (PCT) with the Matlab Distributed Computing Server. It aims to demonstrate that the computationally intensive software testing schemes, such as mutation, can be facilitated by using parallel processing. The experiments were carried out on eight different Simulink models. The results represented the efficiency of the proposed approaches in terms of execution time during the testing process.

Słowa kluczowe

EN

mutant execution; mutation testing; parallel processing; software testing

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2017
• Tom: nr 4
• Strony: 90--100
• Opis fizyczny: Bibliogr. 31 poz., rys., tab.

Twórcy

autor

Hanh L. T. M.

• The University of Danang, University of Science and Technology, 54 Nguyen Luong Bang, Lien Chieu, Danang, Vietnam

autor

Binh N. T.

• The University of Danang, University of Science and Technology, 54 Nguyen Luong Bang, Lien Chieu, Danang, Vietnam

autor

Tung K. T.

• The University of Danang, University of Science and Technology, 54 Nguyen Luong Bang, Lien Chieu, Danang, Vietnam

Bibliografia

• [1] B. Beizer, Software Testing Techniques, 2nd ed., Thomason Computer Press, 1990.
• [2] R. H. Untch, A. J. Offutt, and M. J. Harrold, “Mutation analysis using program schemata”, in Proc. Int. Symp. on Software, Cambridge, Massachusetts, 1993, pp. 28–30.
• [3] K. N. King and A. J. Offutt, “A Fortran language system for mutation based software testing”, Software: Practice and Experience, vol. 21, no. 7, pp. 685–718, 1991.
• [4] E. F. Barbosa, J. C. Maldonado, A. Marcelo, and R. Vincenzi, “Toward the determination of sufficient mutant operators for C”, Software Test., Verif. and Reliabil., vol. 11, no. 2, pp. 13–136, 2001.
• [5] A. J. Offutt, G. Rothermel, R. H. Untch, and C. Zapf, “An experimental determination of suffcient mutant operators”, ACM Trans. on Software Engin. and Methodol., vol. 5, no. 2, pp. 99–118, 1996.
• [6] W. E. Wong and A. P. Mathur, “How strong is constrained mutation in fault deletion”, in Proc. Int. Computer Symp. ICS’94, Hsinchu, Taiwan, Republic of China, 1994, pp. 515–520.
• [7] W. E. Wong, J. C. Maldonado, M. E. Delamaro, and A. P. Mathur, “Constrained mutation in C programs”, in Proc. 8th Simpósio Brasileiro de Engenharia de Software SBES 94, Curitiba, PR, Brazil, 1994, pp. 439–452.
• [8] M. Polo, M. Piattini, and I. Garcia-Rodriguez, “Decreasing the cost of mutation testing with 2-order mutants”, Softw. Test. Verif. Reliab., vol. 19, no. 2, pp. 111–131, 2008.
• [9] Y. S. Ma, J. Offutt, and Y. R. Kwon, “MuJava: an automated class mutation system”, Software Test., Verif. and Reliabil., vol. 15, no. 2, pp. 97–133, 2005.
• [10] Y. Jia and M. Harman, “An analysis and survey of the development of mutation testing”, IEEE Trans. on Software, vol. 37, no. 5, pp. 649–678, 2011.
• [11] P. R. Mateo and M. P. Usaola, “Mutation testing cost reduction techniques: a survey”, IEEE Software, vol. 27, no. 3, pp. 80–86, 2010.
• [12] A. P. Mathur and E. W. Krauser, “Modeling mutation on a vector processor”, in Proc. 10th Int. Conf. on Software Engin. ICSE’88, Singapore, 1988, pp. 154–161.
• [13] E. W. Krauser, A. P. Mathur, and V. J. Rego, “High performance software testing on SIMD machine”, IEEE Trans. on Software Engin., vol. 17, no. 5, pp. 403–423, 1991.
• [14] B. Choi and A. Mathur, “High-performance mutation testing”, J. of Syst. and Software, vol. 20, no. 2, pp. 135–152, 1993.
• [15] R. A. DeMillo, D. S. Guindi, K. N. King, W. M. McCracken, and J. Offutt, “An extended overview of the Mothra software testing environment”, in Proc. 2nd Worksh. on Softw. Test., Verif. and Anal., Banff, Alberta, Canada, 1988, pp. 142–151.
• [16] A. J. Offutt, R. P. Pargas, S. V. Fichter, and P. K. Khambekar, “Mutation testing of software using a MIMD computer”, in Proc. Int. Conf. on Parallel Process. ICPP 1992, Chicago, Illinois, USA, 1992, pp. 257–266.
• [17] V. N. Fleyshgakker and S. N. Weiss, “Efficient mutation analysis: a new approach”, in Proc. Int. Symp. on Software Test. and Anal. ISSTA 1994, Seattle, WA, USA, 1994, pp. 185–195.
• [18] S. N. Weiss and V. N. Fleyshgakker, “Improved serial algorithms for mutation analysis”, in Proc. Int. Symp. on Software Test. and Anal. ISSTA 1993, Cambridge, MA, USA, 1993, pp. 149–158.
• [19] P. R. Mateo and M. P. Usaola, “Parallel mutation testing”, J. of Software Test., Verif. and Reliabil., vol. 23, no. 4, pp. 315–350, 2013.
• [20] P. R. Mateo and M. P. Usaola,“Bacterio: Java mutation testing tool: A framework to evaluate quality of tests cases”, in Proc. of the Int. Conf. on Software Mainten. ICSM 2012, Trento, Italy, 2012, pp. 646–649.
• [21] S. F. Hummel, E. Schonberg, and L. E. Flynn, “Factoring: A method for scheduling parallel loops”, J. of Commun. of ACM, vol. 35, no. 8, pp. 90–101, 1992.
• [22] C. C. Pablo, G. M. Mercedes, and N. Alberto, “EMINENT: EMbarrassINgly parallEl mutatioN Testing”, Procedia Comp. Science, vol. 80, pp. 63–73, 2016.
• [23] I. Saleh and K. Nagi, “Hadoopmutator: A cloud-based mutation testing framework”, in 14th Int. Conf. on Software Reuse ICSR 2015, Miami, FL, USA, 2014, pp. 172–187.
• [24] Matlab Inc. [Online]. Available: http://www.mathworks.com/ products/simulink/ (accessed on March 10, 2017).
• [25] K. Ghani, J. A. Clark, and Y. Zhan, “Comparing Algorithms for Search-based Test Data Generation of Matlab Simulink Model, in Proc. 10th IEEE Congr. on Evol. Comput. CEC’09, Trondheim, Norway, 2009, pp. 2940–2947.
• [26] R. DeMillo, R. Lipton, and F. Sayward, “Hints on test data selection: help for practicing for programmer”, IEEE Computer, vol. 11, no. 4, pp. 34–41, 1978.
• [27] L. T. M. Hanh and N. T. Binh, “Mutation Operators for Simulink Models”, in Proc. of the 4th Int. Conf. on Knowl. and Syst. Engin. KSE 2012, Danang, Vietnam, 2012, pp. 54–59.
• [28] T. A. Budd and D. Angluin, “Two notions of correctness and their relation”, Acta Informatica, vol. 18, no. 1, pp. 31–45, 1982.
• [29] L. T. M. Hanh and N. T. Binh, “Automatic generation of mutants for simulink models”, in Proc. 16th Nat. Conf.: Selec. Problems About IT and Telecommun., Danang, Vietnam, 2013, pp. 339–346.
• [30] A. Krishnamurthy, S. Samsi, and V. Gadepally, “Parallel Matlab techniques”, in Image Processing, Y.-S. Chen, Ed. InTech, 2009 [Online]. Available: http://www.intechopen.com/books/ image-processing/parallel-matalab-techniques
• [31] G. Sharma and J. Martin, “MATLAB: A language for parallel computing”, Int. J. of Parallel Programm., vol. 37, no. 1, pp. 3–36, 2009.