An Approach to Mutation-Based Test Data Generation

Fang Wang; Ri Na Wu; Shu Fang  Lee; Tian Hua  Zheng

doi:10.4028/www.scientific.net/AMM.347-350.491

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 347-350An Approach to Mutation-Based Test Data Generation

An Approach to Mutation-Based Test Data Generation

Abstract:

Software testing is an important technology used to assure the quality of software. The design of test data is very important, which determines the testing effect in the software testing. Existing design approach to test data cant simulate the fault in software run-environment systematically. Mutation testing is an effective software testing method, which can simulate software defects systematically. Using mutation testing for reference, this paper proposes an approach to mutation-based test data generation. By analyzing the demands of test data, such as coverage rate, fault simulation, we design a series of data mutation operators, which can accomplish design of test data systematically. Experiments are carried out on the supporting tool to validate the effectiveness of this approach.

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Periodical:

Applied Mechanics and Materials (Volumes 347-350)

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491-495

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https://doi.org/10.4028/www.scientific.net/AMM.347-350.491

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Online since:

August 2013

Authors:

Fang Wang, Ri Na Wu, Shu Fang Lee, Tian Hua Zheng

Keywords:

Fault Simulation, Mutation Operator, Software Testing, Test Data

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References

[1] Aichernig, Bernhard K., et al. Fault-based test case generation for component connectors., Theoretical Aspects of Software Engineering, 2009. TASE 2009. Third IEEE International Symposium on. IEEE, (2009).

DOI: 10.1109/tase.2009.14

Google Scholar

[2] Kochte, Michael A., et al. Efficient fault simulation on many-core processors., Design Automation Conference (DAC), 2010 47th ACM/IEEE. IEEE, (2010).

DOI: 10.1145/1837274.1837369

Google Scholar

[3] Jia, Yue, and Mark Harman. An analysis and survey of the development of mutation testing., Software Engineering, IEEE Transactions on 37. 5 (2011): 649-678.

DOI: 10.1109/tse.2010.62

Google Scholar

[4] Bai, Xiaoying, Shufang Lee, and Yinong Chen. Mutation-based simulation test data generation for testing complex real-time software. " Simulation Symposium, 2007. ANSS, 07. 40thAnnual. IEEE, 2007, pp.73-80.

DOI: 10.1109/anss.2007.30

Google Scholar

[5] Andrews, James H., et al. Using mutation analysis for assessing and comparing testing coverage criteria., Software Engineering, IEEE Transactions on 32. 8 (2006): 608-624.

DOI: 10.1109/tse.2006.83

Google Scholar

[6] Murnane, Tafline, and Karl Reed. On the effectiveness of mutation analysis as a black box testing technique., Software Engineering Conference, 2001. Proceedings. 2001 Australian. IEEE, (2001).

DOI: 10.1109/aswec.2001.948492

Google Scholar

[7] Johnson, James B., Verag Mecoyan, and Eddie Tang. Dynamic simulator software., AUTOTESTCON Proceedings, 2000 IEEE. IEEE, 2000: 300-312.

DOI: 10.1109/autest.2000.885606

Google Scholar