[1] Jiang Yuting, Li Bixin,. Novel technique for cost reduction in mutation testing [J]. Journal of Southeast University (English Edition), 2011, 27 (1): 17-21. [doi:10.3969/j.issn.1003-7985.2011.01.004]

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Novel technique for cost reduction in mutation testing()

一种用于降低变异测试代价的新技术

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

27

Issue:

2011 1

Page:

17-21

Research Field:

Computer Science and Engineering

Publishing date:

2011-03-30

Info

Title:

Novel technique for cost reduction in mutation testing

一种用于降低变异测试代价的新技术

Author(s):

Jiang Yuting;  Li Bixin

School of Computer Science and Engineering, Southeast University, Nanjing 210096, China

蒋玉婷;  李必信

东南大学计算机科学与工程学院, 南京210096

Keywords:

mutation testing;  mutation distance;  sample learning;  execution cost;  test case selection

变异测试;  变异距离;  样本学习;  执行代价;  测试用例选择

PACS:

TP311

DOI:

10.3969/j.issn.1003-7985.2011.01.004

Abstract:

Aimed at the problem of expensive costs in mutation testing which has hampered its wide use, a technique of introducing a test case selection into the process of mutation testing is proposed. For each mutant, a fixed number of test cases are selected to constrain the maximum allowable executions so as to reduce useless work. Test case selection largely depends on the degree of mutation. The mutation distance is an index describing the semantic difference between the original program and the mutated program. It represents the percentage of effective test cases in a test set, so it can be used to guide the selection of test cases. The bigger the mutation distance is, the easier it is that the mutant will be killed, so the corresponding number of effective test cases for this mutant is greater. Experimental results suggest that the technique can remarkably reduce execution costs without a significant loss of test effectiveness.

针对变异测试代价大、无法广泛应用的问题, 提出了一种在变异测试过程中引进测试用例选择以降低测试代价的方法.通过为每个变异体选择一定数量的测试用例, 约束变异体允许执行的最大次数, 从而减少无用功.测试用例的选择与变异体的变异程度相关, 变异距离是描述源程序和变异体之间差异程度的指标, 能够衡量测试集中有效测试用例的比例, 进而指导测试用例的选择.距离越大, 意味着变异体越容易被杀死, 对应的有效测试用例则越多.实验结果表明该方法在不影响测试效果的情况下, 可以明显降低变异测试的执行成本.

References:

[1] DeMillo R A, Lipton R J, Sayward F G. Hints on test data selection: help for the practicing programmer[J]. IEEE Computer Society, 1978, 11(4): 34-41.
[2] Frankl P G, Weiss S N, Hu C. All-uses versus mutation: an experimental comparison of effectiveness[J]. Journal of Systems and Software, 1997, 38(3): 235-253.
[3] Wong W E, Mathur A P. Fault detection effectiveness of mutation and data-flow testing[J]. Software Quality Journal, 1995, 4(1): 69-83.
[4] Andrews J H, Brand L C, Labiche Y. Is mutation an appropriate tool for testing experiments? [C]//Proceedings of the 27th International Conference on Software Engineering. Los Alamitos, CA, USA, 2005: 402-411.
[5] Yue J, Harman M. An analysis and survey of the development of mutation testing[R]. London: Center for Research on Evolution, Search and Testing(CREST), 2009.
[6] Wong W E, Mathur A P. Reducing the cost of mutation testing: an empirical study[J]. The Journal of Systems and Software, 1995, 31(3):185-196.
[7] Bottaci L, Mresa E S. Efficiency of mutation operators and selective mutation strategies: an empirical study[J]. Software Testing, Verification and Reliability, 1999, 9(4): 205-232.
[8] Zhang L, Hou S S, Hu J J, et al. Is operator-based mutant selection superior to random mutant selection? [C]//Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering. New York, NY, USA:ACM, 2010:435-444.
[9] Offutt A J, Lee A, Rothermel G, et al. An experimental determination of sufficient mutant operators[J]. ACM Transactions on Software Engineering and Methodology, 1996, 5(2): 99-118.
[10] Offutt A J, Rothermel G, Zapf C. An experimental evaluation of selective mutation[C]//Proceedings of the 15th International Conference on Software Engineering. Baltimore, MD, USA, 1993:100-107.
[11] DeMillo R A, Offutt A. Constraint-based automatic test data generation[J]. IEEE Transactions on Software Engineering, 1991, 17(9):900-910.

Memo

Memo:

Biographies: Jiang Yuting(1986—), female, graduate; Li Bixin(corresponding author), male, doctor, professor, bx.li@seu.edu.cn.
Foundation items: The National High Technology Research and Development Program of China(863 Program)(No.2008AA01Z113), the National Natural Science Foundation of China(No. 60773105, 60973149).
Citation: Jiang Yuting, Li Bixin. Novel technique for cost reduction in mutation testing[J].Journal of Southeast University(English Edition), 2011, 27(1):17-21.[doi:10.3969/j.issn.1003-7985.2011.01.004]

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