|Table of Contents|

[1] Nie Changhai, Xu Baowen, , et al. Generating test cases for software configuration testing [J]. Journal of Southeast University (English Edition), 2004, 20 (1): 26-30. [doi:10.3969/j.issn.1003-7985.2004.01.006]
Copy

Generating test cases for software configuration testing()
Share:

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

Volumn:
20
Issue:
2004 1
Page:
26-30
Research Field:
Computer Science and Engineering
Publishing date:
2004-03-30

Info

Title:
Generating test cases for software configuration testing
Author(s):
Nie Changhai1 3 Xu Baowen1 2 3 4
1Department of Computer Science and Engineering, Southeast University, Nanjing 210096, China
2School of Computer Science, National University of Defense Technology, Changsha 410073, China
3Jiangsu Institute of Software Quality, Nanjing 210096, China
4State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, China
Keywords:
software testing configuration testing test case combination cover
PACS:
TP311
DOI:
10.3969/j.issn.1003-7985.2004.01.006
Abstract:
Software configuration testing is used to test a piece of software with all kinds of hardware to ensure that it can run properly on them. This paper generates test cases for configuration testing with several common methods, such as multiple single-factor experiments, uniform design, and orthogonal experiment design used in other fields. This paper analyzes their merits and improves the orthogonal experiment design method with pairwise testing, and decrease the testing risk caused by incomplete testing with a method of multiple-factors-covering. It also presents a simple factor cover method which can cover all the factors and pairwise combinations to the greatest degree. Finally some comparisons of these methods are made on the aspects of test suite scale, coverage, and usability, etc.

References:

[1] Patton Ron. Software testing [M]. Indianapolis: Sams Publishing, 2001.
[2] Cohen D M, Dalal S R, Fredman M L, et al. The AETG system: an approach to testing based on combinatorial design [J]. IEEE Trans on Software Engineering, 1997, 23(7): 437-444.
[3] Cohen D M, Dalal S R, Parelius J, et al. The combinatorial design approach to automatic test generation [J]. IEEE Software, 1996, 13(5): 83-87.
[4] Lei Y, Tai K C. In_parameter_oder: a test gene ̄ration strategy for pairwise testing [R]. Technical Report TR-2001-03. Raleigh, North Carolina: Department of Computer Science, North Carolina State University, 2001.
[5] Tai K C, Lei Y. A test generation strategy for pairwise testing [J]. IEEE Trans on Software Engineering, 2002, 28(1): 109-111.
[6] Kobayashi N, Tsuchiya T, Kikuno T. A new method for constructing pairwise covering designs for software testing [J]. Information Processing Letters, 2002, 81(2): 85-91.
[7] Heller E. Using design of experiment structures to generate test cases [A]. In: Proc 12th Int’l Conf Testing Computer Software, ACM [C]. New York, 1995. 33-41.
[8] Mandl R. Orthogonal Latin squares: an application of experimental design to compiler testing [J]. Communications of the ACM, 1985, 28(10): 1054-1058.
[9] Brownlie R, Prowse J, Phadke M. Robust testing of AT&T PMX/StarMail using OATS [J]. AT&T Technical Journal, 1992, 71(3): 41-47.
[10] Cohen D M, Fredman M L. New techniques for designing qualitatively independent systems [J]. J Combin Designs, 1998, 6(6): 411-416.
[11] Williams A W, Probert R L. A practical strategy for testing pairwise coverage of network interfaces [A]. In: Proc 7th International Symp Software Reliability Engineer [C]. 1997. 246-254.
[12] Fang K T, Wang Y. Number-theoretic methods in statistics [M]. London: Chapman & Hall, 1993.

Memo

Memo:
Biographies: Nie Changhai(1971—), male, graduate; Xu Baowen(corresponding author), male, professor, bwxu@seu.edu.cn.
Last Update: 2004-03-20