Mats Grindal
ABSTRACT
Combination strategies are test methods that generate test cases based on input parameter models. This paper suggests a structured modeling method used to translate requirements expressed in a general format into an input parameter model suitable for combination strategies.
This paper also describes results from two initial experiments exploring the efficiency and effectiveness of the modeling method. These results indicate that the resulting models may contain enough information to detect the vast majority of faults in the system under test. Further, results indicate that the modeling method is simple enough to use in practical testing.
- {1} B. Beizer. Software Testing Techniques. Van Nostrand Reinhold, 1990. Google Scholar
- {2} T. Chen, P.-L. Poon, S.-F. Tang, and T. Tse. On the Identification of Categories and Choices for Specification-based Test Case Generation. Information and Software Technology, 46(13):887-898, 2004.Google Scholar
- {3} T. Chen, S.-F. Tang, P.-L. Poon, and T. Tse. Identification of Categories and Choices in Activity Diagrams. In Proceedings of the Fifth International Conference on Quality Software (QSIC 2005) 19-20 September 2005, Melbourne, Australia, pages 55-63. IEEE Computer Society, September 2005. Google Scholar
- {4} D. M. Cohen, S. R. Dalal, A. Kajla, and G. C. Patton. The automatic efficient test generator (AETG) system. In Proceedings of Fifth International Symposium on Software Reliability Engineering (ISSRE'94), Los Alamitos, California, USA, November 6-9, 1994, pages 303-309. IEEE Computer Society, 1994.Google Scholar
- {5} D. M. Cohen, S. R. Dalal, J. Parelius, and G. C. Patton. The Combinatorial Design Approach to Automatic Test Generation. IEEE Software, 13(5):83-89, September 1996. Google Scholar
- {6} M. Grindal, Å. G. Dahlstedt, A. J. Offutt, and J. Mellin. Using Combination Strategies for Software Testing in Practice - A proof-of-concept. Technical Report HS-IKI-TR-06-010, School of Humanities and Informatics, University of Skövde, 2006.Google Scholar
- {7} M. Grindal, B. Lindström, A. J. Offutt, and S. F. Andler. An evaluation of combination strategies for test case selection. Empirical Software Engineering, Available in SpringerLink electronic Online First version, 2006. Google Scholar
- {8} M. Grindal, A. J. Offutt, and S. F. Andler. Combination testing strategies: A survey. Software Testing, Verification, and Reliability, 15(3):167-199, September 2005.Google Scholar
- {9} M. Grochtmann and K. Grimm. Classification Trees for Partition Testing. Journal of Software Testing, Verification, and Reliability, 3(2):63-82, 1993.Google Scholar
- {10} Y. K. Malaiya. Antirandom testing: Getting the most out of black-box testing. In Proceedings of the International Symposium On Software Reliability Engineering, (ISSRE'95), Toulouse, France, Oct, 1995, pages 86-95, Oct. 1995.Google Scholar
- {11} G. J. Myers. The Art of Software Testing. John Wiley and Sons, 1979. Google Scholar
- {12} T. J. Ostrand and M. J. Balcer. The Category-Partition Method for Specifying and Generating Functional Tests. Communications of the ACM, 31(6):676-686, June 1988. Google Scholar
- {13} H. Yin, Z. Lebne-Dengel, and Y. K. Malaiya. Automatic Test Generation using Checkpoint Encoding and Antirandom Testing. Technical Report CS-97-116, Colorado State University, 1997.Google Scholar
Index Terms
- Input parameter modeling for combination strategies
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