Skip to main content

An Integrated Automatic Test Data Generation System

  • Chapter
Case Technology

Abstract

The Godzilla automatic test data generator is an integrated collection of tools that implements a relatively new test data generation method—constraint-based testing—that is based on mutation analysis. Constraint-based testing integrates mutation analysis with several other testing techniques, including statement coverage, branch coverage, domain perturbation, and symbolic evaluation. Because Godzilla uses a rule-based approach to generate test data, it is easily extendible to allow new testing techniques to be integrated into the current system. This article describes the system that has been built to implement constraint-based testing Godzilla’s design emphasizes orthogonality and modularity, allowing relatively easy extensions. Godzilla’s internal structure and algorithms are described with emphasis on internal structures of the system and the engineering problems that were solved during the implementation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. A.T. Acree, “On mutation,” Ph.D. dissertation, Georgia Institute of Technology, Atlanta, GA, 1980.

    Google Scholar 

  2. A.T. Acree, T.A. Budd, R.A. DeMillo, R.J. Lipton, and F.G. Sayward, “Mutation analysis,” Technical Report GIT-ICS79/08, School of Information and Computer Science, Georgia Institute of Technology, Atlanta, GA, September 1979.

    Google Scholar 

  3. L.A. Clarke, “A system to generate test data and symbolically execute programs,” IFFY Trans. Software Eng. vol. 2, no. 3, pp. 215–222, September 1976.

    Article  Google Scholar 

  4. L.A. Clarke, A. Podgurski, D.J. Richardson, and S.J. Zeil, “A comparison of data flow path selection criteria,” in Proc. Eighth Int. Conf Software Eng., London UK, pp. 244–251, August 1985.

    Google Scholar 

  5. L.A. Clarke and D.J. Richardson, “Applications of symbolic evaluation,” J. Syst. Software, vol. 5, no. 1, pp. 15–35, 1985.

    Article  Google Scholar 

  6. R.A. DeMillo, D.S. Guindi, K.N. King, W.M. McCracken, and A.J. Offutt, “An extended overview of the Mothra software testing environment,” in Proc. Second Workshop Software Testing, Verification, and Analysis, Banff, Alberta, Canada, pp. 142–151, July 1988.

    Google Scholar 

  7. R.A. DeMillo, E.W. Krauser, R.J. Martin, A.J. Offutt, and E.H. Spafford, “The Mothra tool set,” in Proc. 22nd Hawaii Int. Conf. Syst. Sci., Kailua-Kona, HI, pp. 275–284, January 1989.

    Google Scholar 

  8. R.A. DeMillo, R.J. Lipton, and F.G. Sayward, “Hints on test data selection: Help for the practicing programmer,” IEEE Computer vol. 11, no. 4, pp. 34–41, April 1978.

    Article  Google Scholar 

  9. R.A. DeMillo, W.M. McCracken, R.J. Martin, and J.F. Passafiume, Software Testing and Evaluation. Benjamin/Cummings: Menlo Park, CA, 1987.

    Google Scholar 

  10. R.A. DeMillo and A.J. Offutt, “Constraint-based automatic test data generation,” IEEE Trans. Software Eng. vol. 17, no. 9, September 1991.

    Google Scholar 

  11. R.A. DeMillo and A.J. Offutt, “Experimental results of automatically generated adequate test sets,” in Proc. Sixth Annual Pacific Northwest Software Quality Conf., Portland, OR, pp. 209–232, September 1988.

    Google Scholar 

  12. J.B. Goodenough, “A survey of program issues,” in P. Wegner, ed., Research Directions in Software Technology. Prentice-Hall: Englewood Cliffs, NJ, 1979, pp. 316–340.

    Google Scholar 

  13. W.E. Howden, “Reliability of the path analysis testing strategy,” IEEE Trans. Software Eng. vol. 2, no. 3, pp. 208–215, September 1976.

    Article  MathSciNet  MATH  Google Scholar 

  14. W.E. Howden, “Weak mutation testing and completeness of test sets,” IEEE Trans. Software Eng. vol. 8, no. 4, pp. 371–379, July 1982.

    Article  Google Scholar 

  15. 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. 686–718, July 1991.

    Article  Google Scholar 

  16. R.J. Lipton and F.G. Sayward, “The status of research on program mutation,” in Digest for the Workshop on Software Testing and Test Documentation, pp. 355–373, December 1978.

    Google Scholar 

  17. Z. Manna, Mathematical Theory of Computation. McGraw-Hill: New York, 1974.

    MATH  Google Scholar 

  18. L.J. Morell, “Theoretical insights into fault-based testing,” in Proc. Second Workshop on Software Testing,Verification, and Analysis, Banff, Alberta, Canada, pp. 45–62, July 1988.

    Google Scholar 

  19. G. Myers, The Art of Software Testing. Wiley: New York, 1979.

    Google Scholar 

  20. A.J. Offutt, “Automatic test data generation,” Ph.D. dissertation, Georgia Institute of Technology, Atlanta, GA, 1988. Technical Report GIT-ICS 88/28 (also released as Purdue University Software Engineering Research Center Technical Report SERC-TR-25-P).

    Google Scholar 

  21. A.J. Offutt, “The coupling effect: Fact or fiction?” in Proc. Third Symp. on Software Testing,Analysis, and Verification, Key West, FL, pp. 131–140, December 1989.

    Chapter  Google Scholar 

  22. A.J. Offutt, “Using mutation analysis to test software,” in Proc. Seventh International Conference on Testing Computer Software, San Francisco, CA, pp. 65–77, June 1990.

    Google Scholar 

  23. S. Rapps and W.J. Weyuker, “Selecting software test data using data flow information,” IEEE Trans. Software Eng. vol. 11, no. 4, pp. 367–375, April 1985.

    Article  MATH  Google Scholar 

  24. E.J. Weyuker, “Assessing test data adequacy through program inference,” ACM Trans. Programming Languages Syst. vol. 5, no. 4, pp. 641–655, October 1983.

    Article  MATH  Google Scholar 

  25. M.R. Woodward and K. Halewood, “From weak to strong, dead or alive? An analysis of some mutation testing issues,” in Proc. Second Workshop on Software Testing, Verification,and Analysis, Banff, Alberta, Canada, pp. 152–158, July 1988.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1991 Springer Science+Business Media New York

About this chapter

Cite this chapter

Offutt, A.J. (1991). An Integrated Automatic Test Data Generation System. In: Yeh, R.T. (eds) Case Technology. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3644-4_7

Download citation

  • DOI: https://doi.org/10.1007/978-1-4615-3644-4_7

  • Received:

  • Revised:

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-6621-8

  • Online ISBN: 978-1-4615-3644-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics