Test Suite Quality for Model Transformation Chains

  • Eduard Bauer
  • Jochen M. Küster
  • Gregor Engels
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6705)

Abstract

For testing model transformations or model transformation chains, a software engineer usually designs a test suite consisting of test cases where each test case consists of one or several models. In order to ensure a high quality of such a test suite, coverage achieved by the test cases with regards to the system under test must be systematically measured. Using coverage analysis and the resulting coverage information, missing test cases and redundant test cases can be identified and thereby the quality of the test suite can be improved. As test cases consist of models, a coverage analysis approach must measure how complete models cover the domains of the transformations in the chain and to what degree of completeness transformations are covered when executing the test suite. In this paper, we present a coverage analysis approach for measuring test suite quality for model transformation chains. Our approach combines different coverage criteria and yields detailed coverage information that can be used to identify missing and redundant test cases.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
  2. 2.
    Ammann, P., Offutt, J.: Introduction to Software Testing. Cambridge University Press, New York (2008)CrossRefGoogle Scholar
  3. 3.
    Andrews, A., France, R., Ghosh, S., Craig, G.: Test Adequacy Criteria for UML Design Models. Software Testing, Verification and Reliability 13(2), 95–127 (2003)CrossRefGoogle Scholar
  4. 4.
    Baudry, B., Dinh-Trong, T., Mottu, J.-M., Simmonds, D., France, R., Ghosh, S., Fleurey, F., Le Traon, Y.: Model Transformation Testing Challenges. In: Proceedings of IMDT workshop in conjunction with ECMDA 2006, Bilbao, Spain (2006)Google Scholar
  5. 5.
    Bauer, E.: Analyzing Test Suites for Model Transformation Chains. Master’s thesis, University of Paderborn (2010)Google Scholar
  6. 6.
    Csertán, G., Huszerl, G., Majzik, I., Pap, Z., Pataricza, A., Varró, D.: VIATRA: Visual Automated Transformations for Formal Verification and Validation of UML Models. In: ASE 2002: 17th IEEE International Conference on Automated Software Engineering, pp. 267–270. IEEE Computer Society Press, Los Alamitos (2002)Google Scholar
  7. 7.
    Czarnecki, K., Helsen, S.: Feature-based Survey of Model Transformation Approaches. IBM Systems Journal 45(3), 621–645 (2006)CrossRefGoogle Scholar
  8. 8.
    Cariou, E., Marvie, R., Seinturier, L., Duchien, L.: OCL for the Specification of Model Transformation Contracts. In: Workshop OCL and Model Driven Engineering of the Seventh International Conference on UML Modeling Languages and Applications UML 2004, Lisbon, Portugual, October 12 (2004)Google Scholar
  9. 9.
    Fleurey, F., Baudry, B., Muller, P., Le Traon, Y.: Qualifying Input Test Data for Model Transformations. Software and Systems Modeling 8(2), 185–203 (2009)CrossRefGoogle Scholar
  10. 10.
    Object Management Group (OMG). Meta Object Facility (MOF) 2.0 Query/View/Transformation Specification Version 1.1 (January 2011)Google Scholar
  11. 11.
    Guerra, E., de Lara, J., Kolovos, D., Paige, R.: A Visual Specification Language for Model-to-Model Transformations. In: IEEE Symposium on Visual Languages and Human-Centric Computing, vol. 0, pp. 119–126. IEEE Computer Society Press, Los Alamitos (2010)Google Scholar
  12. 12.
    Harrold, M.J., Gupta, R., Soffa, M.L.: A Methodology for Controlling the Size of a Test Suite. ACM Transactions on Software Engineering and Methodology 2(3), 270–285 (1993)CrossRefGoogle Scholar
  13. 13.
    Heimdahl, M., George, D.: Test-suite Reduction for Model Based Tests: Effects on Test Quality and Implications for Testing. In: Proceedings of the 19th IEEE International Conference on Automated Software Engineering (ASE), pp. 176–185. IEEE Computer Society, Los Alamitos (2004)Google Scholar
  14. 14.
    Jouault, F., Allilaire, F., Bézivin, J., Kurtev, I.: ATL: A Model Transformation Tool. Science of Computer Programming 72(1-2), 31–39 (2008)MathSciNetCrossRefMATHGoogle Scholar
  15. 15.
    Küster, J.M., Gerth, C., Förster, A., Engels, G.: Detecting and Resolving Process Model Differences in the Absence of a Change Log. In: Dumas, M., Reichert, M., Shan, M.-C. (eds.) BPM 2008. LNCS, vol. 5240, pp. 244–260. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  16. 16.
    Leon, D., Podgurski, A., White, L.: Multivariate Visualization in Observation-based Testing. In: ICSE 2000: Proceedings of the 22nd International Conference on Software Engineering, pp. 116–125. ACM Press, New York (2000)Google Scholar
  17. 17.
    McQuillan, J., Power, J.: White-Box Coverage Criteria for Model Transformations. In: 1st International Workshop on Model Transformation with ATL, Nantes, France, July 8-9 (2009)Google Scholar
  18. 18.
    Meyer, B.: Applying ”Design by Contract”. Computer 25(10), 40–51 (1992)CrossRefGoogle Scholar
  19. 19.
    Object Management Group (OMG). Business Process Modeling Notation, V2.0 Beta 2 (June 2010)Google Scholar
  20. 20.
    Parsa, S., Khalilian, A., Fazlalizadeh, Y.: A New Algorithm to Test Suite Reduction Based on Cluster Analysis. In: International Conference on Computer Science and Information Technology, vol. 0, pp. 189–193 (2009)Google Scholar
  21. 21.
    Rothermel, G., Harrold, M.J., Ostrin, J., Hong, C.: An Empirical Study of the Effects of Minimization on the Fault Detection Capabilities of Test Suites. In: ICSM 1998: Proceedings of the International Conference on Software Maintenance, pp. 34–43. IEEE Computer Society Press, Los Alamitos (1998)Google Scholar
  22. 22.
    von Pilgrim, J., Vanhooff, B., Schulz-Gerlach, I., Berbers, Y.: Constructing and Visualizing Transformation Chains. In: Schieferdecker, I., Hartman, A. (eds.) ECMDA-FA 2008. LNCS, vol. 5095, pp. 17–32. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  23. 23.
    Yan, S., Chen, Z., Zhao, Z., Zhang, C., Zhou, Y.: A Dynamic Test Cluster Sampling Strategy by Leveraging Execution Spectra Information. In: ICST 2010: Proceedings of the 2010 Third International Conference on Software Testing, Verification and Validation, pp. 147–154. IEEE Computer Society Press, Washington, DC, USA (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Eduard Bauer
    • 1
  • Jochen M. Küster
    • 1
  • Gregor Engels
    • 2
  1. 1.IBM ResearchRüschlikonSwitzerland
  2. 2.Department of Computer ScienceUniversity of PaderbornGermany

Personalised recommendations