From Ontologies to Input Models for Combinatorial Testing

  • Franz WotawaEmail author
  • Yihao Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11146)


Ordinary tools for computing combinatorial test suites rely on simple input models comprising variables together with their domains and constraints limiting possible combinations. Modeling for combinatorial testing requires to represent the input domain of the application in a way such that it fits to the combinatorial testing input model. Depending on the application’s domain this mapping ranges from trivial to more complicated. In this paper, we focus on modeling for combinatorial testing in cases the application’s domain can be represented in form of an ontology, i.e., concepts and their relationships. We formally introduce the notation of ontology we rely on in this paper, and show how such ontologies can be automatically mapped to a combinatorial testing input model. We discuss the algorithm and show its properties.


Combinatorial testing Ontologies Combinatorial testing input models 



The research was supported by ECSEL JU under the project H2020 737469 AutoDrive - Advancing fail-aware, fail-safe, and fail-operational electronic components, systems, and architectures for fully automated driving to make future mobility safer, affordable, and end-user acceptable. AutoDrive is funded by the Austrian Federal Ministry of Transport, Innovation and Technology (BMVIT) under the program “ICT of the Future” between May 2017 and April 2020. More information Open image in new window.


  1. 1.
    Blomqvist, E., Seil Sepour, A., Presutti, V.: Ontology testing - methodology and tool. In: ten Teije, A. (ed.) EKAW 2012. LNCS (LNAI), vol. 7603, pp. 216–226. Springer, Heidelberg (2012). Scholar
  2. 2.
    Cohen, D.M., Dalal, S.R., Fredman, M.L., Patton, G.C.: The AETG system: an approach to testing based on combinatorial design. IEEE Trans. Softw. Eng. 23(7), 437–444 (1997)CrossRefGoogle Scholar
  3. 3.
    Feilmayr, C., Wöß, W.: An analysis of ontologies and their success factors for application to business. Data Knowl. Eng. 101, 1–23 (2016). Scholar
  4. 4.
    Hülsen, M., Zöllner, J.M., Weiss, C.: Traffic intersection situation description ontology for advanced driver assistance. In: 2011 IEEE Intelligent Vehicles Symposium (IV), pp. 993–999, June 2011.
  5. 5.
    Khalsa, S.K., Labiche, Y.: An orchestrated survey of available algorithms and tools for combinatorial testing. In: 25th International Symposium on Software Reliability Engineering, pp. 323–334 (2015)Google Scholar
  6. 6.
    Kuhn, D.R., Kacker, R.N., Lei, Y.: Combinatorial testing. In: Laplante, P.A. (ed.) Encyclopedia of Software Engineering. Taylor & Francis, Abingdon (2012)Google Scholar
  7. 7.
    Kuhn, D.R., Bryce, R., Duan, F., Ghandehari, L.S., Lei, Y., Kacker, R.N.: Combinatorial testing: theory and practice. Adv. Comput. 99, 1–66 (2015)CrossRefGoogle Scholar
  8. 8.
    Kuhn, R., Kacker, R., Lei, Y., Hunter, J.: Combinatorial software testing. Computer 42, 94–96 (2009)CrossRefGoogle Scholar
  9. 9.
    Kuhn, R., Kacker, R., Lei, Y.: Practical combinatorial testing. Technical report 800–142, NIST Special Publication (NIST SP), 100 Bureau Drive, Gaithersburg, MD 20899, USA, October 2010Google Scholar
  10. 10.
    Li, H., Guo, H., Chen, F., Yang, H., Yang, Y.: Using ontology to generate test cases for GUI testing. Int. J. Comput. Appl. Technol. 42(2/3), 213–224 (2011)CrossRefGoogle Scholar
  11. 11.
    Li, R., Ma, S.: The implementation of user interface autogenerate for spacecraft automatic tests based on ontology. In: 12th International Conference on Fuzzy Systems and Knowledge Discovery, pp. 2676–2681 (2015)Google Scholar
  12. 12.
    Moser, T., Dürr, G., Biffl, S.: Ontology-based test case generation for simulating complex production automation systems. In: 22nd International Conference on Software Engineering and Knowledge Engineering, pp. 478–483 (2010)Google Scholar
  13. 13.
    Naseer, H., Rauf, A.: Validation of ontology based test case generation for graphical user interface. In: 15th International Multitopic Conference (2012)Google Scholar
  14. 14.
    Nasser, V.H.: Ontology-based unit test generation. Master’s thesis, Amirkabir University of Technology (2007)Google Scholar
  15. 15.
    Nguyen, C.D., Perini, A., Tonella, P.: Ontology-based test generation for multiagent systems. In: 7th International Conference on Autonomous Agents and Multiagent Systems, pp. 1315–1318, May 2008Google Scholar
  16. 16.
    Nie, C., Leung, H.: A survey of combinatorial testing. ACM Comput. Surv. 43(2), 11 (2011)CrossRefGoogle Scholar
  17. 17.
    Regele, R.: Using ontology-based traffic models for more efficient decision making of autonomous vehicles. In: Fourth International Conference on Autonomic and Autonomous Systems (ICAS 2008), pp. 94–99, March 2008.
  18. 18.
    Satish, P., Basavaraja, M., Narayan, M.S., Rangarajan, K.: Building combinatorial test input model from use case artefacts. In: 10th IEEE International Conference on Software Testing, Verification and Validation Workshops, pp. 220–228 (2017)Google Scholar
  19. 19.
    Satish, P., Paul, A., Rangarajan, K.: Extracting the combinatorial test parameters and values from UML sequence diagrams. In: 7th IEEE International Conference on Software Testing, Verification, and Validation Workshops, pp. 88–97 (2014)Google Scholar
  20. 20.
    Satish, P., Sheeba, K., Rangarajan, K.: Deriving combinatorial test design model from UML activity diagram. In: 6th IEEE International Conference on Software Testing, Verification and Validation Workshops, pp. 331–337 (2013)Google Scholar
  21. 21.
    Schlenoff, C., Balakirsky, S., Uschold, M., Provine, R., Smith, S.: Using ontologies to aid navigation planning in autonomous vehicles. Knowl. Eng. Rev. 18(3), 243–255 (2003). Scholar
  22. 22.
    Souza, E.F., Falbo, R.A., Vijaykumar, N.L.: Using ontology patterns for building a reference software testing ontology. In: 17th IEEE International Enterprise Distributed Object Computing Conference Workshops, pp. 21–30 (2013)Google Scholar
  23. 23.
    de Souza, E.F.: Knowledge management applied to software testing: an ontology based framework. Ph.D. thesis, National Institute for Space Research (2014)Google Scholar
  24. 24.
    Tai, K., Lei, Y.: A test generation strategy for pairwise testing. IEEE Trans. Softw. Eng. 28(1), 109–111 (2002)MathSciNetCrossRefGoogle Scholar
  25. 25.
    Vasanthapriyan, S., Tian, J., Zhao, D., Xiong, S., Xiang, J.: An ontology-based knowledge sharing portal for software testing. In: 17th IEEE International Conference on Software Quality, Reliability and Security (Companion Volume), pp. 472–479 (2017)Google Scholar
  26. 26.
    Yu, L., Lei, Y., Kacker, R., Kuhn, D.: ACTS: a combinatorial test generation tool. In: 2013 IEEE Sixth International Conference on Software Testing, Verification and Validation (ICST), pp. 370–375 (2013)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  1. 1.Institute for Software TechnologyTechnische Universität GrazGrazAustria

Personalised recommendations