Abstract

The development and testing of software-based systems is an essential activity for the automotive industry. 50-70 software-based systems with different complexities and developed by various suppliers are installed in today’s premium vehicles, communicating with each other via different bus systems. The integration and testing of systems of this complexity is a very challenging task. The aim of testing is to detect faults in the systems under test and to convey confidence in the correct functioning of the systems if no faults are found during comprehensive testing. Faults not found in the different testing phases could have significant consequences that range from customer dissatisfaction to damage of physical property or, in safety relevant areas, even to the endangering of human lives. Therefore, the thorough testing of developed systems is essential. Evolutionary Testing tries to improve the effectiveness and efficiency of the testing process by transforming testing objectives into search problems, and applying evolutionary computation in order to solve them.

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References

  1. 1.
    Dijkstra, E.W., Dahl, O.J., Hoare, C.A.R.: Structured programming. Academic Press, London (1972)MATHGoogle Scholar
  2. 2.
    Wegener, J., Grochtmann, M.: Verifying timing constraints of real-time systems by means of Evolutionary Testing. Real-Time, Systems 15(3), 275–298 (1998)CrossRefGoogle Scholar
  3. 3.
    Jones, B.-F., Sthamer, H.-H., Eyres, D.: Automatic structural testing using genetic algorithms. Software Engineering Journal 11(5), 299–306 (1996)CrossRefGoogle Scholar
  4. 4.
    Sthamer, H.-H.: The automatic generation of software test data using genetic algorithms. PhD Thesis, University of Glamorgan, Pontyprid, Wales, Great Britain (1996)Google Scholar
  5. 5.
    Tracey, N., Clark, J., Mander, K., McDermid, J.: An automated framework for structural test-data generation. In: Proceedings of the 13th IEEE Conference on Automated Software Engineering, Hawaii, USA (1998)Google Scholar
  6. 6.
    Buehler, O., Wegener, J.: Evolutionary functional testing of an automated parking system. In: Proceedings of the International Conference on Computer, Communication and Control Technologies and the 9th. International Conference on Information Systems Analysis and Synthesis, Orlando, Florida, USA (2003)Google Scholar
  7. 7.
    Buehler, O., Wegener, J.: Automatic testing of an autonomous parking system using evolutionary computation. SAE World Congress, Detroit, USA (2004)Google Scholar
  8. 8.
    Buehler, O., Wegener, J.: Evolutionary functional testing of a vehicle brake assistant system. In: 6th Metaheuristics International Conference, Vienna, Austria (2005)Google Scholar
  9. 9.
    Wegener, J., Baresel, A., Sthamer, H.: Evolutionary test environment for automatic structural testing. Special Issue of Information and Software Technology devoted to the Application of Meta-heuristic Algorithms to Problems in Software Engineering (2001)Google Scholar
  10. 10.
    McMinn, P.: Search-based software test data generation: a survey. Software Testing, Verification and Reliability 14(2), 105–156 (2004)CrossRefGoogle Scholar
  11. 11.
    Wegener, J., Mueller, F.: A comparison of static analysis and evolutionary testing for the verification of timing constraints. Real-Time Systems 21(3), 241–268 (2001)MATHCrossRefGoogle Scholar
  12. 12.
    Puschner, P., Nossal, R.: Testing the results of static worst-case execution-time analysis. In: Proceedings of the 19th IEEE Real-Time Systems Symposium, Madrid, Spain, pp. 134–143 (1998)Google Scholar
  13. 13.
    Tracey, N., Clark, J., Mander, K.: The way forward for unifying dynamic test-case generation: The optimisation-based approach. In: International Workshop on Dependable Computing and Its Applications, pp. 169–180 (1998)Google Scholar
  14. 14.
    Gross, H.-G.: Evolutionary testing in component-based real-time system construction. In: Proceedings of the Genetic and Evolutionary Computation Conference. Late Breaking Papers, New York, USA, pp. 207–214 (2002)Google Scholar
  15. 15.
    Harman, M., Hu, L., Hierons, R., Baresel, A., Sthamer, H.: Improving evolutionary testing by flag removal. In: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1359–1366. Morgan Kaufmann, New York (2002)Google Scholar
  16. 16.
    Baresel, A., Sthamer, H.: Evolutionary testing of flag conditions. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003. LNCS, vol. 2724, pp. 2442–2454. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  17. 17.
    Harman, M., Fox, C., Hierons, R., Hu, L., Danicic, S., Wegener, J.: VADA: A transformation-based system for variable dependence analysis. In: 2nd IEEE International Workshop on Source Code Analysis and Manipulation, Montreal, Canada, pp. 55–64 (2002)Google Scholar
  18. 18.
    McMinn, P., Holcombe, M.: The state problem for evolutionary testing. In: Proceedings of the Genetic and Evolutionary Computation Conference, Chicago, USA. LNCS, vol. 2274, pp. 2488–2497. Springer, Heidelberg (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Joachim Wegener
    • 1
  1. 1.DaimlerChrysler AG, Research and TechnologyBerlinGermany

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