Component-Based Hazard Analysis: Optimal Designs, Product Lines, and Online-Reconfiguration

  • Holger Giese
  • Matthias Tichy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4166)


Software plays an important role in the safety of today’s systems and is increasingly used to create system with variants in form of product families or systems with online-reconfiguration in a cost-efficient manner. Therefore, the required hazard analysis has to consider not only a concrete system and its embedded software but also the different software configurations. We present several extensions to an existing component-based hazard analysis approach. At first, our approach permits to identify the optimal design variant w.r.t. the probabilities of the considered hazard. As the number of variants in a product family is often enormous, our approach secondly supports the hazard analysis of a whole product family at once. The analysis identifies the variant or combination of variants with the worst hazard probability. Finally, we show that also the hazards of systems with online-reconfiguration can be analyzed using the presented approach.


Hazard Analysis Product Family Fault Tree Binary Decision Diagram Failure Propagation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Grimm, K.: Software technology in an automotive company: major challenges. In: Proceedings of the 25th International Conference on Software Engineering (ICSE), pp. 498–503. IEEE Computer Society, Washington (2003)CrossRefGoogle Scholar
  2. 2.
    Knauber, P., Bermejo, J., Böckle, G., do Prado Leite, J.C., van der Linden, F., Northrop, L., Stark, M., Weiss, D.M.: Quantifying product line benefits. In: van der Linden, F.J. (ed.) PFE 2002. LNCS, vol. 2290, pp. 155–163. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  3. 3.
    Schmid, K.: A comprehensive product line scoping approach and its validation. In: ICSE 2002: Proc. of the 24th International Conference on Software Engineering, pp. 593–603. ACM Press, New York (2002)CrossRefGoogle Scholar
  4. 4.
    Thiel, S., Hein, A.: Modeling and using product line variability in automotive systems. IEEE Software 19(4), 66–72 (2002)CrossRefGoogle Scholar
  5. 5.
    Wirsing, M. (ed.): Report on the EU/NSF Strategic Workshop on Engineering Software-Intensive Systems, Edinburgh, GB (2004)Google Scholar
  6. 6.
    Sztipanovits, J., Karsai, G., Bapty, T.: Self-adaptive software for signal processing. Commun. ACM 41(5), 66–73 (1998)CrossRefGoogle Scholar
  7. 7.
    Giese, H., Tichy, M., Schilling, D.: Compositional Hazard Analysis of UML Components and Deployment Models. In: Heisel, M., Liggesmeyer, P., Wittmann, S. (eds.) SAFECOMP 2004. LNCS, vol. 3219. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  8. 8.
    Giese, H., Tichy, M., Burmester, S., Schäfer, W., Flake, S.: Towards the Compositional Verification of Real-Time UML Designs. In: Proc. of the 9th European software engineering conference held jointly with 11th ACM SIGSOFT international symposium on Foundations of software engineering (ESEC/FSE-11), pp. 38–47. ACM Press, New York (2003)CrossRefGoogle Scholar
  9. 9.
    McDermid, J.A.: Trends in Systems Safety: A European View? In: Lindsay, P. (ed.) Seventh Australian Workshop on Industrial Experience with Safety Critical Systems and Software, Adelaide, Australia. Conferences in Research and Practice in Information Technology, vol. 15, pp. 3–8. ACS (2003)Google Scholar
  10. 10.
    Papadopoulos, Y., McDermid, J., Sasse, R., Heiner, G.: Analysis and synthesis of the behaviour of complex programmable electronic systems in conditions of failure. Reliability Engineering & System Safety 71, 229–247 (2001)CrossRefGoogle Scholar
  11. 11.
    Kaiser, B., Liggesmeyer, P., Maeckel, O.: A New Component Concept for Fault Trees. In: Proceedings of the 8th National Workshop on Safety Critical Systems and Software (SCS 2003), Canberra, Australia, October 9-10, 2003. Research and Practice in Information Technology, vol. 33 (2003)Google Scholar
  12. 12.
    Grunske, L., Neumann, R.: Quality Improvement by Integrating Non-Functional Properties in Software Architecture Specification. In: Proc. of the Second Workshop on Evaluating and Architecting System dependabilitY (EASY), San Jose, California, USA, October 6, 2002 (2002)Google Scholar
  13. 13.
    Grunske, L.: Transformational Patterns for the Improvement of Safety. In: Proc. of the The Second Nordic Conference on Pattern Languages of Programs (VikingPLoP 2003). Microsoft Buisness Press (2003)Google Scholar
  14. 14.
    Fenelon, P., McDermid, J.A., Nicolson, M., Pumfrey, D.J.: Towards integrated safety analysis and design. ACM SIGAPP Applied Computing Review 2(1), 21–32 (1994)CrossRefGoogle Scholar
  15. 15.
    McDermid, J., Pumfrey, D.: A Development of Hazard Analysis to aid Software Design. In: Reggio, G., Astesiano, E., Tarlecki, A. (eds.) Abstract Data Types 1994 and COMPASS 1994. LNCS, vol. 906, pp. 17–25. Springer, Heidelberg (1995)Google Scholar
  16. 16.
    Ogata, K.: Modern control engineering. Prentice Hall, Englewood Cliffs (1990)zbMATHGoogle Scholar
  17. 17.
    Selic, B., Gullekson, G., Ward, P.: Real-Time Object-Oriented Modeling. John Wiley and Sons, Chichester (1994)zbMATHGoogle Scholar
  18. 18.
    Addouche, N., Antoine, C., Montmain, J.: Combining Extended UML Models and Formal Methods to Analyze Real-Time Systems. In: Winther, R., Gran, B.A., Dahll, G. (eds.) SAFECOMP 2005. LNCS, vol. 3688, pp. 24–36. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  19. 19.
    Ortmeier, F., Thums, A., Schellhorn, G., Reif, W.: Combining Formal Methods and Safety Analysis - The ForMoSa Approach. In: Ehrig, H., Damm, W., Desel, J., Große-Rhode, M., Reif, W., Schnieder, E., Westkämper, E. (eds.) INT 2004. LNCS, vol. 3147, pp. 474–493. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  20. 20.
    Giese, H., Burmester, S., Klein, F., Schilling, D., Tichy, M.: Multi-Agent System Design for Safety-Critical Self-Optimizing Mechatronic Systems with UML. In: Henderson-Sellers, B., Debenham, J. (eds.) OOPSLA 2003 - Second International Workshop on Agent-Oriented Methodologies, Anaheim, CA, USA, Center for Object Technology Applications and Research (COTAR), University of Technology, Sydney, Australia, pp. 21–32 (2003)Google Scholar
  21. 21.
    Rauzy, A.: A new methodology to handle Boolean models with loops. IEEE Transactions on Reliability 52, 96–105 (2003)CrossRefGoogle Scholar
  22. 22.
    Bryant, R.E.: Symbolic Boolean manipulation with ordered binary-decision diagrams. ACM Computing Surveys 24(3), 293–318 (1992)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Holger Giese
    • 1
  • Matthias Tichy
    • 1
  1. 1.Software Engineering GroupUniversity of PaderbornPaderbornGermany

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