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Evaluation of Standard Reliability Growth Models in the Context of Automotive Software Systems

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Product-Focused Software Process Improvement (PROFES 2013)


Reliability and dependability of software in modern cars is of utmost importance. Predicting these properties for software under development is therefore important for modern car OEMs, and using reliability growth models (e.g. Rayleigh, Goel-Okumoto) is one approach. In this paper we evaluate a number of standard reliability growth models on a real software system from automotive industry. The results of the evaluation show that models can be fitted well with defect inflow data, but certain parameters need to be adjusted manually in order to predict reliability more precisely in the late test phases. In this paper we provide recommendations for how to adjust the models and how the adjustments should be used in the development process of software in the automotive domain by investigating data from an industrial project.

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  1. Liggesmeyer, P., Trapp, M.: Trends in embedded software engineering. IEEE Software 26, 19–25 (2009)

    Article  Google Scholar 

  2. Broy, M.: Challenges in automotive software engineering. In: Proceedings of the 28th International Conference on Software Engineering, pp. 33–42 (2006)

    Google Scholar 

  3. Grimm, K.: Software technology in an automotive company: major challenges. In: Proceedings of the 25th International Conference on Software Engineering, pp. 498–503 (2003)

    Google Scholar 

  4. ISO 26262:2011 Road vehicles - Functional safety (2011)

    Google Scholar 

  5. Stringfellow, C., Andrews, A.A.: An empirical method for selecting software reliability growth models. Empirical Software Engineering 7, 319–343 (2002)

    Article  MATH  Google Scholar 

  6. Lyu, M.R.: Software reliability engineering: A roadmap. In: Future of Software Engineering, FOSE 2007, pp. 153–170 (2007)

    Google Scholar 

  7. Ullah, N., Morisio, M., Vetro, A.: A Comparative Analysis of Software Reliability Growth Models using Defects Data of Closed and Open Source Software. In: 2012 35th Annual IEEE Software Engineering Workshop (SEW), pp. 187–192 (2012)

    Google Scholar 

  8. Wood, A.: Predicting software reliability. Computer 29, 69–77 (1996)

    Article  Google Scholar 

  9. Staron, M., Meding, W.: Predicting weekly defect inflow in large software projects based on project planning and test status. Information and Software Technology 50, 782–796 (2008)

    Article  Google Scholar 

  10. Pham, H.: Software reliability and cost models: Perspectives, comparison, and practice. European Journal of Operational Research 149, 475–489 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  11. Mellegård, N., Staron, M., Törner, F.: A light-weight defect classification scheme for embedded automotive software and its initial evaluation (2012)

    Google Scholar 

  12. Goel, A.L., Okumoto, K.: Time-dependent error-detection rate model for software reliability and other performance measures. IEEE Transactions on Reliability 28, 206–211 (1979)

    Article  MATH  Google Scholar 

  13. Yamada, S., Ohba, M., Osaki, S.: S-shaped reliability growth modeling for software error detection. IEEE Transactions on Reliability 32, 475–484 (1983)

    Article  Google Scholar 

  14. Kan, S.H., et al.: Metrics and Models in Software Quality Engineering, 2nd edn. Pearson Education India (2003)

    Google Scholar 

  15. Yamada, S., Tokuno, K., Osaki, S.: Imperfect debugging models with fault introduction rate for software reliability assessment. International Journal of Systems Science 23, 2241–2252 (1992)

    Article  MATH  Google Scholar 

  16. Taghi, M.K., Edward, B.A.: Logistic regression modeling of software quality. International Journal of Reliability, Quality and Safety Engineering 6, 303–317 (1999)

    Article  Google Scholar 

  17. Ohishi, K., Okamura, H., Dohi, T.: Gompertz software reliability model: Estimation algorithm and empirical validation. Journal of Systems and Software 82, 535–543 (2009)

    Article  Google Scholar 

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Rana, R. et al. (2013). Evaluation of Standard Reliability Growth Models in the Context of Automotive Software Systems. In: Heidrich, J., Oivo, M., Jedlitschka, A., Baldassarre, M.T. (eds) Product-Focused Software Process Improvement. PROFES 2013. Lecture Notes in Computer Science, vol 7983. Springer, Berlin, Heidelberg.

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39258-0

  • Online ISBN: 978-3-642-39259-7

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