Skip to main content

The Dynamic Fault Tree Rare Event Simulator

  • Conference paper
  • First Online:
Quantitative Evaluation of Systems (QEST 2020)

Abstract

The dynamic-fault-tree rare event simulator, DFTRES, is a statistical model checker for dynamic fault trees (DFTs), supporting the analysis of highly dependable systems, e.g. with unavailability or unreliability under \(10^{-30}\). To efficiently estimate such low probabilities, we apply the Path-ZVA algorithm to implement Importance Sampling with minimal user input. Calculation speed is further improved by selective automata composition and bisimulation reduction. DFTRES reads DFTs in the Galileo or JANI textual formats. The tool is written in Java 11 with multi-platform support, and it is released under the GPLv3. In this paper we describe the architecture, setup, and input language of DFTRES, and showcase its accurate estimation of dependability metrics of (resilient) repairable DFTs from the FFORT benchmark suite.

This work was partially funded by NWO project 15474 (SEQUOIA).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Change history

  • 18 December 2020

    In the original version of this chapter Reference 5 was published incorrectly. Reference 5 has now been corrected.

Notes

  1. 1.

    Available at https://github.com/utwente-fmt/DFTRES.

  2. 2.

    While every effort is made to provide accurate confidence intervals, their coverage can fall considerably below 95% due to the extreme probability distributions involved [8].

References

  1. Arnold, F., Belinfante, A., Van der Berg, F., Guck, D., Stoelinga, M.: DFTCalc: a tool for efficient fault tree analysis. In: Bitsch, F., Guiochet, J., Kaâniche, M. (eds.) SAFECOMP 2013. LNCS, vol. 8153, pp. 293–301. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40793-2_27

    Chapter  Google Scholar 

  2. Budde, C.E.: FIG: the finite improbability generator. TACAS 2020. LNCS, vol. 12078, pp. 483–491. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-45190-5_27

    Chapter  Google Scholar 

  3. Budde, C.E., D’Argenio, P.R., Hartmanns, A., Sedwards, S.: An efficient statistical model checker for nondeterminism and rare events. Int. J. Softw. Tools Technol. Transf. 1–22 (2020). https://doi.org/10.1007/s10009-020-00563-2

  4. Budde, C.E., Dehnert, C., Hahn, E.M., Hartmanns, A., Junges, S., Turrini, A.: JANI: quantitative model and tool interaction. In: Legay, A., Margaria, T. (eds.) TACAS 2017. LNCS, vol. 10206, pp. 151–168. Springer, Heidelberg (2017). https://doi.org/10.1007/978-3-662-54580-5_9

    Chapter  Google Scholar 

  5. Budde, C.E., Ruijters, E., Stoelinga, M.: The dynamic fault tree rare event simulator: experimental replication package (2020). https://figshare.com/articles/software/The_Dynamic_Fault_Tree_Rare_Event_Simulator/12235889, https://doi.org/10.6084/m9.figshare.12235889.v2

  6. Dugan, J., Boyd, S.B.M.: Fault trees and sequence dependencies. In: Annual Proceedings on Reliability and Maintainability Symposium, pp. 286–293 (1990). https://doi.org/10.1109/ARMS.1990.67971

  7. Feldman, S.I.: Make - a program for maintaining computer programs. Softw. Pract. Exp. 9(4), 255–265 (1979). https://doi.org/10.1002/spe.4380090402

    Article  MATH  Google Scholar 

  8. Glynn, P.W., Rubino, G., Tuffin, B.: Robustness properties and confidence interval reliability issues. In: Rubino and Tuffin [16], pp. 63–84. https://doi.org/10.1002/9780470745403.ch4

  9. Hartmanns, A., et al.: The 2019 comparison of tools for the analysis of quantitative formal models. In: TACAS. LNCS, vol. 11429, pp. 69-92. Springer (2019). https://doi.org/10.1007/978-3-030-17502-3_5

  10. Heidelberger, P.: Fast simulation of rare events in queueing and reliability models. ACM Trans. Model. Comput. Simul. 5(1), 43–85 (1995). https://doi.org/10.1145/203091.203094

    Article  MATH  Google Scholar 

  11. Hensel, C., Junges, S., Katoen, J.P., Quatmann, T., Volk, M.: The probabilistic model checker storm. arXiv e-prints arXiv:2002.07080 (2020). https://arxiv.org/abs/2002.07080

  12. Jégourel, C., Legay, A., Sedwards, S.: Command-based importance sampling for statistical model checking. Theor. Comput. Sci. 649, 1–24 (2016). https://doi.org/10.1016/j.tcs.2016.08.009

    Article  MathSciNet  MATH  Google Scholar 

  13. Nicola, V.F., Shahabuddin, P., Nakayama, M.: Techniques for fast simulation of models of highly dependable systems. IEEE Trans. Reliab. 50(3), 246–264 (2001). https://doi.org/10.1109/24.974122

    Article  Google Scholar 

  14. Reijsbergen, D., de Boer, P.T., Scheinhardt, W., Juneja, S.: Path-ZVA: general, efficient and automated importance sampling for highly reliable Markovian systems. ACM TOMACS 28(3), 22:1–22:25 (2018). https://doi.org/10.1145/3161569

  15. Rubino, G., Tuffin, B.: Introduction to rare event simulation. In: Rubino and Tuffin [16], pp. 1–13. https://doi.org/10.1002/9780470745403.ch1

  16. Rubino, G., Tuffin, B. (eds.): Rare Event Simulation Using Monte Carlo Methods. Wiley, Hoboken (2009). https://doi.org/10.1002/9780470745403

  17. Ruijters, E., et al.: FFORT: a benchmark suite for fault tree analysis. In: ESREL, pp. 878–885 (2019). https://doi.org/10.3850/978-981-11-2724-3_0641-cd

  18. Ruijters, E., Reijsbergen, D., de Boer, P.T., Stoelinga, M.: Rare event simulation for dynamic fault trees. Reliab. Eng. Syst. Safety 186, 220–231 (2019). https://doi.org/10.1016/j.ress.2019.02.004

    Article  Google Scholar 

  19. Ruijters, E., Stoelinga, M.: Fault tree analysis: a survey of the state-of-the-art in modeling, analysis and tools. Comput. Sci. Rev. 15–16, 29–62 (2015). https://doi.org/10.1016/j.cosrev.2015.03.001

    Article  MathSciNet  MATH  Google Scholar 

  20. Sullivan, K.J., Dugan, J.B.: Galileo user’s manual & design overview, v2.1-alpha (1998). www.cse.msu.edu/~cse870/Materials/FaultTolerant/manual-galileo.htm

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Carlos E. Budde .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Budde, C.E., Ruijters, E., Stoelinga, M. (2020). The Dynamic Fault Tree Rare Event Simulator. In: Gribaudo, M., Jansen, D.N., Remke, A. (eds) Quantitative Evaluation of Systems. QEST 2020. Lecture Notes in Computer Science(), vol 12289. Springer, Cham. https://doi.org/10.1007/978-3-030-59854-9_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-59854-9_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59853-2

  • Online ISBN: 978-3-030-59854-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics