Stochastic Process Algebra Based Software Process Simulation Modeling

  • Jian Zhai
  • Qiusong Yang
  • Feng Su
  • Junchao Xiao
  • Qing Wang
  • Mingshu Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5543)


In recent years, simulation techniques that have been widely used in many other disciplines are being increasingly used in analyzing software processes. However, researchers from software process simulation community tend to build a separate new model with various technologies from traditional software models. This is partially because that software process simulation might take a completely different approach to describe a process under certain circumstances, for instance, a process being modeled as an overall system. Another reason is that traditional software process modeling methods can not provide simulation functions. The gap between traditional software process modeling and software process simulation modeling confined a wider application of simulation approach in the software engineering community. In this paper, we show the possibility of a simulation model being automatically derived from a traditional descriptive process model and thus one does not necessarily need to build a separate simulation model. By doing so, all information in the descriptive models can be reused.


Software Process Mapping Rule Gantt Chart Software Project Management Terminal Activity 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Lonchamp, J.: A structured conceptual and terminological framework for software process engineering. In: Proceedings of the Second International Conference on the Software Process, pp. 41–53. IEEE Computer Society Press, Los Alamitos (1993)Google Scholar
  2. 2.
    Conradi, R., Jaccheri, M.L.: Process modelling languages. In: Derniame, J.C., Kaba, B.A., Wastell, D.G. (eds.) Promoter-2 1998. LNCS, vol. 1500, pp. 27–52. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  3. 3.
    Zamli, K.Z., Lee, P.A.: Taxonomy of process modeling languages. In: AICCSA 2001: Proceedings of the ACS/IEEE International Conference on Computer Systems and Applications, Washington, DC, USA, p. 435. IEEE Computer Society Press, Los Alamitos (2001)Google Scholar
  4. 4.
    Arbaoui, S., Derniame, J.-C., Oquendo, F., Verjus, H.: A comparative review of process-centered software engineering environments. Ann. Softw. Eng. 14(1-4), 311–340 (2002)CrossRefzbMATHGoogle Scholar
  5. 5.
    Kellner, M.I., Madachy, R.J., Raffo, D.M.: Software process simulation modeling: Why? what? how? Journal of Systems and Software 46(2), 91–105 (1999)CrossRefGoogle Scholar
  6. 6.
    Zhang, H., Kitchenham, B.A., Pfahl, D.: Reflections on 10 years of software process simulation modeling: A systematic review. In: Wang, Q., Pfahl, D., Raffo, D.M. (eds.) ICSP 2008. LNCS, vol. 5007, pp. 345–356. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  7. 7.
    Yang, Q., Li, M., Wang, Q., Yang, G., Zhai, J., Li, J., Hou, L., Yang, Y.: An Algebraic Approach for Managing Inconsistencies in Software Processes. In: Wang, Q., Pfahl, D., Raffo, D.M. (eds.) ICSP 2007. LNCS, vol. 4470, pp. 121–133. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. 8.
    Milner, R., Parrow, J., Walker, D.: A calculus of mobile processes – part I and II. Journal of Information and Computation 100, 1–77 (1992)CrossRefzbMATHGoogle Scholar
  9. 9.
    Herzog, U.: Formal description, time and performance analysis: A framework. Technical Report 15/90, IMMD VII, Friedrich-Alexander-Universität (1990)Google Scholar
  10. 10.
    Milner, R.: A Calculus of Communicating Systems. Springer, Heidelberg (1980)CrossRefzbMATHGoogle Scholar
  11. 11.
    Hoare, C.A.R.: Communicating sequential processes. Commun. ACM 21(8), 666–677 (1978)CrossRefzbMATHGoogle Scholar
  12. 12.
    Lecca, P., Priami, C.: Cell cycle control in eukaryotes: A biospi model. Electron. Notes Theor. Comput. Sci. 180(3), 51–63 (2007)CrossRefGoogle Scholar
  13. 13.
    Priami, C., Regev, A., Shapiro, E., Silverman, W.: Application of a stochastic name-passing calculus to representation and simulation of molecular processes. Information Processing Letters 80(1), 25–31 (2001)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Li, M.: Expanding the horizons of software development processes: A 3-D integrated methodology. In: Li, M., Boehm, B., Osterweil, L.J. (eds.) ISPW 2005. LNCS, vol. 3840, pp. 54–67. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  15. 15.
    Clark, A., Gilmore, S., Hillston, J., Tribastone, M.: Stochastic process algebras. In: Bernardo, M., Hillston, J. (eds.) SFM 2007. LNCS, vol. 4486, pp. 132–179. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  16. 16.
    Abdel-Hamid, T., Madnick, S.E.: Software project dynamics: an integrated approach. Prentice-Hall, Inc., Upper Saddle River (1991)Google Scholar
  17. 17.
    Pfahl, D., Ruhe, G.: Immos. a methodology for integrated measurement, modelling, and simulation (2003)Google Scholar
  18. 18.
    Schriber, T.J., Brunner, D.T.: Inside discrete-event simulation software: how it works and why it matters. In: WSC 2005: Proceedings of the 37th conference on Winter simulation, Winter Simulation Conference, pp. 167–177 (2005)Google Scholar
  19. 19.
    Raffo, D.: Combining process feedback with discrete event simulation models to support. In: Software Project Management. International Software Process Simulation Modeling Workshop (ProSim 2004), pp. 24–25 (2004)Google Scholar
  20. 20.
    Choi, K., Bae, D.-H., Kim, T.: An approach to a hybrid software process simulation using the devs formalism. Software Process: Improvement and Practice 11(4), 373–383 (2006)CrossRefGoogle Scholar
  21. 21.
    Bradley, J.T., Gilmore, S.T.: Stochastic simulation methods applied to a secure electronic voting model. Electronic Notes in Theoretical Computer Science 151, 5–25 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jian Zhai
    • 1
    • 3
  • Qiusong Yang
    • 1
  • Feng Su
    • 1
    • 3
  • Junchao Xiao
    • 1
  • Qing Wang
    • 1
  • Mingshu Li
    • 1
    • 2
  1. 1.Laboratory for Internet Software Technologies, Institute of SoftwareThe Chinese Academy of SciencesBeijingChina
  2. 2.Key Laboratory for Computer ScienceThe Chinese Academy of SciencesBeijingChina
  3. 3.Graduate University of Chinese Academy of ScienceBeijingChina

Personalised recommendations