Abstract
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.
Supported by the National Natural Science Foundation of China under grant Nos. 90718042, the Hi-Tech Research and Development Program (863 Program) of China under grant No.2007AA010303, 2007AA01Z186, as well as the National Basic Research Program (973 program) under grant No. 2007CB310802.
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References
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)
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)
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)
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)
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)
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)
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)
Milner, R., Parrow, J., Walker, D.: A calculus of mobile processes – part I and II. Journal of Information and Computation 100, 1–77 (1992)
Herzog, U.: Formal description, time and performance analysis: A framework. Technical Report 15/90, IMMD VII, Friedrich-Alexander-Universität (1990)
Milner, R.: A Calculus of Communicating Systems. Springer, Heidelberg (1980)
Hoare, C.A.R.: Communicating sequential processes. Commun. ACM 21(8), 666–677 (1978)
Lecca, P., Priami, C.: Cell cycle control in eukaryotes: A biospi model. Electron. Notes Theor. Comput. Sci. 180(3), 51–63 (2007)
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)
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)
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)
Abdel-Hamid, T., Madnick, S.E.: Software project dynamics: an integrated approach. Prentice-Hall, Inc., Upper Saddle River (1991)
Pfahl, D., Ruhe, G.: Immos. a methodology for integrated measurement, modelling, and simulation (2003)
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)
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)
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)
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)
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Zhai, J., Yang, Q., Su, F., Xiao, J., Wang, Q., Li, M. (2009). Stochastic Process Algebra Based Software Process Simulation Modeling. In: Wang, Q., Garousi, V., Madachy, R., Pfahl, D. (eds) Trustworthy Software Development Processes. ICSP 2009. Lecture Notes in Computer Science, vol 5543. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01680-6_14
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DOI: https://doi.org/10.1007/978-3-642-01680-6_14
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