Stochastic process algebra based software process simulation modeling

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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. © Springer-Verlag Berlin Heidelberg 2009.

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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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5543 LNCS, pp. 136–147). https://doi.org/10.1007/978-3-642-01680-6_14

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