Stochastic process algebra models have been successfully used in the area of performance modelling for the last twenty years, and more recently have been adopted for modelling biochemical processes in systems biology. Most research on these modelling formalisms has been on quantitative analysis, particularly the derivation of quantified dynamic information about the system modelled in the face of the state space explosion problem. In this paper we instead consider qualitative analysis, looking at how recent developments to tackle state space explosion in quantified analysis can be also harnessed to establish properties such as freedom from deadlock in an efficient manner. © 2011 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Ding, J., & Hillston, J. (2011). Structural analysis for stochastic process algebra models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6486 LNCS, pp. 1–27). https://doi.org/10.1007/978-3-642-17796-5_1
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