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The PEPA Eclipse Plug-in supports the creation and analysis of performance models, from small-scale Markov models to large-scale simulation studies and differential equation systems. Whichever form of analysis is used, models are expressed in a single highlevel language for quantitative modelling, Performance Evaluation Process Algebra (PEPA).
We present an application of partial evaluation to performance models expressed in the PEPA stochastic process algebra [1]. We partially evaluate the state-space of a PEPA model in order to remove uses of the cooperation and hiding operators and compile an arbitrary sub-model into a single sequential component. This transformation is applied to PEPA models(More)
Starting from a biochemical signalling pathway model expressed in a process algebra enriched with quantitative information we automatically derive both continuous-space and discrete-state representations suitable for numerical evaluation. We compare results obtained using implicit numerical differentiation formulae to those obtained using approximate(More)
Bio-PEPA [1, 2] is a timed process algebra designed specifically for the description of biological phenomena and their analysis through quantitative methods such as stochastic simulation and probabilistic model-checking. The context of application we consider is that of biochemical networks. A biochemical network is composed of n species which interact(More)
The Performance Evaluation Process Algebra (PEPA) language is a stochastic process algebra, generating Continuous Time Markov Chains (CTMC) to allow quantitative analysis. Protocols such as BitTorrent are highly parallel in nature, and represent one area where CTMC analysis is limited by the well-known state space problem. The number of unique states each(More)
The vast majority of biochemical systems involve the exchange of information between different compartments, either in the form of transportation or via the intervention of membrane proteins which are able to transmit stimuli between bordering compartments. The correct quantitative handling of compartments is, therefore, extremely important when modelling(More)
This paper surveys the design of software tools for the Bio-PEPA process algebra. Bio-PEPA is a high-level language for modelling biological systems such as metabolic pathways and other biochemical reaction networks. Through providing tools for this modelling language we hope to allow easier use of a range of simulators and model-checkers thereby freeing(More)
Passage-end calculations are a new style of passage measurement for eXtended Stochastic Probes (XSP) [1] which add the ability to split the analysis into several cases depending on conditions which hold at the end of a passage. This makes it possible to separate successful responses to a request from negative responses, timeouts or other failures. This(More)
view Stochastic Simulation individual view Abstract Bio-PEPA model Fig. 1. Alternative modelling approaches: a single Bio-PEPA description of a system may be used to derive alternative mathematical representations o ering di erent analysis possibilities In contrast, biologists often take a population-based view of cellular systems, representing them as(More)