@article{eprints2601,
           title = {Scalable differential analysis of process algebra models},
            year = {2012},
          volume = {38},
           month = {January},
          number = {1},
           pages = {205--219},
       publisher = {IEEE Computer Society},
         journal = {IEEE Transactions on Software Engineering},
          author = {Mirco Tribastone and Stephen Gilmore and Jane Hillston},
        keywords = {Markov processes; Modeling and prediction; ordinary differential equations
},
             url = {http://eprints.imtlucca.it/2601/},
        abstract = {The exact performance analysis of large-scale software systems with discrete-state approaches is difficult because of the well-known problem of state-space explosion. This paper considers this problem with regard to the stochastic process algebra PEPA, presenting a deterministic approximation to the underlying Markov chain model based on ordinary differential equations. The accuracy of the approximation is assessed by means of a substantial case study of a distributed multithreaded application.}
}