%L eprints2601
%A Mirco Tribastone
%A Stephen Gilmore
%A Jane Hillston
%V 38
%N 1
%D 2012
%I IEEE Computer Society
%K Markov processes; Modeling and prediction; ordinary differential equations

%R 10.1109/TSE.2010.82
%P 205-219
%X 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.
%J IEEE Transactions on Software Engineering
%T Scalable differential analysis of process algebra models