A tool for the numerical solution of cooperating Markov chains in product-form

Performance modelling of complex and heterogeneous systems based on analytical models are often solved by the analysis of underlying Markovian models. We consider performance models based on Continuous Time Markov Chains (CTMCs) and their solution, that is the analysis of the steady-state distribution, to efficiently derive a set of performance indices. This paper presents a tool that is able to decide whether a set of cooperating CTMCs yields a product-form stationary distribution. In this case, the tool computes the unnormalised steadystate distribution. The algorithm underlying the tool has been presented in [10] by exploiting the recent advances in the theory of product-form models such as the Reversed Compound Agent Theorem (RCAT) [5]. In this paper, we focus on the peculiarities of the formalism adopted to describe the interacting CTMCs and on the software design that may have interesting consequences for the performance community.