Test case generation using stochastic automata networks: quantitative analysis

Abstract

The software engineering community has been using Markov Chains (MC) to describe usage models. We have been working on the use of a more sophisticated discrete state formalism: Stochastic Automata Networks (SAN). SAN is a formalism with the same power of description as MC, however a system in SAN is described as a collection of subsystems described by local states, transitions and synchronizing events, allowing higher modularity and maintainability. We present a description of SAN formalism, as well as quantitative analysis of the modeling examples considering the generation time, quality of the test suites.