Mapping state diagram to petri net : An approach to use markov theory for analyzing non-functional parameters

Abstract

The quality of an architectural design of a software system has a great influence on achieving nonfunctional requirements to the system. Unified Modeling Language (UML), which is the industry standard as a common object oriented modeling language needs a well-defined semantic base for its notation. Integrating formal methods Petri nets (PNs) with object oriented design concepts UML is useful to benefit from the strengths of both approaches. Formalization of the graphical notation enables automated processing and analysis tasks. In this paper we use a method to converting State Diagram to Generalized Stochastic Petri Net (GSPN) and then we derive the embedded Continues Time Markov Chain from the GSPN and finally we use Markov Chain theory to obtain performance parameters. © 2007 Springer.