Mapping Activity Diagram To Petri Net: Application Of Markov Theory For Analyzing Non-Functional Parameters

The quality of an architectural design of a software system has a great influence on achieving non-functional requirements of a system. A regular software development project is often influenced by non-functional factors such as the customers' expectations about the performance and reliability of the software as well as the reduction of underlying risks. The evaluation of nonfunctional parameters of a software system at the early stages of design and its development process are often considered as major factors in dealing with these issues. Because these evaluations can help us to choose the most proper model which is the securest and the most reliable. In this paper, a method is presented to obtain performance parameters from Generalized Stochastic Petri Net (GSPN) to be able to analyze the stochastic behavior of the system. The embedded Continuous Time Markov Chain (CTMC) is derived from the GSPN and the Markov chain theory is used to obtain the performance parameters.