Abstract

State diagrams are simple diagrams that are used to define the structure and behavior of
discrete reactive systems in a visual and intuitive manner. In computer science, the most
commonly used variants are statecharts, an extension of state diagrams using concurrent
subsystems to model parallel execution.
This thesis elaborates the use of the probabilistic extension of statecharts, the P-statecharts,
to support modeling of randomness in the system and in the system environment. The focus is on the development environment, able to edit, execute, simulate and especially test
P-statecharts.
To facilitate productive development and use of P-statecharts, an extension using pseudonodes is presented. For this extension, the fundamentals of execution and simulation of
P-statecharts are laid out in detail, including granular single step execution and analysis
using Monte-Carlo simulations.
A development environment for P-statecharts has been developed which is also described in this thesis. It includes an editor for P-statecharts and two ways to simulate
them: either step by step or in the form of Monte Carlo simulations.
In conclusion, P-statecharts become a very powerful modeling tool when supported by
an appropriate development environment including visual editor, debugger and simulation.

Keywords: State Diagrams, UML-statecharts, probabilistic, P-statecharts, pseudo-nodes,
debugging, Monte Carlo method

Results/Implementation/Project Description (coming soon)

Conclusion (coming soon)

Thesis pdf:

Final presentation: