Fundamental Approaches to Software Engineering

Volume 6013 of the series Lecture Notes in Computer Science pp 154-157

Stochastic Simulation of Graph Transformation Systems

  • Paolo TorriniAffiliated withDepartment of Computer Science, University of Leicester
  • , Reiko HeckelAffiliated withDepartment of Computer Science, University of Leicester
  • , István RáthAffiliated withDepartment of Measurement and Information Systems, Budapest University of Technology and Economics


Stochastic graph transformation systems (SGTS) [1] support integrated modelling of architectural reconfiguration and non-functional aspects such as performance and reliability. In its simplest form a SGTS is a graph transformation system (GTS) where each rule name is associated with a rate of an exponential distribution governing the delay of its application. However, this approach has its limitations. Model checking with explicit states does not scale well to models with large state space. Since performance and reliability properties often depend on the behaviour of large populations of entities (network nodes, processes, services, etc.), this limitation is significant. Also, exponential distributions do not always provide the best abstraction. For example, the time it takes to make a phone call or transmit a message is more likely to follow a normal distribution.