Stochastic Simulation of Graph Transformation Systems
- Cite this paper as:
- Torrini P., Heckel R., Ráth I. (2010) Stochastic Simulation of Graph Transformation Systems. In: Rosenblum D.S., Taentzer G. (eds) Fundamental Approaches to Software Engineering. FASE 2010. Lecture Notes in Computer Science, vol 6013. Springer, Berlin, Heidelberg
Stochastic graph transformation systems (SGTS)  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.