On Petri-net synthesis and attribute-based visualization

State space visualization is important for a good understanding of the system’s behavior. Unfortunately, today’s visualization tools typically ignore the fact that states might have attributes. Based on these attributes, some states can be considered equivalent after abstraction, and can thus be clustered, which simplifies the state space. Attributebased visualization tools are the exception to this rule. These tools can deal with attributes. In this paper, we investigate an approach based on Petri nets. Places in a Petri net correspond in a straightforward way to attributes. Furthermore, we can use existing techniques to automatically derive a Petri net from some state space, that is, to automatically add attributes to that state space. As a result, we can use attribute-based visualization tools for any state space. Unfortunately, the approach is hampered by the fact that not every state space results in a usable Petri net.