Unravel Nets. A way to represent behaviors compactly and to relate them to event structures

The present work introduces a new class of nets which aims to give a more compact non-sequential semantics to safe Petri nets, namely unravel nets. As causal nets can be a representation of runs of a safe Petri net, i.e. its unfolding, unravel nets can be regarded as a succinct version of these unfoldings. The main contributions of the thesis, beside the definition of this class of nets, are: • their close connection with a brand of event structures, namely bundle event structures, and we show that configurations of the former can be mapped into the ones of the latter and vice versa, • the encodings, in terms of unravel nets, of the existing approaches for merging unfoldings, • the definition of a general notion of merging relation which can, under certain constraints, preserve some properties of a net, in particular we introduce the notion of conflict conditions which can force a net to be an unravel one after the merging, • the addition of contextual arcs (in our approach read arcs) to unravel nets, which allow to model new kinds of causality. We consider various kind of event structure with non-standard causality, namely dynamic causality event structure, and prove that they are related to contextual unravel nets simi larly to what happens to bundle event structures and unravel nets without contexts.