Abstract
Causal trees are one of the earliest pioneering contributions of Pierpaolo Degano, in joint work with Philippe Darondeau. The idea is to record causality dependencies in processes and in their actions. As such, causal trees sit between interleaving models and truly concurrent ones and they originate an abstract, event-based bisimulation semantics for causal processes, where, intuitively, minimal causal trees represent the semantic domain. In the paper we substantiate this feeling, by first defining a nominal, compositional operational semantics based on History-Dependent automata and then we apply categorical techniques, based on named-sets, showing that causal trees form the final coalgebra semantics of a suitable coalgebraic representation of causal behaviour.
Research supported by MIUR PRIN Project CINA Prot. 2010LHT4KM and by NWO Project 612.001.113 Practical Coinduction.
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Notes
- 1.
An analogous concept of location automata was introduced in [14] for modelling the location semantics of CCS.
- 2.
As it is common in final semantics, the final coalgebra is typically an infinite object that accounts for all possible behaviours, but the minimal representative of an HD-automaton needs to account just for the behaviours of that automaton: it decomposes uniquely the map from the HD-automaton to the final object into a surjective mapping from the HD-automaton to the representative and an embedding of the latter into the final object.
- 3.
Note that inactive agents of the form \(K \mathbin {\vdash }\mathbf {0}\) are just disregarded.
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Bruni, R., Montanari, U., Sammartino, M. (2015). Causal Trees, Finally. In: Bodei, C., Ferrari, G., Priami, C. (eds) Programming Languages with Applications to Biology and Security. Lecture Notes in Computer Science(), vol 9465. Springer, Cham. https://doi.org/10.1007/978-3-319-25527-9_4
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