  We propose communication pattern logic. A communication pattern describes how
processes or agents inform each other, independently of the information
content. The full-information protocol in distributed computing is the special
case wherein all agents inform each other. We study this protocol in
distributed computing models where communication might fail: an agent is
certain about the messages it receives, but it may be uncertain about the
messages other agents have received. In a dynamic epistemic logic with
distributed knowledge and with modalities for communication patterns, the
latter are interpreted by updating Kripke models. We propose an axiomatization
of communication pattern logic, and we show that collective bisimilarity
(comparing models on their distributed knowledge) is preserved when updating
models with communication patterns. We can also interpret communication
patterns by updating simplicial complexes, a well-known topological framework
for distributed computing. We show that the different semantics correspond, and
propose collective bisimulation between simplicial complexes.
