Abstract Relational Causal Models (RCM) generalize Causal Bayesian Networks so as to
extend causal discovery to relational domains. We provide a novel and elegant …

As usual, the SIGOPS workshop provided a great platform for interesting discussion. Among
other things, a controversy arose around the usefulness of causal ordering in a distributed …

Cause-effect graphs are often used as a method for deriving test case suites for black-box
testing different types of systems. This paper represents a survey focusing entirely on the …

Many distributed algorithms require knowledge of the causal relationships between events.
Examples include optimistic recovery protocols, distributed debugging systems, and causal …

Automatic Generation of DistAlgo Programs from Event-B Models | SpringerLink Skip to main
content Advertisement SpringerLink Account Menu Find a journal Publish with us Track your …

Relational order structures are used to describe and investigate properties of concurrent
systems. To reduce the complexity of order structures, one typically considers only their …

Causal discovery plays a vital role in the human understanding of the world. Searching a
directed acyclic graph (DAG) from observed data is one of the most widely used methods …

/spl Delta/-causal ordering is a communication abstraction designed for distributed
applications whose messages (i) have to be delivered according to causal ordering and (ii) …

Today's fault management requires a sophisticated event management to condense events
to meaningful fault reports. This severe practical need is addressed by event correlation …

Rapide: A Language and Toolset for Simulation of Distributed Systems by Partial Orderings of
Events Page 1 Rapide: A Language and Toolset for Simulation of Distributed Systems by …