546 research outputs found
Petri Games: Synthesis of Distributed Systems with Causal Memory
We present a new multiplayer game model for the interaction and the flow of
information in a distributed system. The players are tokens on a Petri net. As
long as the players move in independent parts of the net, they do not know of
each other; when they synchronize at a joint transition, each player gets
informed of the causal history of the other player. We show that for Petri
games with a single environment player and an arbitrary bounded number of
system players, deciding the existence of a safety strategy for the system
players is EXPTIME-complete.Comment: In Proceedings GandALF 2014, arXiv:1408.556
Unfolding-based Partial Order Reduction
Partial order reduction (POR) and net unfoldings are two alternative methods
to tackle state-space explosion caused by concurrency. In this paper, we
propose the combination of both approaches in an effort to combine their
strengths. We first define, for an abstract execution model, unfolding
semantics parameterized over an arbitrary independence relation. Based on it,
our main contribution is a novel stateless POR algorithm that explores at most
one execution per Mazurkiewicz trace, and in general, can explore exponentially
fewer, thus achieving a form of super-optimality. Furthermore, our
unfolding-based POR copes with non-terminating executions and incorporates
state-caching. Over benchmarks with busy-waits, among others, our experiments
show a dramatic reduction in the number of executions when compared to a
state-of-the-art DPOR.Comment: Long version of a paper with the same title appeared on the
proceedings of CONCUR 201
Abstract Interpretation with Unfoldings
We present and evaluate a technique for computing path-sensitive interference
conditions during abstract interpretation of concurrent programs. In lieu of
fixed point computation, we use prime event structures to compactly represent
causal dependence and interference between sequences of transformers. Our main
contribution is an unfolding algorithm that uses a new notion of independence
to avoid redundant transformer application, thread-local fixed points to reduce
the size of the unfolding, and a novel cutoff criterion based on subsumption to
guarantee termination of the analysis. Our experiments show that the abstract
unfolding produces an order of magnitude fewer false alarms than a mature
abstract interpreter, while being several orders of magnitude faster than
solver-based tools that have the same precision.Comment: Extended version of the paper (with the same title and authors) to
appear at CAV 201
APQL: A process-model query language
As business process management technology matures, organisations acquire more and more business process models. The management of the resulting collections of process models poses real challenges. One of these challenges concerns model retrieval where support should be provided for the formulation and efficient execution of business process model queries. As queries based on only structural information cannot deal with all querying requirements in practice, there should be support for queries that require knowledge of process model semantics. In this paper we formally define a process model query language that is based on semantic relationships between tasks in process models and is independent of any particular process modelling notation
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