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Formal Aspects of Computing
Article . 1995 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
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zbMATH Open
Article . 1995
Data sources: zbMATH Open
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Article . 2022
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Interpreting Message Flow Graphs

Interpreting message flow graphs
Authors: Ladkin, Peter B.; Leue, Stefan;

Interpreting Message Flow Graphs

Abstract

Abstract We give a semantics for Message Flow Graphs (MFGs), which play the role for interprocess communication that Program Dependence Graphs play for control flow in parallel processes. MFGs have been used to analyse parallel code, and are closely related to Message Sequence Charts and Time Sequence Diagrams in telecommunications systems. Our requirements are firstly, to determine unambiguously exactly what execution traces are specified by an MFG, and secondly, to use a finite-state interpretation. Our methods function for both asynchronous and synchronous communications. From a set of MFGs, we define a transition system of global states, and from that a Büchi automaton by considering safety and liveness properties of the system. In order easily to describe liveness properties, we interpret the traces of the transition system as a model of Manna-Pnueli temporal logic. Finally, we describe the expressive power of MFGs by mimicking an arbitrary Büchi automaton by means of a set of MFGs.

Country
Germany
Related Organizations
Keywords

message flow graphs, Semantics in the theory of computing, Büchi automaton, Formal languages and automata, info:eu-repo/classification/ddc/004

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
52
Average
Top 1%
Top 10%
Green
bronze