Refinement sensitive formal semantics of state machines with persistent choice
File(s)refinement-state-machines.pdf (329.11 KB)
Accepted version
Author(s)
Fecher, H
Huth, M
Schmidt, H
Schoenborn, J
Type
Journal Article
Abstract
Modeling languages usually support two kinds of nondeterminism, an external one for interactions of a system with its environment, and one that stems from under-specification as familiar in models of behavioral requirements. Both forms of nondeterminism are resolvable by composing a system with an environment model and by refining under-specified behavior (respectively). Modeling languages usually donÆt support nondeterminism that is persistent in that neither the composition with an environment nor refinements of under-specification will resolve it. Persistent nondeterminism is used, e.g., for modeling faulty systems. We present a formal semantics for UML state machines enriched with an operator ôpersistent choiceö that models persistent nondeterminism. This semantics is based on abstract models (mu-automata with a novel refinement relation) and a sound three-valued satisfaction relation for properties expressed in the mu-calculus.\r\n
Date Issued
2008
Citation
Electronic Notes in Theoretical Computer Science, 2008, 250 (1), pp.71-86
ISSN
1571-0661
Publisher
Elsevier
Start Page
71
End Page
86
Journal / Book Title
Electronic Notes in Theoretical Computer Science
Volume
250
Issue
1
Copyright Statement
© 2009 Elsevier B.V. All rights reserved. NOTICE: this is the author’s version of a work that was accepted for publication in Electronic Notes in Theoretical Computer Science. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in ELECTRONIC NOTES IN THEORETICAL COMPUTER SCIENCE, VOL:250, ISSUE:1, (2009) DOI:10.1016/j.entcs.2009.08.006
Source Volume Number
250
Coverage Spatial
Oxford, UK