Cavalcanti, Ana Lucia Caneca orcid.org/0000-0002-0831-1976, Filho, Madiel Conserva, De Oliveira Salazar Ribeiro, Pedro Fernando orcid.org/0000-0003-4319-4872 et al. (1 more author) (2023) Laws of Timed State Machines. The Computer Journal. bxad124. ISSN 1460-2067
Abstract
State machines are widely used in industry and academia to capture behavioural models of control. They are included in popular notations, such as UML and its variants, and used (sometimes informally) to describe computational artefacts. In this paper, we present laws for state machines that we prove sound with respect to a process algebraic semantics for refinement, and complete, in that they are sufficient to reduce an arbitrary model to a normal form that isolates basic (action and control) elements. We consider two variants of UML-like state machines, both enriched with facilities to deal with time budgets, timeouts and deadlines over triggers and actions. In the first variant, machines are self-contained components, declaring all the variables, events and operations that they require or define. In contrast, in the second variant, machines are open, like in UML for instance. Laws for open state machines do not depend on a specific context of variables, events and operations, and normalization uses a novel operator for open-machine (de)composition. Our laws can be used in behaviour-preservation transformation techniques. Their applications are automated by a model-transformation engine.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Funding Information: | Funder Grant number EPSRC EP/R025479/1 EPSRC EP/M025756/1 |
Depositing User: | Pure (York) |
Date Deposited: | 31 Jan 2024 13:30 |
Last Modified: | 10 Dec 2024 00:22 |
Published Version: | https://doi.org/10.1093/comjnl/bxad124 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1093/comjnl/bxad124 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:208533 |