The FTG+PM framework for multi-paradigm modelling

Mustafiz, Sadaf; Denil, Joachim; Levi, Lucio; Vangheluwe, Hans

doi:10.1145/2508443.2508446

Cited by 29 publications

(16 citation statements)

References 11 publications

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“…We have already introduced the inaccuracy construct (Section 5.2) to integrate the results of such predictions with IRM-SA. This idea aligns well with research in stochastic hybrid systems, and also complies with our vision to employ Multi-Paradigm Modeling (MPM) in siCPS [61]. MPM that will allow to work with different types of models (such as physical-world, communication, mechanical, and adaptability models) which would be integrated into a single rich software architecture model (similar to [11]).…”

Section: Discussionmentioning

confidence: 61%

Self-adaptation in software-intensive cyber–physical systems: From system goals to architecture configurations

Gerostathopoulos

Bureš

Hnětynka

et al. 2016

Journal of Systems and Software

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International audienceDesign of self-adaptive software-intensive Cyber-Physical Systems (siCPS) operating in dynamic environments is a significant challenge when a sufficient level of dependability is required. This stems partly from the fact that the concerns of self-adaptivity and dependability are to an extent contradictory. In this paper, we introduce IRM-SA (Invariant Refinement Method for Self-Adaptation) – a design method and associated formally grounded model targeting siCPS – that addresses self-adaptivity and supports dependability by providing traceability between system requirements, distinct situations in the environment, and predefined configurations of system architecture. Additionally, IRM-SA allows for architecture self-adaptation at runtime and integrates the mechanism of predictive monitoring that deals with operational uncertainty. As a proof of concept, it was implemented in DEECo, a component framework that is based on dynamic ensembles of components. Furthermore, its feasibility was evaluated in experimental settings assuming decentralized system operation

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Section: Discussionmentioning

confidence: 61%

Self-adaptation in software-intensive cyber–physical systems: From system goals to architecture configurations

Gerostathopoulos

Bureš

Hnětynka

et al. 2016

Journal of Systems and Software

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“…In [194,196,216] a Process Model (PM) language is proposed to describe the control and data flow between design activities. To this end, a subset of the Unified Modelling Language (UML) 2.0 activity diagrams are used.…”

Section: Reasoning About Maturitymentioning

confidence: 99%

“…Finally, the join and fork Activity Diagram flow constructs, represented in Figure 9.4 as horizontal bars, allow one to represent concurrent design activities. Corresponding to mega-model principles [19,31,142], the Formalism Transformation Graph (FTG) [194,196,216] is a language that allows one to declare those formalisms and transformations. It models the relations between the different languages using transformations.…”

Section: Control Flowmentioning

confidence: 99%

Foundations of Multi-Paradigm Modelling for Cyber-Physical Systems

Broenink¹

2020

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“…We will go through the different simulation models created for the power window during the deployment process. More information about the design process of the power window can be found in Mustafiz et al 38…”

Section: The Window Must Start Moving Within 200 Ms Aftermentioning

confidence: 99%

DEVS for AUTOSAR-based system deployment modeling and simulation

et al. 2017

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AUTOSAR (AUTomotive Open System ARchitecture) is an open and standardized automotive software architecture, developed by automobile manufacturers, suppliers, and tool developers. Its design is a direct consequence of the increasingly important role played by software in vehicles. As design choices during the software deployment phase have a large impact on the behavior of the system, designers need to explore various trade-offs. Examples of such design choices are the mapping of software components to processors, the priorities of tasks and messages, and buffer allocation. In this paper, we evaluate the appropriateness of DEVS, the Discrete-Event System specification, for modeling and subsequent performance evaluation of AUTOSAR-based systems. Moreover, a DEVS simulation model is constructed for AUTOSAR-based electronic control units connected by a communication bus. To aid developers in evaluating a deployment solution, the simulation model is extended with co-simulation with a plant and environment model, evaluation at different levels of detail, and fault injection. Finally, we examine how the simulation model supports the relationship between the supplier and the original equipment manufacturer in the automotive industry. We demonstrate and validate our work by means of a power window case study.

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The FTG+PM framework for multi-paradigm modelling

Cited by 29 publications

References 11 publications

Self-adaptation in software-intensive cyber–physical systems: From system goals to architecture configurations

Self-adaptation in software-intensive cyber–physical systems: From system goals to architecture configurations

Foundations of Multi-Paradigm Modelling for Cyber-Physical Systems

DEVS for AUTOSAR-based system deployment modeling and simulation

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