MOCAS: A State-Based Component Model for Self-Adaptation

Ballagny, Cyril; Hameurlain, Nabil; Barbier, Franck

doi:10.1109/saso.2009.11

Cited by 25 publications

(19 citation statements)

References 63 publications

(67 reference statements)

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“…Another perspective is using contract for managing software adaptation at runtime. Indeed, the MOCAS platform not only executes state machines, it is dedicated to performing adaptations of software components [1]. A direct application of execution contracts is to guiding the adaptation of the executed components (e.g., refining the behavior of a component or changing an operating mode of a component).…”

Section: Resultsmentioning

confidence: 99%

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Contracts for Model Execution Verification

Cariou

Ballagny²,

Feugas

et al. 2011

Modelling Foundations and Applications

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Abstract. One of the main goals of model-driven engineering is the manipulation of models as exclusive software artifacts. Model execution is in particular a means to substitute models for code. We focus in this paper on verifying model executions. We use a contract-based approach to specify an execution semantics for a meta-model. We show that an execution semantics is a seamless extension of a rigorous meta-model specification and is composed of complementary levels, from static element definition to dynamic elements, execution specifications as well. We use model transformation contracts for controlling the dynamic consistent evolution of a model during its execution. As an illustration, we apply our approach to UML state machines using OCL as the contract expression language.

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Section: Resultsmentioning

confidence: 99%

“…This refinement is made during the execution of the model, at runtime. This kind of structural modification is typically what can be done for supporting adaptation at runtime [1].…”

Section: Run_to_completion(dooropenevent) Run_to_completion(doorclosementioning

confidence: 99%

Contracts for Model Execution Verification

Cariou

Ballagny²,

Feugas

et al. 2011

Modelling Foundations and Applications

Self Cite

View full text Add to dashboard Cite

show abstract

“…[5,6] have been used as a base for defining the direct model execution characterization exposed in this paper. The MOCAS platform [1] defines a UML agent state machine observing an executed business UML state machine and requiring changes on its current state or structural content. The adaptation is then made following common models@run.time adaptation techniques (case (c) of figure 1).…”

Section: Related Workmentioning

confidence: 99%

Characterization of Adaptable Interpreted-DSML

Cariou

Goaer

Barbier

et al. 2013

Modelling Foundations and Applications

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Abstract. One of the main goals of model-driven engineering (MDE) is the manipulation of models as exclusive software artifacts. Model execution is in particular a means to substitute models for code. More precisely, as models of a dedicated domain-specific modeling language (DSML) are interpreted through an execution engine, such a DSML is called interpreted-DSML (i-DSML for short). On another way, MDE is a promising discipline for building adaptable systems based on models at runtime. When the model is directly executed, the system becomes the model: This is the model that is adapted. In this paper, we propose a characterization of adaptable i-DSML where a single model is executed and directly adapted at runtime. If model execution only modifies the dynamical elements of the model, we show that the adaptation can modify each part of the model and that the execution and adaptation semantics can be changed at runtime.

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“…Contrary to the above approaches, MOCAS [65] deals with building self-adaptive componentbased systems. It specifies the structure of the components using a UML profile whereas their behaviour is specified using UML state machines that are also used to describe adaptation policies.…”

Section: Software Evolution By Using Models At Runtimementioning

confidence: 99%

Addressing the evolution of automated user behaviour patterns by runtime model interpretation

2013

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The use of high-level abstraction models not only can facilitate and improve system development but also runtime system evolution. This is the idea of this work, in which behavioural models created at design time are also used at runtime to evolve system behaviour.These behavioural models describe the routine tasks that users want to be automated by the system. However, users' needs may change after system deployment, and the routine tasks automated by the system must evolve to adapt to these changes. To facilitate this evolution, the automation of the specified routine tasks is achieved by directly interpreting the models at runtime. This turns models into the primary means to understand and interact with the system behaviour associated to the routine tasks as well as to execute and modify it. Thus, we provide tools to allow the adaptation of this behaviour by modifying the models at runtime. This means that the system behaviour evolution is performed by using high-level abstractions and avoiding the costs and risks associated to shutting down and restarting the system.

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MOCAS: A State-Based Component Model for Self-Adaptation

Abstract: 1. 40% des investissements dans les technologies de l'information sont utilisés juste pour l'intégration des différentes technologies utilisées un sein d'un même système [7]. 2. La littérature anglo-saxonne qualifie ces propriétés de « self-star » ou « self-* » [9].

Cited by 25 publications

References 63 publications

Contracts for Model Execution Verification

Contracts for Model Execution Verification

Characterization of Adaptable Interpreted-DSML

Addressing the evolution of automated user behaviour patterns by runtime model interpretation

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