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

Authors:
Cyril Ballagny;Nabil Hameurlain;Franck Barbier
Affiliations:
-;-;-
Venue:
SASO '09 Proceedings of the 2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems
Year:
2009

Citing 0
Cited 5

On the performance of UML state machine interpretation at runtime

Proceedings of the 6th International Symposium on Software Engineering for Adaptive and Self-Managing Systems
Contracts for model execution verification

ECMFA'11 Proceedings of the 7th European conference on Modelling foundations and applications
A development framework and methodology for self-adapting applications in ubiquitous computing environments

Journal of Systems and Software
An eclipse modelling framework alternative to meet the models@runtime requirements

MODELS'12 Proceedings of the 15th international conference on Model Driven Engineering Languages and Systems
Characterization of adaptable Interpreted-DSML

ECMFA'13 Proceedings of the 9th European conference on Modelling Foundations and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper introduces MOCAS (Model Of Components for Adaptive Systems), a generic state-based component model which enables the self-adaptation of software components together with their coordination. MOCAS relies on behavioral adaptation instead of structural adaptation and uses the United Modeling Language (UML). Each component embeds a UML state machine to realize its behavior at runtime. It is installed in a container managing the adaptation process and ensuring its consistency. Adaptation is triggered when invariants related to the components business properties are violated. The component supports updates of its specification while it is running. This component model is illustrated through the GridStix case study.