MIXIN BASED BEHAVIOUR MODELLING - An example based on composed state machines

Ashley McNeile, Nicholas Simons

2004

Abstract

State Machines are the basic mechanism used to specify the behaviour of objects in UML based object models and admit the possibility of direct animation or execution of a model. Tools that exploit this potential offer the promise of both supporting early validation of a model under development and allowing generation of final code directly from the model. Recently, we have made some new proposals on how state machines are used to model behaviour: firstly, that complex object behaviour can be best modelled by the parallel composition of multiple state machines; and secondly, that a formal distinction can be made between purely event driven machines and those whose states are derived from other information in the model. We illustrate the advantages of this approach with a small example that shows how it can help reduce redundancy and promote simplicity.

References

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Paper Citation


in Harvard Style

McNeile A. and Simons N. (2004). MIXIN BASED BEHAVIOUR MODELLING - An example based on composed state machines . In Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 3: ICEIS, ISBN 972-8865-00-7, pages 179-183. DOI: 10.5220/0002644601790183


in Bibtex Style

@conference{iceis04,
author={Ashley McNeile and Nicholas Simons},
title={MIXIN BASED BEHAVIOUR MODELLING - An example based on composed state machines},
booktitle={Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 3: ICEIS,},
year={2004},
pages={179-183},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002644601790183},
isbn={972-8865-00-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 3: ICEIS,
TI - MIXIN BASED BEHAVIOUR MODELLING - An example based on composed state machines
SN - 972-8865-00-7
AU - McNeile A.
AU - Simons N.
PY - 2004
SP - 179
EP - 183
DO - 10.5220/0002644601790183