A pattern based approach to defining the dynamic infrastructure of UML 2.0.

APPUKUTTAN, Biju K, CLARK, Anthony, EVANS, Andy, MASKERI, Girish, SAMMUT, Paul, TRATT, Laurence and WILLANS, James (2002). A pattern based approach to defining the dynamic infrastructure of UML 2.0. In: Fourth Workshop on Rigorous Object Oriented Methods, University College, London, March 2002. N/A.

[img]
Preview
PDF
Tratt-pattern_based_approach_to_defyning_...UML20%5B1%5D.pdf
All rights reserved.

Download (51kB) | Preview

Abstract

The 2U Consortium has recently submitted a proposal for the definition of the UML 2.0 infrastructure. This uses an innovative technique of rapidly “stamping out” the definition using a small number of patterns commonly found in software architecture. The patterns, their instantiation, and any further language details are described using precise class diagrams and OCL, this enables the definition to be easily understood. The main focus of the 2U approach is on the static part of the definition. A further concern when modelling software, using languages such as the UML, is describing the dynamic behaviour of the system over time. The contribution of this paper is to provide a template that can be used to “stamp out” the dynamic part of the UML 2.0 infrastructure. We argue for the suitability of the dynamic template because it makes little commitment to concrete abstractions and can, therefore, be used to support a broad spectrum of behavioural languages.

Item Type: Conference or Workshop Item (Paper)
Research Institute, Centre or Group - Does NOT include content added after October 2018: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
Depositing User: Tony Clark
Date Deposited: 07 Apr 2016 09:30
Last Modified: 18 Mar 2021 15:50
URI: https://shura.shu.ac.uk/id/eprint/11898

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics