Ajagbe, Muideen (2017) Exploring Model Driven Engineering from Behavioural Models. MSc by research thesis, University of York.
Abstract
Model Driven Engineering (MDE) is an approach in software engineering that promotes the use of models as first class artefacts. It enables improved productivity and consistency through the reuse of models to generate other necessary artefacts such as working code and textual documents. In MDE, modelling tools and model management operations are deployed to explore a system under development. Through model management operations (e.g. model transformation, validation and comparison), many system can be automated. For example, model-to-model transformation (M2M) are used to develop other model artefacts from the source models.
EAE system is used as our case study and code is normally hand-crafted for its simulation. However, this hand-crafted code might contain bugs as modellers are prone to error. The need to avoid this error gives rise to using MDE practices on the system and it provides an avenue to generating OO code. This code is meant to be fitness-for-purpose thereby leading to support for EAE simulation. As MDE is applied to this system, the transformation of EAE model mostly represented in behaviour diagrams to structure model is conceived.
This thesis explores EAE's models by transforming its behaviour diagrams to structural diagram where OO code can be generated. Our techniques deploy two approaches towards the EAE's domain model. The structural diagram produces by these different approaches leads to OO code generation which will be used as a guide to EAE's simulation. This process is supported by the results of transformation rule used in the thesis thereby reducing loss of information during the transformation process.
Metadata
Supervisors: | Polack, FAC and Paige, Richard |
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Awarding institution: | University of York |
Academic Units: | The University of York > Computer Science (York) |
Depositing User: | Mr Muideen Ajagbe |
Date Deposited: | 27 Sep 2017 08:21 |
Last Modified: | 27 Sep 2017 08:21 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:18240 |
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