Automatic generation of software applications: a platform-based MDA approach

The Model Driven Architecture (MDA) allows moving the software development from the time consuming and error-prone level of writing program code to the next higher level of modeling. In order to gain benefit from this innovative technology, it is necessary to satisfy two requirements. These are first, the creation of compact, complete and correct platform independent models (PIM) and second, the development of a flexible and extensible model transformation framework taking into account frequent changes of the target platform. In this thesis a platform-based methodology is developed to create PIM by abstracting common modeling elements into a platform independent modeling library called Design Platform Model (DPM). The DPM contains OCL-based types for modeling primitive and collection types, a platform independent GUI toolkit as well as other common modeling elements, such as those for IO-operations. Furthermore, a DPM profile containing diverse domain specific and design pattern-based stereotypes is also developed to create PIM with high-level semantics. The behavior in PIM is specified using an OCL-like action language called eXecutable OCL (XOCL), which is also developed in this thesis. For model transformation, the model compiler MOCCA is developed based on a flexible and extensible architecture. The model mapper components in the current version of MOCCA are able to map desktop applications onto JSE platform; the both business object layer and persistence layer of a three-layered enterprise applications onto JEE platform and SAP ABAP platform. The entire model transformation process is finished with complete code generation

Applied metamodelling: a foundation for language driven development.

The motivation behind XMF was to develop a technology that would support a language driven approach to modelling and system development. Our starting point was that UML was not sufficiently flexible and in order to address this we designed an executable meta-language. This book describes the approach and provides an introduction to the key technologies: meta-models, language definition and mappings. The book concludes with a number of worked examples

UMLexe – UML virtual machine : a framework for model execution

The aim of this thesis is the specification and development of a new UML virtual machine – UMLexe- capable of executing platform independent system specifications. For executing models, computational completeness is required and UMLexe propose a subset of UML and operational semantics for executing those models. UMLexe will provide prototype functionality to prove the concept of executing components combined with interaction models. The first part of the thesis describes a case scenario illuminating the model notation. After a more detailed look at the specification and implementation, this case is executed to prove the concept. The last part of the thesis is dedicated to the specification and development of the UMLexe virtual machine and the evaluation of the implementation in terms of defined requirements and existing solutions executing UML models

Applied metamodelling : a foundation for language driven development

The Third Edition of Applied Metamodelling represents a small increment since the Second Edition was produced in 2008. The book continues to be referenced in schol- arly articles with 212 citations on Google Scholar including nearly 150 since 2008. The open-source release of the accompanying technologies XMF and XMF-Mosaic did not generate the same level of interest, partly due to a lack of exposure and associated tuto- rial materials. Recently, interest in the field of multi-level modelling has increased and has led to publications and a Dagstuhl Seminar based on the ideas of meta-languages and tool-modelling. An overview of the historical development of XMF, the ideas in this book, and the the birth and death of an associated startup company has been published in 2012 as part of the 10th anniversary edition of the the Journal of Software and Systems Modeling. A project based on the foundations developed in this book and the tooling, now rebranded XModeler, is underway and the aim is to advance the field of multi-level language-based system engineering

Consistency Modeling in a Multi-Model Architecture : Integrate and Celebrate Diversity

Central to Model-Driven Engineering (MDE) is seeing models as objects that can be handled and organized into metamodel stacks and multi-model architectures. This work contributes with a unique way of doing consistency modeling where the involved models are explicitly organized in a multi-model architecture; a general model for creating multi-model architectures that allows semantics to be attached is defined and applied; explicit attachment of semantics is demonstrated by attaching Java classes that implement different instantiation semantics in order to realize the consistency modeling and the automatic generation of consistency data. The kind of consistency addressed concerns relations between data residing in legacy databases defined by different schemas. The consistency modeling is meant to solve the problem of exposing inconsistencies by relating the data. The consistency modeling combines in a practical way visual modeling and logic (OCL). The approach is not limited to exposing inconsistencies, but may also be used to derive more general information given one or more data sets. The consistency is modeled by defining a consistency model that relates elements of two given legacy models. The consistency model is expressed in a language specially designed for consistency modeling. The language allows definition of classes, associations and invariants expressed in OCL. The interpretation of the language is special: Given one conforming data set for each of the legacy models, the consistency model may then be automatically instantiated to consistency data that tells if the data sets are consistent or not. The invariants are used to decide what instances to generate when making the consistency data. The amount of consistency data to create is finite and limited by the given data sets. The consistency model is instantiated until no more elements can be added without breaking some invariant or multiplicity. The consistency data is presented as a model which can be investigated by the user