Axel van Lamsweerde · 2010
The effectiveness of model-driven engineering relies on our ability to build high-quality models. This task is intrinsically difficult. We need to produce sufficiently complete, adequate, consistent, and well-structured models from incomplete, imprecise, and sparse material originating from multiple, often conflicting sources. The system we need to consider in the early stages comprises software and environment components including people and devices.
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Nicolas Farcet, Nicolas Farcet, Damien Pollet Reflective et al. · 2012
In many large organizations, the model transformations allowing the engineers to more or less automatically go from platformindependent models (PIM) to platform-specific models (PSM) are increasingly seen as vital assets. As tools evolve, it is critical that these transformations are not prisoners of a given CASE tool. Considering in this paper that a CASE tool can be seen as a platform for processing a model transformation, we propose to reflectively apply the MDA to itself. We propose to describe models of transformations that are CASE tool independent (platform-independent transformations or PIT) and from them to derive platform-specific transformations (PST). We show how this approach might help in reaching a consensus in the RFP on MOF QVT, including a solution for the declarative/imperative dilemma. We finally explore the consequences of this approach on the development life-cycle.
Cited by 5Open access
Don Batory · ACM eBooks · 2026
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Fabrice Kordon, Jérôme Hugues, Xavier Renault · Lecture notes in computer science · 2008
Cited by 10
Amstel, van, MF Marcel, Brand, van den, MGJ Mark, Protic, Z Zvezdan et al. · Data Archiving and Networked Services (DANS) · 2014
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Bill Karakostas, Yannis Zorgios · IGI Global eBooks · 2008
This chapter argues that modeling is at the core of every service engineering method. Modeling not only allows us to understand business services but, what is equally important, to transform them into software-realized services. In general, models provide abstractions of a physical system that allow engineers to reason about that system while ignoring irrelevant details and focusing on relevant ones (Brown, 2004). All forms of engineering and science rely on models to understand complex, real-world systems. Models are used to predict system properties, reason about how changes in some parts of it will affect the rest of a system, and communicate key system characteristics to various stakeholders. The models may be developed as a mock-up or blueprint prior to implementing the physical system, or they may be derived from an existing system or a system in development, as an aid to understanding its behavior.
Cited by 1
Rolv Bræk, Geir Melby · 2005
SummaryAbstraction and platform are two of the most central concepts in MDA. To succeed with MDA means to build a clear, operational understanding of the two concepts. Two key questions are how to express the PIM and especially its behavior, and how to deal with implementation and platform dependent properties. In this chapter we offer some answers based on earlier work on model-driven development and current work on model-driven service engineering. A central aim of the latter work is to enable rapid, modular and incremental development and deployment of collaborative services. A model-driven solution supported by a layered execution framework is presented.
Cited by 6Open access
Jean Bézivín, Nicolas Farcet, Jean‐Marc Jezéquél et al. · HAL (Le Centre pour la Communication Scientifique Directe) · 2003
In many large organizations, the model transformations allowing the engineers to more or less automatically go from platformindependent models (PIM) to platform-specific models (PSM) are increasingly seen as vital assets. As tools evolve, it is critical that these transformations are not prisoners of a given CASE tool. Considering in this paper that a CASE tool can be seen as a platform for processing a model transformation, we propose to reflectively apply the MDA to itself. We propose
Cited by 0Open access
Amstel, MF Marcel van, Brand, MGJ Mark van den, Protic, Z Zvezdan et al. · TU/e Research Portal (Eindhoven University of Technology) · 2012
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Daniel Kampka · 2008
Abstract. Model-Driven Architecture (MDA) is a recent software development paradigm which highlights models and transformations between models within an architecture platform to achieve a new way of developing software. Service Engineering is also a new discipline, which deals with systematic development of services in order to facilitate B2B cooperation or integration of business application software. In recent time especially Web Services have been used. This paper presents latest approaches that combine MDA and Web Service engineering methods ranging from an early vision to one of the latest approaches, which uses Semantic Web features. The approaches are classified into top-down or bottom-up development styles and compared to each other. In addition, benefits and drawbacks are pointed out.
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Marcel van Amstel, Mark van den Brand, Zvezdan Protić et al. · 2011
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Bill Karakostas, Yannis Zorgios · IGI Global eBooks · 2011
This chapter argues that modeling is at the core of every service engineering method. Modeling not only allows us to understand business services but, what is equally important, to transform them into software-realized services. In general, models provide abstractions of a physical system that allow engineers to reason about that system while ignoring irrelevant details and focusing on relevant ones (Brown, 2004). All forms of engineering and science rely on models to understand complex, real-world systems. Models are used to predict system properties, reason about how changes in some parts of it will affect the rest of a system, and communicate key system characteristics to various stakeholders. The models may be developed as a mock-up or blueprint prior to implementing the physical system, or they may be derived from an existing system or a system in development, as an aid to understanding its behavior.Request access from your librarian to read this chapter's full text.
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Spencer Rugaber, Kurt Stirewalt · IEEE Software · 2004
Reverse engineering is the process of comprehending software and producing a model of it at a high abstraction level, suitable for documentation, maintenance, or reengineering. But from a manager's viewpoint, there are two painful problems: 1) It's difficult or impossible to predict how much time reverse engineering will require. 2) There are no standards to evaluate the quality of the reverse engineering that the maintenance staff performs. Model-driven reverse engineering can overcome these difficulties. A model is a high-level representation of some aspect of a software system. MDRE uses the features of modeling technology but applies them differently to address the maintenance manager's problems. Our approach to MDRE uses formal specification and automatic code generation to reverse the reverse-engineering process. Models written in a formal specification language called SLANG describe both the application domain and the program being reverse engineered, and interpretations annotate the connections between the two. The ability to generate a similar version of a program gives managers a fixed target for reverse engineering. This, in turn, enables better effort prediction and quality evaluation, reducing development risk.
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Jean Bézivín, Nicolas Farcet, Jean‐Marc Jezéquél et al. · Lecture notes in computer science · 2003
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Kevin Lano, Hessa Alfraihi · Advances in information quality and management · 2024
In this article, the authors describe the field of agile model-driven software engineering methods and present the results of a survey of the research and industrial practice in this field over the last 25 years. They evaluate how the field has grown and diversified over the surveyed time period, describe the range of applications of agile model-driven development, and identify the key milestones and points of progress of the field. The evolution of the area in terms of the techniques employed and the contribution of industrial practitioners is also described.
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Kühne, Stefan, Thränert, Maik, Gebauer, M. · Publikation Server (Leipzig University)
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Tiziana Margaria, Julia Padberg, Gabriele Taentzer et al. · 2006
Abstract: Precise specification of meta-models is an important prerequisite for the successful application of a model-driven engineering (MDE) process. One means of precise specification are textual constraints. However, the task of constraint development is time-consuming and error-prone if done manually. In this paper, we present both a methodology and a tool for developing constraints in a systematic way that can be integrated into a CASE tool. Thus, we provide a semi-automated means for integrating constraints into the MDE process. Our approach is based on an extensible library of generic constraint patterns. Constraint patterns can be combined to create complex constraints and easily parameterized in a CASE tool. Moreover, we show how these parameterized patterns are transformed into platform-independent or platform-specific constraints by a model transformation.
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Milward, David Michael · Oxford University Research Archive (ORA) (University of Oxford) · 2020
Semantic interoperability is a concern in the design and implementation of modern information systems. Whenever two systems communicate it is important that they share an adequate, common interpretation of any information transferred. Similarly, whenever data created or ac- quired in one context is used in another, it is important that the provenance of the data is consistent with its intended usage. Medical researchers depend on understanding good quality data, most of which is kept in information processing systems designed for multiple purposes by multiple organisations and individuals with different motivations in mind. As a result the original meaning and context of the data being used in analysis can be difficult to establish, in addition there are many ways in which data can be corrupted, missing or otherwise altered, resulting in research data scientists spending the majority of their time in activities variously referred to as ‘data-cleaning’, ‘data- wrangling’ and ‘data-munging’, sometimes leading to a lack of trust in the quality of the data. This thesis is a response to that challenge. The approach combines and builds upon existing work in two distinct areas. The first is that of data standards and metadata registries, in which a consensus has been reached regarding the abstract representation of the ‘semantics’ of a data element. The second is that of software modelling and model-driven engineering, in which a consensus has also been reached regarding the abstract representation of data structures and the relationships between data elements. The key contributions of this thesis are firstly a formal language for reasoning about se- mantic interoperability in terms of data models. In addition a formal grammar is provided on which metadata registries can be built guaranteeing consistency of models. A modelling language for metadata description is introduced, based upon the widely-used Eclipse modelling framework, a de-facto standard in model-driven engineering. The thesis then demonstrates that this language, used in combination with a suitable set of constraints for metadata registration and management, can be used to achieve and maintain semantic interoperability in practice.
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Stuart Kent · Electronic Notes in Theoretical Computer Science · 2003
There is currently much interest in model driven approaches to software engineering. The basic idea is to make business, architecture and design models frst class artefacts that are not discarded once the code gets built, but rather can be exercised independently, be reconciled with each other and underlying implementations, and used to (partially) generate each other and implementations. This is particularly valuable when an application needs to be updated and changed, as up-to-date models will still be there to help understand and evolve it using the same abstractions originally used to build it. It is also valuable for applications that need to be delivered on multiple platforms and technologies, which may also change over time, as the models are generally independent of these, hence longer-lived. This talk will argue that to support model driven software engineering, one needs to support model driven language engineering. The former is likely to lead to a larger number of more focused modelling languages, as opposed to a small number of monolithic, poorly integrated languages than we have at present. There will be more emphasis on domain specifc languages. We will need to support the definitions of families of languages where overlap in language capabilities is recognized and repetition is avoided. Furthermore, more sophisticated modelling tools will be required, including tools to exercise models, for validation and verifcation, and tools for reconciliation and translation between models. Thus defnitions should be platform independent, and it should be possible to automate (at least partially) the generation of language-specific modelling, reconciliation and translation tools. The talk will present some on-going work in this area, including a demonstration of language engineering tools that we are currently building, and a vision for the tools and languages we would like to build.
Cited by 8Open access
Michael Wahler, Jana Koehler, Achim D. Brucker · Technische Universität Berlin – Universitätsbibliothek · 2024
Precise specification of meta-models is an important rerequisite for the successful application of a model-driven engineering (MDE) process. One means of precise specification are textual constraints. However, the task of constraint development is time-consuming and error-prone if done manually. In this paper, we present both a methodology and a tool for developing constraints in a systematic way that can be integrated into a CASE tool. Thus, we provide a semi-automated means for integrating constraints into the MDE process. Our approach is based on an extensible library of generic constraint patterns. Constraint patterns can be combined to create complex constraints and easily parameterized in a CASE tool. Moreover, we show how these parameterized patterns are transformed into platform-independent or platform- specific constraints by a model transformation.
Cited by 21Open access