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Model Driven Engineering is a promizing approach that could lead to the emergence of a new paradigm for software evolution, namely Model Driven Software Evolution. Models, Metamodels and Transformations are the cornerstones of this approach. Combining these concepts leads to very complex structures which revealed to be very difficult to understand especially when different technological spaces are considered such as XMLWare (the technology based on XML), Grammarware and BNF, Modelware and UML, Dataware and SQL, etc. The concepts of model, metamodel and transformation are usually ill-defined in industrial standards like the MDA or XML. This paper provides a conceptual framework, called a megamodel, that aims at modelling large-scale software evolution processes. Such processes are modeled as graphs of systems linked with well-defined set of relations such as RepresentationOf (μ), ConformsTo (χ) and IsTransformedIn (τ).  相似文献
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Understanding how software systems evolve is useful from different perspectives: reverse engineering, empirical studies etc.. For an effective understanding we need an explicit meta-model. We introduce Hismo, a meta-model which is centered around the notion of history and we show how we can obtain it from a snapshot meta-model. Based on our experience in developing the Hismo reverse engineering system, we show how we can transform a snapshot meta-model in a history meta-model.  相似文献
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With the recent trend to model driven engineering a common understanding of basic notions such as “model” and “metamodel” becomes a pivotal issue. Even though these notions have been in widespread use for quite a while, there is still little consensus about when exactly it is appropriate to use them. The aim of this article is to start establishing a consensus about generally acceptable terminology. Its main contributions are the distinction between two fundamentally different kinds of model roles, i.e. “token model” versus “type model” (The terms “type” and “token” have been introduced by C.S. Peirce, 1839–1914.), a formal notion of “metaness”, and the consideration of “generalization” as yet another basic relationship between models. In particular, the recognition of the fundamental difference between the above mentioned two kinds of model roles is crucial in order to enable communication among the model driven engineering community that is free of both unnoticed misunderstandings and unnecessary disagreement.  相似文献
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A rule-based update transformation is a model transformation where a single model is transformed in place. A model refactoring is a model transformation that improves the design described in the model. A refactoring should only affect a previously chosen subset of the original model. In this paper, we discuss how to define and execute model refactorings as rule-based transformations in the context of the UML and MOF standards. We also present an experimental tool to execute this kind of transformation.  相似文献
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Software product lines are increasingly built using components from specialized suppliers. A company that is in the middle of a supply chain has to integrate components from its suppliers and offer (partially configured) products to its customers. To satisfy both the variability required by each customer and the variability required to satisfy different customers’ needs, it may be necessary for such a company to use components from different suppliers, partly offering the same feature set. This leads to a product line with alternative components, possibly using different mechanisms for interfacing, binding and variability, which commonly occurs in embedded software development.  相似文献
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Model-driven engineering proposes the use of models to describe the relevant aspects of the system to be built and synthesize the final application from them. Models are normally described using Domain-Specific Modeling Languages (DSMLs), which provide primitives and constructs of the domain. Still, the increasing complexity of systems has raised the need for abstraction techniques able to produce simpler versions of the models while retaining some properties of interest. The problem is that developing such abstractions for each DSML from scratch is time and resource consuming.  相似文献
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Software modernization is critical for organizations that need cost-effective solutions to deal with the rapid obsolescence of software and the increasing demand for new functionality. This paper presents the XIRUP modernization methodology, which proposes a highly iterative process, structured into four phases: preliminary evaluation, understanding, building and migration. This modernization process is feature-driven, component-based, focused on the early elicitation of key information, and relies on a model-driven approach with extensive use of experience from the previous projects. XIRUP has been defined in the European IST project MOMOCS, which has also built a suite of support tools. This paper introduces the process using a case study that illustrates its activities, related tools and results. The discussion highlights the specific characteristics of modernization projects and how a customized methodology can take advantage of them.  相似文献
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Cloud computing can reduce power consumption by using virtualized computational resources to provision an application’s computational resources on demand. Auto-scaling is an important cloud computing technique that dynamically allocates computational resources to applications to match their current loads precisely, thereby removing resources that would otherwise remain idle and waste power. This paper presents a model-driven engineering approach to optimizing the configuration, energy consumption, and operating cost of cloud auto-scaling infrastructure to create greener computing environments that reduce emissions resulting from superfluous idle resources. The paper provides four contributions to the study of model-driven configuration of cloud auto-scaling infrastructure by (1) explaining how virtual machine configurations can be captured in feature models, (2) describing how these models can be transformed into constraint satisfaction problems (CSPs) for configuration and energy consumption optimization, (3) showing how optimal auto-scaling configurations can be derived from these CSPs with a constraint solver, and (4) presenting a case study showing the energy consumption/cost reduction produced by this model-driven approach.  相似文献
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