Subjects, Models, Languages, Transformations

Discussions about model-driven approaches tend to be hampered by terminological confusion. This is at least partially caused by a lack of formal precision in defining the basic concepts, including that of "model" and "thing being modelled" - which we call subject in this paper. We propose a minimal criterion that a model should fulfill: essentially, it should come equipped with a clear and unambiguous membership test; in other words, a notion of which subjects it models. We then go on to discuss a certain class of models of models that we call languages, which apart from defining their own membership test also determine membership of their members. Finally, we introduce transformations on each of these layers: a subject transformation is essentially a pair of subjects, a model transformation is both a pair of models and a model of pairs (namely, subject transformations), and a language transformation is both a pair of languages and a language of model transformations. We argue that our framework has the benefits of formal precision (there can be no doubt about whether something satifies our criteria for being a model, a language or a transformation) and minimality (it is hard to imagine a case of modelling or transformation not having the characterstics that we propose)

Метамоделирование и Многоуровневые Метаданные как Основа Технологии Создания Адаптируемых Информационных Систем

Рассматриваются методы создания распределенных информационных систем, динамически настраиваемых на меняющиеся потребности пользователей и условия эксплуатации. Описываемые средства основаны на использовании многоуровневых моделей и метаданных, представляющих различные стороны функционирования систем на разных уровнях абстракции и с различных точек зрения. Основные уровни метаданных, описывающих систему: логический (описание объектов системы в терминах предметной области), физический (описание представления данных в базе данных) и презентационный (описание интерфейса пользователя системы). Модели и набор метаданных могут изменяться в процессе функционирования системы. На основе базовых моделей могут разрабатываться новые модели (в частности, созданы Web-модель, модели репортинга и бизнес-процессов). Представленный подход реализуется в CASE-технологии METAS, предназначенной для поддержания всего жизненного цикла адаптируемых систем. Функционирование системы строится на интерпретации построенных моделей. Возможности адаптации основаны на средствах реструктуризации данных, генерации и настройки пользовательского интерфейса, управления документами, подключения новых программных компонентов. В CASE-систему включены средства экспорта-импорта, реплицирования данных и моделей, интеграции с внешними системами, а также средства защиты. Разрабатываемые с использованием технологии информационные системы имеют клиент-серверную архитектуру. Технология METAS базируется на использовании языка UML и предметно-ориентированных языков для разработки моделей системы, описания бизнес-правил, специфических для конкретных предметных областей. Предусмотрены средства, позволяющие настраиваться на использование различных реляционных СУБД. Программная платформа – .NET

What is a Model?

With the recent trend to model driven development a commonly agreed notion of model" becomes a pivotal issue. However, currently there is little consensus about what exactly a model is and what it is not. Furthermore, basic terms such as metamodel" are far from being understood in the same way by all members of the modeling community. This article attempts to start establishing a consensus about generally acceptable terminology. Its main contribution is the distinction between two fundamentally different kinds of models, i.e. type model" versus token model". The recognition of the fundamental difference in these two kinds of models is crucial to avoid misunderstandings and unnecessary disputes among members of the modeling community

Metamodelling in the information field

The article studies metamodelling in the information field. Specifics of metamodelling are described. Three basic interpretations of metamodelling are shown. The features of metamodelling in information technologies and information field are presented. A functional difference between the information space and the information field is specified. The article studies metarelations in the information field. Three information situations characterizing metarelations are considered: sequence, transformation, and generalization. The differences in metarelations between an object and a metamodel and between a model and a metamodel are described. The article shows the relation scheme in the system "object – model – metamodel". The scheme of metatheory formation is presented. The principles of metamodelling in the information field are revealed. The article proves that a metamodel in the information field is a model of information construction. A new concept of information metamodelling is introduced

A foundation for multi-level modelling

Multi-level modelling allows types and instances to be mixed in the same model, however there are several proposals for how meta- models can support this. This paper proposes a meta-circular basis for meta-modelling and shows how it supports two leading approaches to multi-level modelling

A foundation for multi-level modelling

Multi-level modelling allows types and instances to be mixed in the same model, however there are several proposals for how metamodels can support this. This paper proposes a meta-circular basis for meta-modelling and shows how it supports two leading approaches to multi-level modelling