Software & Systems Modeling

The realization of model-driven software development requires effective techniques for implementing code generators for domain-specific languages. This paper identifies techniques for improving separation of concerns in the implementation of generators. The core technique is code generation by model transformation, that is, the generation of a structured representation (model) of the target program instead of plain text. This approach enables the transformation of code after generation, which in turn enables the extension of the target language with features that allow better modularity in code generation rules. The technique can also be applied to ‘internal code generation’ for the translation of high-level extensions of a DSL to lower-level constructs within the same DSL using model-to-model transformations. This paper refines our earlier description of code generation by model transformation with an improved architecture for the composition of model-to-model normalization rules, solving the problem of combining type analysis and transformation. Instead of coarse-grained stages that alternate between normalization and type analysis, we have developed a new style of type analysis that can be integrated with normalizing transformations in a fine-grained manner. The normalization strategy has a simple extension interface and integrates non-local, context-sensitive transformation rules. We have applied the techniques in a realistic case study of domain-specific language engineering, i.e. the code generator for WebDSL, using Stratego, a high-level transformation language that integrates model-to-model, model-to-code, and code-to-code transformations.

This expert voice paper presents a comprehensive rationale of multi-level modeling. It aims not only at a systematic assessment of its prospects, but also at encouraging applications of multi-level modeling in business information systems and at providing a motivation for future research. The assessment is developed from a comparison of multi-level modeling with object-oriented, general-purpose modeling languages (GPMLs) and domain-specific modeling languages (DSMLs). To foster a differentiated evaluation, we propose a multi-perspective framework that accounts, among others, for essential design conflicts, different types of users, as well as economic aspects. Besides the assessment of the additional abstraction offered by multi-level modeling, the evaluation also identifies specific drawbacks and remaining challenges. Based on the results of the comparative assessment, in order to foster the adoption and further development of multi-level modeling, we discuss the prospects of supplementing multi-level modeling languages with multi-level programming languages and suggest possible dissemination strategies customized for different groups of users. The paper concludes with an outline of future research.

Much work has been done to clarify the notion of metamodelling and new ideas, such as strict metamodelling, distinction between ontological and linguistic instantiation, unified modelling elements and deep instantiation, have been introduced. However, many of these ideas have not yet been fully developed and integrated into modelling languages with (concrete) syntax, rigorous semantics and tool support. Consequently, applying these ideas in practice and reasoning about their meaning is difficult, if not impossible. In this paper, we strive to add semantic rigour and conceptual clarity to metamodelling through the introduction of Nivel, a novel metamodelling language capable of expressing models spanning an arbitrary number of levels. Nivel is based on a core set of conceptual modelling concepts: class, generalisation, instantiation, attribute, value and association. Nivel adheres to a form of strict metamodelling and supports deep instantiation of classes, associations and attributes. A formal semantics is given for Nivel by translation to weight constraint rule language (WCRL), which enables decidable, automated reasoning about Nivel. The modelling facilities of Nivel and the utility of the formalisation are demonstrated in a case study on feature modelling.