1.2. Model-Driven Engineering

Model-Driven Engineering (MDE), also called model-driven development, is a well-established paradigm in software engineering. Since simulation engineering can be viewed as a special case of software engineering, it is natural to apply the ideas of MDE also to simulation engineering.

In MDE, there is a distinction between three kinds of models as engineering artifacts created in the analysis, design and implementation phases of a development project:

  1. domain models (also called conceptual models), which describe a real-world domain (and are independent of a computational solution),
  2. design models, which define platform-independent solution designs,
  3. implementation models, which are platform-specific.

Domain models are solution-independent descriptions of a problem domain produced in the analysis phase. A domain model may include both descriptions of the domain's state structure (in conceptual information models) and descriptions of its processes (in conceptual process models). They are solution-independent, or computation-independent, in the sense that they are not concerned with making any system design choices or with other computational issues. Rather, they focus on the perspective and language of the subject matter experts for the domain under consideration.

In the design phase, first a platform-independent design model, as a general computational solution, is developed on the basis of the domain model. The same domain model can potentially be used to produce a number of (even radically) different design models. Then, by taking into consideration a number of implementation issues ranging from architectural styles, nonfunctional quality criteria to be maximized (e.g., performance, adaptability) and target technology platforms, one or more platform-specific implementation models are derived from the design model. These one-to-many relationships between conceptual models, design models and implementation models are illustrated in Figure 1-1.

Figure 1-1. From conceptualization via design to implementation

In general, a model does not consist of just one model diagram including all viewpoints or aspects of the system to be developed. Rather it consists of a set of models, one (or more) for each viewpoint. The two most important viewpoints, crosscutting all three modeling levels (domain conceptualization, design and implementation) are

  1. information modeling, which is concerned with the state structure of the domain, design or implementation;
  2. process modeling, which is concerned with the dynamics of the domain, design or implementation.

Examples of widely used languages for information modeling are Entity Relationship (ER) Diagrams and UML Class Diagrams. Since the latter subsume the former, we prefer using UML class diagrams for making all kinds of information models, including SQL database models.

Examples of widely used languages for process modeling are (Colored) Petri Nets, UML Sequence Diagrams, UML Activity Diagrams and the BPMN. Notice that there is more agreement on the right concepts for information modeling than for process modeling, as indicated by the much larger number of different process modeling languages. This reflects a lower degree of understanding the nature of events and processes compared to understanding objects and their relationships.

Model-driven simulation engineering is based on the same kinds of models as model-driven software engineering: going from a domain model via adesign model to an implementation model for the simulation platform of choice (or to several implementation models if there are several target simulation platforms). The specific concerns of simulation engineering, like, e.g., the concern to capture certain parts of the overall system dynamics with the help of random variables, do not affect the applicability of MDE principles. However, they define requirements for the modeling languages to be used.