Suppose, you're going to design a new software system for a specific domain. One of the first steps is to introduce a domain object model which comprises the core entities in the domain as well as their relationships. That's easy, you might say. If it is that simple, why do so many projects fail in establishing the right domain object model? And, of course, this challenge inevitably appears in all kinds of modeling activities.
But now for something completely different - as Monty Python would say. I got two nice cats at home. In order to model a cat, there are different possibilities:
- (ATOM) We could consider a cat as a mere collection of molecules.
- (GENE) Obviously, a cat can be uniquely identified using its DNA.
- (BODY) Another approach is modeling a cat as an aggregation of subsystems such as legs, joints, muscles, intestines.
Does it make sense to apply the first model (ATOM) in order to understand how a cat moves? No, because the detail level is overwhelming.
Is it useful to use the third model for understanding all chemical activities within a cat? Definitely not!
With other words, we can model the same physical concepts in different ways, each of these views strongly depending on the purpose of the model. Don't let yourself be confused. It is not as simple as having only one model for one purpose. For example, to understand the physical appearance of a cat, you could apply model ATOM as well as model BODY.
What are the implications of this observation?
- First of all, you might require different models (views) in order to define and understand a software system.
- Secondly, each model should be motivated by a concrete and useful purpose.
- Thirdly, all participants should agree on syntax and semantics of the model.
- And last but not least, all models should be documented.
Mind the word "useful" in the second bullet point. As organization drives architecture, the organization often directly maps to entities in the model. If your organization is badly structured, your architecture will reveal the same problem. Think about this in the context of your own organization.
As another consequence I'd like to emphasize that it is not sufficient just inventing a couple of sophisticated models. The set of models should also be simple, complete and consistent. All of the models should complement each other in a meaningful and appropriate way. That's the reason why we got view sets such as the UML 4+1 view.
Unfortunately, I often sit in project meetings where people strongly believe they are all sharing the same view of their domain, while in fact they are not. Endless discussions might be an indicator for this problem. Thus, it is essential to explicitly come up with a common domain model that is agreed among all participants. Basically, the design of such a model should be one of the early steps in a development project (directly after scoping but before architecture design). Needless to say that software engineers are surrounded by models: they have specific views of the problem domain and the solution domain, use tools such as compilers or database systems that themselves are built on top of models.
If a software developer's life is about models and model transformations (e.g., the mapping from the problem domain to the solution domain) we should consider models as first class citizens and invest sufficient time for choosing the right viewpoints and establishing the right models.
Interestingly, even our view of the physical world such as the way we understand a cat is determined by models. But this is a different story.
