- Getting Started
- Terms and Concepts
- Common Modeling Techniques
- Hints and Tips
Common Modeling Techniques
Modeling the Vocabulary of a System
You'll use classes most commonly to model abstractions that are drawn from the problem you are trying to solve or from the technology you are using to implement a solution to that problem. Each of these abstractions is a part of the vocabulary of your system, meaning that, together, they represent the things that are important to users and to implementers.
For users, most abstractions are not that hard to identify because, typically, they are drawn from the things that users already use to describe their system. Techniques such as CRC cards and use case-based analysis are excellent ways to help users find these abstractions. For implementers, these abstractions are typically just the things in the technology that are parts of the solution.
To model the vocabulary of a system,
- Identify those things that users or implementers use to describe the problem or solution. Use CRC cards and use case-based analysis to help find these abstractions.
- For each abstraction, identify a set of responsibilities. Make sure that each class is crisply defined and that there is a good balance of responsibilities among all your classes.
- Provide the attributes and operations that are needed to carry out these responsibilities for each class.
Figure 4-9 shows a set of classes drawn from a retail system, including Customer, Order, and Product. This figure includes a few other related abstractions drawn from the vocabulary of the problem, such as Shipment (used to track orders), Invoice (used to bill orders), and Warehouse (where products are located prior to shipment). There is also one solution-related abstraction, Transaction, which applies to orders and shipments.
Figure 4-9 Modeling the Vocabulary of a System
As your models get larger, many of the classes you find will tend to cluster together in groups that are conceptually and semantically related. In the UML, you can use packages to model these clusters of classes.
Your models will rarely be completely static. Instead, most abstractions in your system's vocabulary will interact with one another in dynamic ways. In the UML, there are a number of ways to model this dynamic behavior.
Modeling the Distribution of Responsibilities in a System
Once you start modeling more than just a handful of classes, you will want to be sure that your abstractions provide a balanced set of responsibilities. What this means is that you don't want any one class to be too big or too small. Each class should do one thing well. If you abstract classes that are too big, you'll find that your models are hard to change and are not very reusable. If you abstract classes that are too small, you'll end up with many more abstractions than you can reasonably manage or understand. You can use the UML to help you visualize and specify this balance of responsibilities.
To model the distribution of responsibilities in a system,
- Identify a set of classes that work together closely to carry out some behavior.
- Identify a set of responsibilities for each of these classes.
- Look at this set of classes as a whole, split classes that have too many responsibilities into smaller abstractions, collapse tiny classes that have trivial responsibilities into larger ones, and reallocate responsibilities so that each abstraction reasonably stands on its own.
- Consider the ways in which those classes collaborate with one another, and redistribute their responsibilities accordingly so that no class within a collaboration does too much or too little.
For example, Figure 4-10 shows a set of classes drawn from Smalltalk, showing the distribution of responsibilities among Model, View, and Controller classes. Notice how all these classes work together such that no one class does too much or too little.
Figure 4-10 Modeling the Distribution of Responsibilities in a System
Modeling Nonsoftware Things
Sometimes, the things you model may never have an analog in software. For example, the people who send invoices and the robots that automatically package orders for shipping from a warehouse might be a part of the workflow you model in a retail system. Your application might not have any software that represents them (unlike customers in the example above, since your system will probably want to maintain information about them).
To model nonsoftware things,
- Model the thing you are abstracting as a class.
- If you want to distinguish these things from the UML's defined building blocks, create a new building block by using stereotypes to specify these new semantics and to give a distinctive visual cue.
- If the thing you are modeling is some kind of hardware that itself contains software, consider modeling it as a kind of node as well, so that you can further expand on its structure.
As Figure 4-11 shows, it's perfectly normal to abstract humans (like AccountsReceivableAgent) and hardware (like Robot) as classes, because each represents a set of objects with a common structure and a common behavior.
Figure 4-11 Modeling Nonsoftware Things
Modeling Primitive Types
At the other extreme, the things you model may be drawn directly from the programming language you are using to implement a solution. Typically, these abstractions involve primitive types, such as integers, characters, strings, and even enumeration types, that you might create yourself.
To model primitive types,
- Model the thing you are abstracting as a class or an enumeration, which is rendered using class notation with the appropriate stereotype.
- If you need to specify the range of values associated with this type, use constraints.
As Figure 4-12 shows, these things can be modeled in the UML as types or enumerations, which are rendered just like classes but are explicitly marked via stereotypes. Primitive types such as integers (represented by the class Int) are modeled as types, and you can explicitly indicate the range of values these things can take on by using a constraint; the semantics of primitive types must be defined externally to UML. Enumeration types, such as Boolean and Status, can be modeled as enumerations, with their individual literals listed within the attribute compartment (note that they are not attributes). Enumeration types may also define operations.
Figure 4-12 Modeling Primitive Types