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The Problem with Inheritance

15 January, 2016 - 09:02
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Inheritance seems to work quite well, but suppose we want to do more than just put different kinds of balls on the screen? What if we wanted to be able to change how a ball behaves, after it has been created? What if we want create balls that do a multiple of different behaviors, such as change color and radius? While working solutions using an inheritance-based system do exist, they are cumbersome, inefficient and most importantly, inconsistent with any sort of clear abstract model of what balls should be like.

The problem lies in the very nature of inheritance. When we attempted to separate the variant from the invariant behaviors, we overlooked a crucial aspect of inheritance. In our model, the superclass represented the invariant behaviors of a ball while the subclasses represented the variant behaviors. The separation seemed clear enough in the UML diagram, except that when one has an actual object instance, both the superclass and subclass behaviors are bound into a single entity. A ball object cannot change its variant updateState behavior because it is inextricably bound with to the invariant behaviors. A ball object cannot be composed of multiple updateState behaviors because that code cannot be isolated from the rest of the ball's code. If you want a curving behavior, you have to get it packaged in a whole ball object – you can't get just the behavior.

A clear sympton of this problem is the common code to call the superclass constructor found in all the subclasses' constructors. This tells us that the superclass is really right there in the subclass with everything else. The fact that the code is repeated from class to class says that it is invariant code in the middle of what we want to be variant code.

The inheritance-based model of Ballworld does not separate the variant and the invariant at the proper place. There is invariant code mixed together with the variant code.

That's why they can't be separated and the invariant behaviors are dragged along with the variant behaviors. This is what makes dynamically changing behaviors and multiply composed behaviors so difficult in this system.