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+There are some important considerations I want to make on final state
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+machines. And more in general, on model based testing. The first one
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+is about applicability. Testing based on final state machines is a very
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+general approach, that we can apply in a number of contexts. And in
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+particular, if you are working with UML, you have state machines for
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+free. Because state charts are nothing else but a special kind of
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+state machine. So you can apply the technique that we just saw
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+directly on state charts, and try to cover their states and their transitions.
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+Another important point is that abstraction is key. You have to find the
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+right level of abstraction. The bigger the system, the more you have to
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+abstract if you want to represent it with a model, and in particular, with
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+the final state machine. So it's like having a slider, and you have
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+to decide where you want to move on that slider. The more you represent,
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+the more complex your system is going to be and the more thorough your
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+testing is going to be but also more expensive. The less you represent the
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+less expensive testing is going to be, but also testing might not be as
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+thorough as it would be otherwise. So you have to find
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+the right balance between abstracting the weight too much and abstracting
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+the weight too little. And finally there are many other approaches.
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+So we just scratched the surface, and we just saw one possible
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+approach. But for instance, other models that you can use are
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+decision tables, flow graphs and even historical models. Models that can
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+guide your testing based on problems that occurred in your system
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+in the past. And also, in this case, I'm going to put pointers
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+to additional materials in the class notes.