A strategy
may be very cheap; for example, it may make a random choice of what action
to take, or it may be very expensive and try to compute the best possible choice
according to some optimization criterion. A strategy can use additional memory
besides the model state to record prior action selection history, or it can be memoryless
and forget prior choices. Strategies can use coverage points to help exercise
the implementation thoroughly. There is a whole spectrum of possible strategies.
We illustrate how one can use the basic strategy that is supported by the library and
how one can define customized strategies for on-the-fly testing.
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192 Testing Systems with Complex State
On-the-fly testing with a programmable strategy is the testing technique supported
by the ct tool. Internally, it even handles offline testing (as demonstrated in
Chapter 8) as a special case of this.
12.1 On-the-fly testing
First let us demonstrate on-the-fly testing with the client/server example from previous
chapters. On-the-fly testing is the easiest way to begin testing with the ct
(Conformance Tester) tool. It is not necessary to generate a test suite or create a
scenario. All you need is an implementation (Chapter 2), a model program (Chapter
5), and a test harness or stepper (Chapter 8). The built-in strategy of the ct tool
is random testing: in each state, select an enabled action at random.
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