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+So let's talk more about testing, as we said a
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+little earlier in the lesson, testing means executing the program on
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+a sample of the input domain, that is of all
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+the possible input data and I really want to stress that
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+this sample is tiny sample of the input domain. There
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+are two important aspects of testing that I'm want to mention here,
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+there first one is that testing is a dynamic technique. And
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+what that means is that the program must be executed in
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+order to perform testing. The second important point is that
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+testing is an optimistic approximation. And what does it mean
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+to be optimistic? Well, it means that the program under
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+test is exercised with a very small subset of all the
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+possible inputs as we just said. And this is done
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+under the assumption that the behavior with any other input
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+is consistent with the behavior shown for the selected subset
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+of input data, that is why it is an optimistic approach.
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+Another concept that I want to mention explicitly, is the
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+concept of successful test. And I'm going to do that,
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+using another quote. This one from Goodenough and Gerhart
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+in their paper Towards a Theory of Test Data Selection,
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+and what the quote says is that a test
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+is successful if the program fails. And this might sound
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+counterintuitive, but the point here is that testing cannot
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+prove the absence of errors, but only reveal their presence.
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+If a set of tests does not produce any failure, we are either in the extremely
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+unlikely case of a correct program, or in
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+the very likely situation of a bad set of
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+tests that are not able to reveal failures of the program. And that is why we
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+say that the test is successful if you
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+can show that there are problems in the program.