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Given the empyrical data, adopting pairwise testing to test all the ombinations of pairs of parameters (sometimes also called as "all pairs testing") is a technique that is not only feasible but also provides great results in terms of fault-detection.

Imagining the previous example, instead of having XXX test scenarios to perform, we would need just XX.

Sometimes, we may need to test more thoroughly some parameters, and for those we may choose to 3-way testing, for example, to ensure that we cover all the combinations of values of 3 relevant parameters. In this case we may have mixed-strength scenarios where combinations of certain parameters may be tested more thoroughly than others.

Having a limited set of test generated, we can then execute them. However, usually algoritms generate these tests in a order, so that coverage is greater with the first tests and lesser with the last tests. This way, if we stop testing at a given moment, we can make sure that we track coverage and that we tested the most combinations possible.

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