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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.
Reducing the number of test scenarios
Imagining the previous example, instead of having XXX test scenarios to perform, we would need just XX.
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Let's say that we have 5 parameters. In this case, 5-way testing would generate all the possible combinations of these 5 parameters. Therefore, 5-way testing is precisely the same as saying that we're going to test all combination of parameter values. |
Optmizing further the test scenarios to be performed
The first level of optimization is further reducing the number of generated test
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scenario.
Even if we use pairwise testing, or n-wise testing in general, to dramatically reduce the number of test scenarios, not all of these combinations may make sense for several reasons.
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In Test Case Designer we can apply "constraints" involving the combination of 2 parameter values. We can apply several constrains as shown in the followin example: Class=First cannot exist together neither with Children=1 nor Children=Mode than 1.
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The second level of optimization is about including important scenarios first.
Not But not all combination of parameters may be equaly representative. Sometimes there are parameter combinations we know that are highly important as they represent highly used happy paths, or whose business impact is high.
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