After deep analysis of possible input values, data set was limited to the values that provide various path coverages for tested application. Values were chosen to be the best representatives of data that interacts with each other, and to discover defects that may have critical impact on the tested system.

We created input categories with indicated positive values:

Assumptions:

For provided data we expect to have full coverage of the system. We can try testing all combinations of given values (getting 324 test cases = 3*3*4*3*3 - Cartesian Count) or try to use a shortcut to achieve it with Pairwise, making test case numbers significantly less.

Observations:

Pairwise by AnkrPt generates a Test Suite for this input data set containing 16 test cases, that are composed of 102 simple all-pairs of given values:

Conclusions:

We can see that some pairs of values appear more than once, but this is inevitable, as covering test cases requires return values exactly fulfilling indicated path (to cover minimum amount of test cases with all pairs indicates creating cases where some parameters can have any value from given positive set of data).

Comparing testing all combinations of values to Pairwise numbers makes a huge difference between 324 and 16 test cases.

Assumptions:

It is known that pairwise technique fails when highly probable or high-impact input value combinations get too little attention. To mitigate those risks we use Required Tests, to assure that those combinations are included in generated Test Suite.

We define required tests for given example (empty values stand for "any valid value"):

Observations:

Another run of Pairwise and we get brand new, polished Test Suite composed of 15 test cases, that includes high-risk / highly probable value combinations:

Conclusions:

Adding required test to the suite does not mean that number of test cases will increase.

Pairwise processes them at the beginning of the test case optimization, so they have impact on the process. There are situations where number of test cases may be smaller with required test than without them and this is proper behavior, as Pairwise will give you the best test suite with given input, and it may happen that required test will be better fit for further test generation.

Assumptions:

As we’ve got complete Test Suite covering "happy paths" for the application it is needed to provide tests covering negative values.

We provide negative values that should be included in Test Suite:

Observations:

After another run of Pairwise we have completed Test suite composed with 15 "happy path" test cases (including required ones) and 8 negative test cases.

Conclusions:

AnkrPt Pairwise is giving you Test Suite containing 15 positive test cases and 8 negative, to cover all system paths, highly probable and high-risk value combinations to give you opportunity to discover most defects that might occur during complex combinatorial testing.

We provide constraints for our Test Suite: We know that child and child under 2 should be always treated by pediatrician, and rash as well as rash and fever should be treated by dermatologist or pediatrician(as it may be children issue).

During test generation, we get information, about pairs that were eliminated with Constraints:

Conclusions:

After another run of Pairwise we have completed Test suite composed with 17 "happy path" test cases (including required ones and constraints) and 8 negative ones, but those are more suited for our needs(as we can see, required test changed to meet constraints conditions).

Summing up, AnkrPt Pairwise is a very handy tool that will make your work much easier. Even with complex Test Suite composed of positive, negative criteria, required test and constrains you will get significantly less test cases than with all value combinations (17 "happy path" cases and 8 negative ones, with constraints to 324 Cartesian Count that do not even cover negative cases).

Pairwise require some time in preparing the data, constraints and requirements, as well as understanding the business processes. Testing planing with AnkrPt Pairwise is less time and budget consuming, easier to estimate, and easier to manage with application updates (once you have created your initial set, you can easily update as changes occur).