The pairwise data generation method

When you test any application, you might want to ensure that the test data that you use covers all possible combinations of item type values. To achieve this goal of maximum coverage of all possible scenarios, you must apply the pairwise data generation method on the required item types of a schema.

For testing any application, you must attain the maximum test coverage. You can achieve the maximum test coverage and discover more defects with less effort and time by applying the pairwise data generation method. The pairwise data generation method in HCL OneTest Data helps to generate all the possible combinations of the item type values for each pair of item types. The use of this method decreases the number of the generated test data but covers all the possible combinations of the item type values.

For example, consider that there are three item types in a schema such as a list box with five values (zero, one, two, three, four), one radio button with two values (selected or unselected), and one check box with two values (selected or cleared). Therefore, the combination becomes 5x2x2 as the generated test data, which is equal to 20 values. These 20 values are required to cover all combinations of the item types of the schema without applying the pairwise data generation method. After you apply the pairwise data generation method, you can observe that the generated test data comprises all combinations of item type values for the three pairs of item types among the three item types. This pairing of item types results in 12 combinations of values of the generated test data.

For more information about how to set the pairwise data generation method in HCL OneTest Data, see Setting the pairwise data property.