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Test Author Guide
This guide describes how to create test assets in Rational® Test Automation Server and publish test assets to the Git repository that you have configured. This guide is intended for testers and test managers.
Generation of test data
To test an application, you use data that is passed to get real-time results. Since creating test data manually is time-consuming, you can use HCL® OneTest™ Data, an automated tool to generate random test data. You can generate the test data in various file formats.
Schema design overview
When you compose a schema by using HCL® OneTest™ Data you must define the types of the schema. You can also modify the types of the schema when you import any schema from local file system or use the schema generated by using any external resource.
Setting type properties
After you add types to your schema, you must set type properties.
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.

Test Author Guide
This guide describes how to create test assets in Rational® Test Automation Server and publish test assets to the Git repository that you have configured. This guide is intended for testers and test managers.
- Datasets overview
  A dataset provides tests with variable data during a run. The test that uses a dataset at run time replaces a value in the recorded test with variable test data that is stored in the dataset.
- Generation of test data
  To test an application, you use data that is passed to get real-time results. Since creating test data manually is time-consuming, you can use HCL® OneTest™ Data, an automated tool to generate random test data. You can generate the test data in various file formats.
  - Schema fabrication
    A schema is a graphical structure to represent different types of data. You can fabricate a schema for the generation of test data.
  - Schema design overview
    When you compose a schema by using HCL® OneTest™ Data you must define the types of the schema. You can also modify the types of the schema when you import any schema from local file system or use the schema generated by using any external resource.
    - Defining types
      For optimum test data generation, you must define entire data of schema into types. Types are the components of schemas. After you design schema in the schema designer, you must define entire data as types by using type designer.
    - Setting type properties
      After you add types to your schema, you must set type properties.
      - Value assignation for item types
        When you want to use specific item type values to generate the test data, then you can assign those values to the item types. To assign the values to any item type, you can either import the item type values or add the values manually.
      - Setting weightage values
        You can set weightage values for an item type to determine how often the value of that item type can be displayed in the generated test data.
      - Setting regular expressions
        When you want values of an item type to appear in a certain pattern in the generated test data, you must set the Regular Expression property for that item type in a defined schema.
      - Integrating sample files into a schema
        When you want to generate the test data, you must define a schema. HCL® OneTest™ Data provides sample files with item type values so that you can integrate the sample file into a schema by mapping it to any item type.
      - Adding JavaScript rules
        When you have a JavaScript file with defined rules to create values for any item type, then you can add the JavaScript rules to create the values for the mapped item type.
      - 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.
        Setting the pairwise data property
        When you want to generate an optimum test data that covers all possible combinations of item type values for each pair of item types in a schema, you can set the pairwise data property for those item types.
    - Designing a structural view of a schema
      To define how the item and group types are organized and are related to each other, you must design the structural view of a schema before generating the test data.
    - Setting restrictions
      When you define any item type for a schema, you can specify valid values to that type. You can define validations to the types by setting the restrictions.
    - Applying functions
      You can apply functions on the item types of a schema to define the component rules.
  - Test data generation from structured schemas
    When you want to test your application by using randomly generated test data, then you must generate the test data from the structured schemas.
  - Status of generated test data
    You can view the status of all the test data generated jobs performed in your project, on the Jobs page.

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.