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Test Author Guide
This guide describes how to create and edit test assets in HCL DevOps Test Hub (Test Hub), and then publish test assets to the remote Git repository that you have configured in your project. This guide is intended for testers and test managers.
Data fabrication
Test data is the core component of any application testing. It is very time-consuming to create test data manually. You can use the data fabrication feature in HCL DevOps Test Hub (Test Hub) to create realistic datasets for comprehensive testing scenarios. The feature provides data fabrication capabilities that can help you to generate synthetic data quickly and efficiently without the risk of data leaks or privacy issues.
Basic generators
You can use the built-in basic generators in Data definitions with or without modifying the default configurations of the generators.

Test Author Guide
This guide describes how to create and edit test assets in HCL DevOps Test Hub (Test Hub), and then publish test assets to the remote Git repository that you have configured in your project. This guide is intended for testers and test managers.
- Edit branch overview
  When you want to create or modify a test resource in HCL DevOps Test Hub (Test Hub), you must use an Edit branch. An Edit branch is a temporary branch of the branch in the project repository into which you want to add the created resource or edited resource.
- Data overview
  When you want to create realistic test scenarios that can simulate real-world or practical situations, you can use the data fabrication feature in HCL DevOps Test Hub (Test Hub) to fabricate test data. You can also create or edit datasets that pass variable data to tests at test run time.
- Prerequisites for working with Datasets and Data definition
  You can find information about the tasks that you need to perform before you work with datasets and Data definitions in HCL DevOps Test Hub (Test Hub).
- Working with Datasets on DevOps Test Hub
  You can find information about creating datasets in HCL DevOps Test Hub (Test Hub), applying a dataset classification, editing datasets, and managing datasets that are in your project repository.
- Data fabrication
  Test data is the core component of any application testing. It is very time-consuming to create test data manually. You can use the data fabrication feature in HCL DevOps Test Hub (Test Hub) to create realistic datasets for comprehensive testing scenarios. The feature provides data fabrication capabilities that can help you to generate synthetic data quickly and efficiently without the risk of data leaks or privacy issues.
  - Overview of data fabrication
    You can find information about an overview of the data fabrication feature that is available in HCL DevOps Test Hub (Test Hub).
  - Creating an empty Data definition
    You can create an empty Data definition in HCL DevOps Test Hub (Test Hub) as the first step to create a Data definition. After you save the empty Data definition to a folder in your project repository, you can edit the Data definition to add the different generators.
  - Creating a Data definition by importing fields from a CSV file
    When you want to create a Data definition in HCL DevOps Test Hub (Test Hub) with specific fields for the test data, you can import a CSV file that defines the specific fields. After you import fields to the Data definition, you can edit the Data definition and add generators for the specific fields before you generate the test data.
  - Creating a Data definition by importing fields from a dataset
    When you want to create a Data definition in HCL DevOps Test Hub (Test Hub) with specific fields for the test data, you can import the fields from a dataset. After you import fields to the Data definition, you can edit the Data definition and add generators for the specific fields before you generate the test data.
  - Creating a Data definition by importing fields from a database query
    You can create Data definition to generate a random test data that is required to run a test in HCL DevOps Test Hub (Test Hub) using the specific database fields.
  - Saving a Data definition by adding basic generators with their default settings
    After you create a Data definition in HCL DevOps Test Hub (Test Hub), you must add the basic generators with their default settings and save the Data definition before you can generate test data.
  - Saving a Data definition by adding basic generators with their modified settings
    After you create an empty Data definition in HCL DevOps Test Hub (Test Hub), you must add the basic generators with their modified settings, and save the Data definition before you can generate test data.
  - Modifying a Data definition
    After you create and publish a Data definition in HCL DevOps Test Hub (Test Hub), you can modify the fields or the configuration of the generators in an existing Data definition when you want to change the structure of the test data.
  - Publishing changes in an Edit branch
    After you create or modify a Data definition, a generator, or a generator category in a project in HCL DevOps Test Hub (Test Hub), you can publish all the changes that are in an Edit branch to the branch in the project repository. After which, other members in the project can view and use the test resources. The Edit branch automatically disappears from the Branch list of the Data page and the changes made to the project are merged into the previously selected branch name.
  - Viewing a Data definition and its details
    You can view the contents of a Data definition on the Data page in HCL DevOps Test Hub (Test Hub).
  - Deleting Data definitions
    You can delete Data definitions to remove them when the data definitions are outdated or no longer relevant to the current project. Additionally, when Data definitions contain errors or inaccuracies that can lead to misleading or incorrect fabricated data, then you might want to remove them. This ensures that the project remains clutter-free, optimizes the performance of HCL DevOps Test Hub (Test Hub), and reduces storage requirements.
  - Basic generators
    You can use the built-in basic generators in Data definitions with or without modifying the default configurations of the generators.
    - Parameters of the Address generator
      After you add the Address generator in a field of a Data definition, you can customize the existing configurations of the field.
    - Parameters of the Boolean generator
      After you add the Boolean generator in a field of a Data definition, you can customize the existing configurations of the field.
    - Parameters of the Dataset generator
      After you add the Dataset generator in a field of a Data definition, you can customize the existing configurations of the field.
    - Parameters of the DateTime generator
      After you add the DateTime generator in a field of a Data definition, you can customize the existing configurations of the field.
    - Parameters of the Enumerator generator
      After you add the Enumerator generator in a field of a Data definition, you can customize the existing configurations of the field.
    - Parameters of the Function generator
      After you add the Function generator in a field of a Data definition, you can customize the existing configurations of the field.
    - Parameters of the Name generator
      After you add the Name generator in a field of a Data definition, you can customize the existing configurations of the field.
    - Parameters of the Number generator
      After you add the Number generator in a field of a Data definition, you can customize the existing configurations of the field.
    - Parameters of the Phone generator
      After you add the Phone generator in a field of a Data definition, you can customize the existing configurations of the field.
    - Parameters of the Regex generator
      After you add the Regex generator in a field of a Data definition, you can customize the existing configurations of the field.
    - Parameters of the String generator
      After you add the String generator in a field of a Data definition, you can customize the existing configurations of the field.
    - Parameters of the Text generator
      After you add the Text generator in a field of a Data definition, you can customize the existing configurations of the field.
    - Parameters of the UUID generator
      After you add the UUID (Universal Unique Identifier) generator in a field of a data definition, you can customize the existing configurations of the field.
  - Generation of test data
    You can use the data fabrication feature in HCL DevOps Test Hub (Test Hub) to create realistic datasets for comprehensive testing scenarios. You can generate the test data as the Comma-Separated Values (CSV) files that is saved in your system. You can then use these files to replace any existing datasets in a test during the run time. If a dataset is already associated with a test, you can replace the dataset at runtime with the dataset that is created from the data fabrication feature of Test Hub. This allows you to integrate the generated test data into your test execution process, and you can ensure that your tests are performed with the secure and realistic data.
  - Management of custom generators
    HCL DevOps Test Hub (Test Hub) provides flexibility to create, modify, and delete custom generators. You can access and modify custom generators to suit your specific data requirements in the Catalog page.
  - Management of custom categories
    HCL DevOps Test Hub (Test Hub) provides flexibility to create and delete custom categories in the Catalog page. The Catalog page displays both the basic and custom categories of generators in a project.

Basic generators

You can use the built-in basic generators in Data definitions with or without modifying the default configurations of the generators.

The Data fabrication feature of HCL DevOps Test Hub (Test Hub) contains a collection of built-in data generators available in the Basic category on the Catalog tab of a Data definition.

Basic generators are the built-in generators of the Data fabrication feature of Test Hub that you can use to generate diverse test data. These generators provide commonly used data types and patterns that you can select and configure in a Data definition to generate realistic test data.

The basic generators that you can use in Test Hub are as follows:

Address
Boolean
Dataset
DateTime
Enumerator
Function
Name
Number
Phone
Regex
String
Text
UUID

Every basic generator has unique parameters with default features. When you click a basic generator that is added as a field in the Data definition, the corresponding unique parameters with their default configuration are displayed in a new dialog. The new dialog is named after the generator that you select.

You can change the default configurations of any basic generator only when it is added as a field in a Data definition. You can use the changed configurations for any basic generator in the Data definition by saving the Data definition. The changed configuration is applicable only in the Data definition that contains it and is not available for use from the Catalog tab.

If you want to save the modified generators, you can create them as custom generators and save them in a custom category in the Catalog tab.

You can find details about the parameters in each of the basic generators along with their default configuration and the configurations that you can change or modify. The parameters of the basic generators are as follows: