Home
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.
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.
Deleting a dataset
You can delete the dataset when it is not required in your test environment.

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.
  - Creating a dataset
    You can create datasets in HCL DevOps Test Hub (Test Hub) to replace the values of existing dataset with the values of new dataset during a test or schedule run.
  - Creating a dataset by using a CSV file
    When you use variable data that is contained in a CSV file, you can import the data from the CSV file and create a dataset in HCL DevOps Test Hub (Test Hub).
  - Creating a dataset by using a Data definition
    When you created a Data definition in HCL DevOps Test Hub (Test Hub) to fabricate test data, you can create a dataset by using the Data definition.
  - Creating a dataset by using a database query
    When you use variable data that is contained in a database, you can create a database query to import the required data from a database and use the data that is present in the database query to create a dataset in HCL DevOps Test Hub (Test Hub).
  - Editing a dataset
    You can add, modify, remove, import, or export data from a dataset.
  - Dataset encryption
    Encrypted datasets are useful when you want to run tests that contain confidential information such as a set of passwords or account numbers.
  - Publishing changes in datasets
    After you create, edit, or encrypt datasets in HCL DevOps Test Hub (Test Hub), you can publish all changes made to a dataset to a branch in the project. After you publish the dataset, other members in the project can use your dataset in their test run, if required. The Edit branch automatically disappears from the Branch list and changes made to the datasets are merged into the selected branch of the project repository.
  - Viewing a dataset
    When test assets includes datasets, you can view the contents of a dataset from HCL DevOps Test Hub (Test Hub). The datasets residing in the Git repository are listed in the Datasets page.
  - Deleting a dataset
    You can delete the dataset when it is not required in your test environment.
  - Viewing an encrypted dataset
    You can use the Dataset page to view the contents of an encrypted dataset from HCL DevOps Test Hub (Test Hub).
  - Changing classification for an encrypted dataset
    To move the encrypted dataset from one classification to another dataset in HCL DevOps Test Hub (Test Hub), you can change the classification for an encrypted dataset.
  - Managing an encrypted dataset
    You can use encrypted datasets to limit access to confidential information such as account number or passwords. You can arrange data by an appropriate category so that project members can use datasets more effectively in certain tests and protect them.
- 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.

Deleting a dataset

You can delete the dataset when it is not required in your test environment.

Before you begin

You must have completed the following tasks:

Ensured that you are assigned a role as a Viewer, Tester, or Project Owner in the project.
Created at least one dataset in your Git repository that you have configured.

About this task

You can delete datasets in Test Hub in the following scenarios:

Datasets that you created in the desktop clients and that are cloned to the repository in your project on Test Hub.
Datasets that you created in Test Hub and that are published to the repository in your project.
Datasets that are in the .csv file format.

You cannot delete the following datasets:

Datasets that you created or edited in Test Hub and that are not published to the repository in your project.
Datasets that are in the .sit file format.

Procedure

Log in to Test Hub.

The team space that contains your project is displayed.
Click Active projects > My projects > project_name to open the project that contains the test assets.

The Overview page of the project is displayed.
Click Author > Data.

The Data page and the Data navigator panel are displayed.
Select the branch that contains your project with the datasets that you want to edit.

The projects in the selected branch are displayed in the Data navigator panel. The datasets are listed under the folder you created to contain the dataset within a logical folder named as Datasets.
Right-click the dataset in the data navigator, and then click the Delete option.
Select your action to either select an existing Edit branch or create an Edit branch:
- Perform the following steps to select an existing Edit branch:
  1. Select an Edit branch from the Select branch list if Edit branches already exist in the selected branch of the repository.
  2. Click Ok.
- Perform the following steps to create the Edit branch:
  1. Select Create new branch.
  2. Enter a name for the Edit branch.
  3. Click Save.
Perform the following steps in the Delete <Dataset> dialog that is displayed, where <Dataset> displays the name of the selected dataset.
1. Select the option to publish the deletion from the Edit branch to the main branch.
2. Click Delete.
The selected dataset is deleted and the deletion is published from the edit branch to the main branch.

Results

You deleted a dataset.