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.

You can use the data fabrication feature of Test Hub to generate the test data in the following two ways:
  • Generation of data from a Data definition
  • Generation of data from history of a Data definition

Generation of data from a Data definition

Data definitions are fundamental building blocks that are used to define data structures and generate test data. You can create Data definitions and specify the characteristics of the data that you need for your testing scenarios. You can choose from the built-in data generators, configure new generators, define rules, and set restrictions and distribution for the Data definitions. You can then use the Data definitions to generate synthetic test data that closely resembles real-world scenarios.

You can use customized Data definitions to generate diverse test data that closely resembles real-world scenarios. You can preview a test data to ensure whether the data is in the expected format. You can have a glimpse of the generated test data that can help you to identify any potential issues, inconsistencies, or errors in the Data definitions. If you modify a Data definition but not save it, you can still preview the corresponding test data. However, you can generate the test data only after you save the Data definition. You can add multiple fields in a Data definition without associating them with generators and save the Data definition. However, you cannot preview or generate test data for such a Data definition.
Note: While configuring the generator parameters for a field in a Data definition, you must use the Allowed option of the Duplicates field of the generator with caution, particularly when you configure the data generator with a narrow criteria for data generation. If you enable the Allowed option in scenarios where duplications are not feasible within the defined criteria, then the preview or generation of test data might not be successful.

Also, the data distribution in a generated test data closely aligns with the configured weightage that you provide in the Distribution field of the generator. Therefore, the accuracy of the test data improves as more number of records are generated. See Basic generators.

See Generating data from a Data definition.

Generation of data from history of a Data definition

When you open a Data definition in Test Hub, you can view the history of the Data definition. You can view the historical details of all the previously generated test data for the Data definition. You can use this feature of Data fabrication to regenerate a test data for testing purposes.

See Generating data from history of a Data definition.