High-quality test data ensures good tests and quality software. However, collecting it is difficult due to a variety of challenges.

Effective TDM processes should meet several attributes such as availability, speed, quality, simplicity, and versatility. Lets take a look at how these attributes are addressed through different options: 1. Automated test data generation.

Automated Test Data Generation

Using third-party tools that understand back-end systems helps build up test data efficiently. These tools pump in data like a real-time scenario and are capable of delivering diverse, voluminous test data that enables maximum coverage. They are highly accurate because they are able to take into account the complexity of back-end systems and how they function.

Creating test data manually can be extremely time-consuming and expensive. It also does not detect all the subtle bugs that can only be detected by actual data created by the application being tested.

Another alternative is to use a query-based approach to create test data. This involves writing a query and injecting it into the database to populate it with the test data required. This is a faster and easier method but can result in erroneous output. A more reliable approach is to use a data generation tool such as Generator, an open-source framework that supports multiple databases and formats, including XML, YAML, CSV, flat files, and Excel.

Automated Test Data Sub setting

To avoid relying on masking alone, which is often impractical for large-scale testing needs and erodes data representation, test and development teams must provision full-sized production databases. This can drive up costs in infrastructure and error resolution as well as slow down the overall testing process.

GenRocket provides a high-speed, enterprise-class test data sub setting solution that delivers consistent sets of table data to testers while maintaining referential integrity. Using a web-based test data on demand portal, testers submit requests for specific test case attributes. The system will search back-end systems, find and clone the required data, then provision it to the test environment.

For example, with a GenRocket system, a customer can request a set of data that includes a combination of credit card payment transaction records and future scenario data for black box testing. The result is 100% functional variation coverage, plus effective negative testing and a faster overall test process.

Automated Test Data Management

As part of software testing solutions, these tools provide a way to automate processes that provision test data to applications. Whether for unit tests, integration, or performance tests, accurate and consistent data is essential to reliable testing results.

For many software testing environments, ensuring the right data is available for all tests, without requiring access to production systems, is challenging. These tools can help overcome that challenge by providing ways to extract and clone data, a subset that data for specific testing types, and make that data available on demand.

For example, for service/API testing, GenRocket provides the ability to define and automatically generate realistic test data scenarios that can be masked, transformed, extended, and subset, and then automatically provisioned to application testing environments on demand. This helps to reduce infrastructure costs and ensures compliance with data privacy regulations. The tools in this category also include a variety of other capabilities such as database cloning, data profiling, and intelligently sized data.

Automated Test Data Refresh

Modern software testing requires fast, reliable, and secure access to real data that supports code development, automated test scripts, performance tests, and data compliance. Test Data Management (TDM) is the process of providing controlled data access to modern teams throughout the SDLC.

TDM tools allow for a streamlined synchronization of multiple sources of data from production, versioning copies, sensitive data discovery and masking, multi-cloud distribution, and scalable data provisioning to support modern delivery processes.