Integrated information systems and the data that flows across them aren’t static. So why should your test data be? Test data should be generated dynamically depending on the condition and state of data required at that moment or stage in the testing process. Accurate, controlled data that is dynamically generated in real time is far more useful for complex test environments than static data that is copied from a production environments or static data that is created in spreadsheets.
Testing complex, integrated systems is significantly more efficient when data that meets all test case requirements can be generated dynamically. For example, testing new account opening where the data needs to match very specific rules and conditions across many related applications. In this example not all data values, such as the new account numbers, are known at the start of the testing flow, so some of the system data values need to be retrieved or generated dynamically as part of the testing process.
GenRocket’s dynamic data architecture allows data generation decisions to be made in real time during a test run and newly created system data values, such as account numbers, can be queried and blended with synthetically generated data in real time. The typical alternative to GenRocket dynamic data generation is slow, front-end batch processing which forces testing teams to wait and limits their ability to test complex applications.
Dynamic Data – Handles Changing Data Conditions with Ease
GenRocket Dynamic Data
- Delivers test data that is unavailable in production data copies
- Controls test data generation based on rules & conditions
- Allows dynamic data decisions during a live test, accelerating test cycles
- Integrates test data directly into test automation frameworks in real time
Dynamic Data: An Example
Developers building and testing apps know that systems and data aren’t static – dynamically generated data can help to test every parameter and data exchange among systems interacting with the new app.
To create an insurance policy premium estimate, for example, data from many different systems is required such as customer systems, agent systems, insurance coverage systems and pricing systems. Attempting to pull production data copies from all these systems to simulate data combinations for every test case is a challenge. And, when dynamic data decisions need to be made as part of the testing workflow – such as whether or not a customer chooses monthly payments or annual payments – a dynamic vs. static test data solution is needed. GenRocket allows dynamic data decisions to be made, in real time, as part of the testing workflow, increasing coverage and reducing test data prep time and test cycle time.