Using Synthetic Data for Enhanced Test Coverage

This guide discusses the application of synthetic data generation in software testing, particularly focusing on its role in maximizing test coverage. It outlines the growing interest among quality assurance professionals in synthetic data, driven by the need for data privacy and accelerated data provisioning in Agile and DevOps environments. The document details the GenRocket Test Data Automation (TDA) solution, which enables testers to create comprehensive synthetic test data that includes various combinations and permutations necessary for thorough testing. The guide presents a structured methodology that consists of four stages: defining the data model, designing the test data, deploying the test data, and managing test data projects. Each stage is explained in detail, emphasizing the importance of controlled, realistic, accurate, secure, stateful, scalable, and unique test data. The document also highlights the challenges faced in designing test data and how the GenRocket platform addresses these challenges effectively, ensuring that testers can generate the required test data efficiently.