A Model-Based Approach to Generate Dynamic Synthetic Test Data: A Conceptual Model
Chao Tan, Razieh Behjati, Erik Arisholm · 2019
Having access to high-quality test data is an important requirement to ensure effective cross-organizational integration testing in the Norwegian public sector. Evogent is a PhD project that aims to provide model-based solutions for generating synthetic test data that is statistically representative of real (reference) population, and is dynamic in the same way that the actual population is. This project is carried out in collaboration with the Modernization of the National Registry project (MF) within the Norwegian Tax Department, which serves as our case study. In this paper, we present a conceptual model and related algorithms for event generation.