The Girl Who Leapt Through Data Preparation Time

Automated tests of complex business logic often produce false positives and missed defects due to improperly prepared test data. In this talk, I'll demonstrate a practical approach to preparing data for automated tests using discount logic as an example: how to translate business rules into a compact dataset using test design techniques and how to organize data creation using a test framework. We'll also cover typical causes of instability: conditions falling within the wrong range, hidden parameter dependencies, “dirty” data between runs, and parallel runs. I'll also demonstrate how to implement data isolation and clean up to ensure repeatability and unambiguous error diagnostics.