A structured model of consistency rules in after-state database testing

Database applications retrieve data from database for processing and store data to database for future use. In case, the data stored in the database is wrong or inconsistent, the database application may deliver wrong result even though its logic is correct. Ideally, database applications should ensure the consistency of the data to be stored. However, there is no way to check the data in the database is consistent or not. Revealing inconsistent data in database means the application fails to prevent such data being recorded in the first place. The After-State Database Testing (ASDT) framework aims to reveal such data that is inconsistent with the business rules and system specifications of a database application. One of the key steps in ASDT is to derive the data consistency rules from business rules, system specifications and database schema. It is mainly a manual process and, hence, is error-prone. In this article, we propose a structured model that enables us to generate these rules automatically with the intention to reduce resources and effort in ASDT