Data Flow Testing of SQL-Based Active Database Applications

The relevance of reactive capabilities as a unifying paradigm for handling a number of database features and applications is well-established. Active database systems have been used to implement the persistent data requirements of applications on several knowledge domains. They extend passive ones by automatically performing predefined actions in response to events that they monitor. These reactive abilities are generally expressed with active rules defined within the database itself. We investigate the use of data flow-based testing to identify the presence of faults in active rules written in SQL. The goal is to improve reliability and overall quality in this realm. Our contribution is the definition of a family of adequacy criteria, which require the coverage of inter-rule persistent data flow associations, and its effectiveness in various data flow analysis precisions. Both theoretical and empirical investigations show that the criteria have strong fault detecting ability at a polynomial complexity cost.