Maintaining data-driven rules in databases

A new model with invariant-based language effectively handles data-driven rules in databases and uses the rules´ inherent semantic properties and supporting mechanisms to meet high-level language requirements. It is an extension of the basic PARDES model developed by Opher Etzion in 1990 to support derivations and integrity constraints in databases. The model´s invariant-based language, unlike other programming languages, can follow data-driven rules´ semantic properties. Such rules are activated by modifications of data items in a database, and they play an important role in many applications that maintain complex relationships between data items or interdependencies between parts of the database. Applications include expert systems, real-time databases, simulations, and decision-support systems. The authors present requirements for choosing an adequate programming style that uses data-driven rules. These requirements are based on software-engineering criteria such as compatibility with a high-level language and verifiability of the rule language. The authors show that contemporary database programming styles fail to meet these requirements, and they present the invariant-based language as a viable solution