A new model with invariant-based language effectively handles data-dri
ven rules in databases and uses the rules' inherent semantic propertie
s 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 langu
ages, can follow data-driven rules' semantic properties. Such rules ar
e activated by modifications of data items in a database, and they pla
y an important role in many applications that maintain complex relatio
nships between data items or interdependencies between parts of the da
tabase. Applications include expert systems, real-time databases, simu
lations, and decision-support systems. The authors present requirement
s for choosing an adequate programming style that uses data-driven rul
es. 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 invarian
t-based language as a viable solution.