Incorporating Stratified Negation into Query-Subquery Nets for Evaluating Queries to Stratified Deductive Databases

Abstract

Most of the previously known evaluation methods for deductive databases are either breadth-first or depth-first (and recursive). There are cases when these strategies are not the best ones. It is desirable to have an evaluation framework for stratified Datalog ¬ that is goal-driven, set-at-a-time (as opposed to tuple-at-atime) and adjustable w.r.t. flow-of-control strategies. These properties are important for efficient query evaluation on large and complex deductive databases. In this paper, by incorporating stratified negation into so-called query-subquery nets, we develop an evaluation framework, called QSQN-STR, with such properties for evaluating queries to stratified Datalog ¬ databases. A variety of flow-of-control strategies can be used for QSQN-STR. The generic evaluation method QSQN-STR for stratified Datalog ¬ is sound, complete and has a PTIME data complexity.