Extending Query-Subquery Nets for Deductive Databases under the Well-Founded Semantics

We propose a method, called QSQN-WF, for evaluating queries to Datalog~ databases under the well-founded semantics. It is the first one that is set-at-a-time and strictly goal-directed w.r.t. SLS-resolution defined by Przymusinski. These properties are important for reducing accesses to the secondary storage and redundant computations. The first property distinguishes our method from the one based on SLG-resolution by Chen et al. (which is tuple-at-a-time). The second property distinguishes our method from the ones based on the magic-sets transformation by Kemp et al. and by Morishita, which use magic atoms not in the most appropriate way and are not strictly goal-directed w.r.t. SLS-resolution. Our method follows SLS-resolution, with Van Gelder’s alternating fixpoint semantics on the background, but uses a query-subquery net to implement tabulation and the set-at-a-time technique, reduce redundant computations and allow any control strategy within each iteration of the main loop. It is sound and complete w.r.t. the well-founded semantics and has PTIME data complexity.