Abstract
This paper proposes a model, called Deductive High-Level Petri Net (DHLPN), for which syntax and semantics are derived from High-Level Petri Nets (HLPN). This model serves as a means for capturing the behavior of deductive databases and for implementing an efficient recursive query evaluation. The efficiency of the proposed query evaluation technique lies in the fact that the order of generated tokens (ground predicates) is never greater than the initial set of tokens. We will compare this interpretation technique to the well known interpretation techniques that are magic-sets and envelopes. We will also show that it is possible to give a necessary and sufficient structural condition for the existence of query answers, not taking account of the extensional database.
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Barkaoui, K., Maïzi, Y. (1997). Efficient answer extraction of deductive databases modeled by HLPN. In: Hameurlain, A., Tjoa, A.M. (eds) Database and Expert Systems Applications. DEXA 1997. Lecture Notes in Computer Science, vol 1308. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0022042
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DOI: https://doi.org/10.1007/BFb0022042
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