By Monique Le Poncin

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Another point for further research is the use of non-deterministic constructs that are more appropriate for deductive databases, like these proposed in [GPZ01]. Apart from its theoretical interest, the transformation algorithm can be viewed as the basis of new evaluation strategies for a class of moded Datalog programs. It would therefore be interesting to carry out a careful performance comparison with related optimization techniques, which would reveal the strong and weak points of each approach.

Let P be a Choice DatalognS program, D a database and I an interpretation of PD . Then, CPD (I) is defined as follows: CPD (I) = {I ∪ {#p(L, e)} | p, L, e ∈ SI } A Transformation Technique for Datalog Programs 39 Some observations can be made about the CPD operator. The first one is that CPD preserves the previous computed atoms (it does not reject anything). The next thing is that CPD when applied to an interpretation I, chooses exactly one among all the possible p, L, e triples in SI , and returns the atom #p(L, e).

Rondogiannis, and M. Gergatsoulis The language we will be using in the rest of this paper as the target language of the transformation, is DatalognS extended with choice predicates. Notice that for every predicate symbol p (either IDB or EDB) a predicate #p is associated. Definition 3. A Choice DatalognS program is a DatalognS program which may contain choice atoms in the bodies of its clauses. An exposition of the formal semantics of Choice DatalognS is given in the Appendix of the paper. 5 The Transformation Algorithm In this section we provide a formal definition of the transformation algorithm.

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