Author:
Gogacz Tomasz,Marcinkowski Jerzy,Pieris Andreas
Abstract
AbstractThe chase procedure is a fundamental algorithmic tool in database theory with a variety of applications. A key problem concerning the chase procedure is all-instances chase termination: for a given set of tuple-generating dependencies (TGDs), is it the case that the chase terminates for every input database? In view of the fact that this problem is, in general, undecidable, it is natural to ask whether well-behaved classes of TGDs, introduced in different contexts, ensure decidability. It has been recently shown that the problem is decidable for the restricted (a.k.a. standard) version of the chase, and linear TGDs, a prominent class of TGDs that has been introduced in the context of ontological query answering, under the assumption that only one atom appears in TGD-heads. We provide an alternative proof for this result based on Monadic Second-Order Logic, which we believe is simpler that the ones obtained from the literature.
Publisher
Springer Science and Business Media LLC
Reference26 articles.
1. Aho Alfred V, Sagiv Yehoshua, Ullman Jeffrey D (1979) Efficient optimization of a class of relational expressions. ACM Trans. Database Syst 4(4):435–454
2. Baget J-F, Leclère M, Mugnier M-L, Salvat E (2011) On rules with existential variables: walking the decidability line. Artif Intell 175(9–10):1620–1654
3. Baget J-F, Mugnier M-L, Rudolph S, Thomazo M (2011) Walking the complexity lines for generalized guarded existential rules. In: IJCAI, 712–717
4. Bednarczyk B, Ferens R, Ostropolski-Nalewaja P (2020) All-instances oblivious chase termination is undecidable for single-head binary tgds. In: IJCAI, 1719–1725
5. Beeri C, Vardi MY (1984) A proof procedure for data dependencies. J ACM 31(4):718–741
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Non-Uniformly Terminating Chase: Size and Complexity;Proceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems;2022-06-12
2. Special Issue on Ontologies and Data Management: Part II;KI - Künstliche Intelligenz;2020-12