Computing Repairs Under Functional and Inclusion Dependencies via Argumentation

Abstract: We discover a connection between finding subset-maximal repairs for sets of functional and inclusion dependencies, and computing extensions within argumentation frameworks (AFs). We study the complexity of the existence of a repair and deciding whether a given tuple belongs to some (or every) repair, by simulating the instances of these problems via AFs. We prove that subset-maximal repairs under functional dependencies correspond to the naive extensions, which also coincide with the preferred and stable extensions in the resulting AFs. For inclusion dependencies, one needs a pre-processing step on the resulting AFs in order for the extensions to coincide. Allowing both types of dependencies breaks this relationship between extensions, and only preferred semantics captures the repairs. Finally, we establish that the complexities of the above decision problems are NP-complete and Pi_2^P-complete, when both functional and inclusion dependencies are allowed.