Repair checking in inconsistent databases: algorithms and complexity

Managing inconsistency in databases has long been recognized as an important problem. One of the most promising approaches to coping with inconsistency in databases is the framework of database repairs, which has been the topic of an extensive investigation over the past several years. Intuitively, a repair of an inconsistent database is a consistent database that differs from the given inconsistent database in a minimal way. So far, most of the work in this area has addressed the problem of obtaining the consistent answers to a query posed on an inconsistent database. Repair checking is the following decision problem: given two databases r and r', is r' a repair of r? Although repair checking is a fundamental algorithmic problem about inconsistent databases, it has not received as much attention as consistent query answering. In this paper, we give a polynomial-time algorithm for subset-repair checking under integrity constraints that are the union of a weakly acyclic set of local-as-view (LAV) tuple-generating dependencies and a set of equality-generating dependencies. This result significantly generalizes earlier work for subset-repair checking when the integrity constraints are the union of an acyclic set of inclusion dependencies and a set of functional dependencies. We also give a polynomial-time algorithm for symmetric-difference repair checking, when the integrity constraints form a weakly acyclic set of LAV tgds. After this, we establish a number of complexity-theoretic results that delineate the boundary between tractability and intractability for the repair-checking problem. Specifically, we show that the aforementioned tractability results are optimal; in particular, subset-repair checking for arbitrary weakly acyclic sets of tuple-generating dependencies is a coNP-complete problem. We also study cardinality-based repairs and show that cardinality-repair checking is coNP-complete for various classes of integrity constraints encountered in database design and data exchange.