期刊名称：Bulletin of the Technical Committee on Data Engineering
出版年度：2018
卷号：41
期号：1
页码：39
出版社：IEEE Computer Society
摘要：Data provenance approaches track how the answer to a database query derive from input items; however, priorapproaches used “positive” provenance and were not directly usable for explaining “expected” but missinganswers. A similar problem arises with the failure of integrity constraints. Our perspective is to offer expla-nations via possible (minimal) repairs using provenance. This is useful for debugging, repairing, and cleaningdatabases. In this paper, we introduce a novel approach to this problem for both missing/erroneous answers andintegrity failures. The approach uses recent advances in provenance for first-order model checking.
