Handling failing queries over uncertain databases

A large number of applications manage uncertain data. Usually, users expect high quality results when they pose queries with strict conditions over these data. However, as they may not be clear about the contents of the databases that contain such data, these queries may be failing i.e., they may return no result or results that do not satisfy the expected degree of certainty. In this paper, we deal with this problem, in the field of uncertain databases, by proposing an efficient approach that identifies the parts of the failing query, called Minimal Failing Subqueries (mFSs), that are responsible of its failure. Our approach also computes, in the same time, a set of Maximal Succeeding Subqueries (XSSs) that represent non failing queries with a maximal number of predicates of the initial query. We demonstrate the impact of our proposal with a set of experiments on synthetic and real datasets.