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TL;DR

This paper introduces a novel approach to integrity checking in databases that tolerates errors and inconsistencies, challenging the traditional requirement for initial data integrity.

Contribution

It formally characterizes the property of inconsistency tolerance and demonstrates its validity for existing integrity checking methods.

Findings

Integrity checking methods can be correctly applied without initial data integrity.

Correct simplifications preserve consistency across updates.

Inconsistency tolerance broadens the applicability of integrity methods.

Abstract

We revisit integrity checking in relational and deductive databases with an approach that tolerates erroneous, inconsistent data. In particular, we relax the fundamental prerequisite that, in order to apply any method for simplified integrity checking, all data must initially have integrity. As opposed to a long-standing belief, integrity in the old state before the update is not needed for a correct application of simplification methods. Rather, we show that correct simplifications preserve what was consistent across updates. We formally characterize this property, that we call inconsistency tolerance, and state its validity for some well-known methods for integrity checking.