Simplified Integrity Checking for an Expressive Class of Denial Constraints

Data integrity is crucial for ensuring data correctness and quality and is maintained through integrity constraints that must be continuously checked, especially in data-intensive systems like OLTP. While DBMSs handle very simple cases of constraints (such as primary key and foreign key constraints) well, more complex constraints often require ad hoc solutions. Research since the 1980s has focused on automatic and simplified integrity constraint checking, leveraging the assumption that databases are consistent before updates. This paper presents program transformation operators to generate simplified integrity constraints, focusing on complex constraints expressed in denial form. In particular, we target a class of integrity constraints, called extended denials, which are more general than tuple-generating dependencies and equality-generating dependencies. One of the main contributions of this study consists in the automatic treatment of such a general class of constraints, encompassing the all the most useful and common cases of constraints adopted in practice. Another contribution is the applicability of the proposed technique with a “preventive” approach; unlike all other methods for integrity maintenance, we check whether an update will violate the constraints before executing it, so we never have to undo any work, with potentially huge savings in terms of execution overhead. These techniques can be readily applied to standard database practices and can be directly translated into SQL.

Authors

Institutions

Publication Details

Journal
Algorithms
Published
2025-02-20
DOI
https://doi.org/10.3390/a18030123
Primary Topic
Formal Methods in Verification
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simplified Integrity Checking for an Expressive Class of Denial Constraints

Davide Martinenghi
Algorithms
Formal Methods in Verification
article

Simplified Integrity Checking for an Expressive Class of Denial Constraints

Davide Martinenghi
article en

Abstract

Data integrity is crucial for ensuring data correctness and quality and is maintained through integrity constraints that must be continuously checked, especially in data-intensive systems like OLTP. While DBMSs handle very simple cases of constraints (such as primary key and foreign key constraints) well, more complex constraints often require ad hoc solutions. Research since the 1980s has focused on automatic and simplified integrity constraint checking, leveraging the assumption that databases are consistent before updates. This paper presents program transformation operators to generate simplified integrity constraints, focusing on complex constraints expressed in denial form. In particular, we target a class of integrity constraints, called extended denials, which are more general than tuple-generating dependencies and equality-generating dependencies. One of the main contributions of this study consists in the automatic treatment of such a general class of constraints, encompassing the all the most useful and common cases of constraints adopted in practice. Another contribution is the applicability of the proposed technique with a “preventive” approach; unlike all other methods for integrity maintenance, we check whether an update will violate the constraints before executing it, so we never have to undo any work, with potentially huge savings in terms of execution overhead. These techniques can be readily applied to standard database practices and can be directly translated into SQL.

AlgorithmsVol. 18(3)
Politecnico di Milano (IT)
Openalex Percentile: Top 96%
Formal Methods in Verification
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.