Publication
Title
Detecting errors in numeric attributes
Author
Abstract
To detect errors in numeric data, this paper proposes numeric functional dependencies (NFDs), a class of dependencies that allow us to specify arithmetic relationships among numeric attributes. We show that NFDs subsume conditional functional dependencies (CFDs); hence, we can catch data inconsistencies, numeric or not, in a uniform logic framework by using NFDs as data quality rules. Better still, NFDs do not increase the complexity of reasoning about data quality rules. We show that the satisfiability and implication problems for NFDs remain NP-complete and coNP-complete, respectively, the same as their counterparts for CFDs. Moreover, NFDs can be implemented in SQL and hence, error detection can be readily supported by DBMS. In addition, we show that NFDs and CFDs can be extended across multiple tables, without increasing the complexity of static analyses and error detection.
Language
English
Source (journal)
Lecture notes in computer science. - Berlin, 1973, currens
Publication
Berlin : 2014
ISSN
0302-9743 [print]
1611-3349 [online]
Volume/pages
8485(2014), p. 125-137
ISI
000342838500015
Full text (Publishers DOI)
Full text (publishers version - intranet only)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 02.09.2014
Last edited 03.05.2017
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