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BFASTDC: A Bitwise Algorithm for Mining Denial Constraints

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Database and Expert Systems Applications (DEXA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11029))

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Abstract

Integrity constraints (ICs) are meant for many data management tasks. However, some types of ICs can express semantic rules that others ICs cannot, or vice versa. Denial constraints (DCs) are known to be a response to this expressiveness issue because they generalize important types of ICs, such as functional dependencies (FDs), conditional FDs, and check constraints. In this regard, automatic DC discovery is essential to avoid the expensive and error-prone task of manually designing DCs. FASTDC is an algorithm that serves this purpose, but it is highly sensitive to the number of records in the dataset. This paper presents BFASTDC, a bitwise version of FASTDC that uses logical operations to form the auxiliary data structures from which DCs are mined. Our experimental study shows that BFASTDC can be more than one order of magnitude faster than FASTDC.

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Notes

  1. 1.

    We have adapted binary search for procedure \(\textsc {Predecessors}(A_j,k)\).

  2. 2.

    Available at: http://da.qcri.org/dc/.

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Authors and Affiliations

  1. Federal University of Technology, Toledo, Paraná, Brazil

    Eduardo H. M. Pena

  2. Federal University of Paraná, Curitiba, Brazil

    Eduardo Cunha de Almeida

Authors
  1. Eduardo H. M. Pena
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  2. Eduardo Cunha de Almeida
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Corresponding author

Correspondence to Eduardo H. M. Pena .

Editor information

Editors and Affiliations

  1. Clausthal University of Technology, Clausthal-Zellerfeld, Germany

    Sven Hartmann

  2. Victoria University of Wellington, Wellington, New Zealand

    Hui Ma

  3. Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  4. University of Regensburg, Regensburg, Germany

    Günther Pernul

  5. Johannes Kepler University, Linz, Austria

    Roland R. Wagner

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Pena, E.H.M., de Almeida, E.C. (2018). BFASTDC: A Bitwise Algorithm for Mining Denial Constraints. In: Hartmann, S., Ma, H., Hameurlain, A., Pernul, G., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2018. Lecture Notes in Computer Science(), vol 11029. Springer, Cham. https://doi.org/10.1007/978-3-319-98809-2_4

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  • DOI: https://doi.org/10.1007/978-3-319-98809-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98808-5

  • Online ISBN: 978-3-319-98809-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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