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Proceedings of SAI Intelligent Systems Conference

IntelliSys 2018: Intelligent Systems and Applications pp 1–19Cite as

A Query Inversion Technique for Detection of Unexpected Values in Relational Databases

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 869))

Abstract

Day by day data volumes are increasing, and most of the data are stored in the databases after manual transformations and derivations. The behavior of those stored data is unpredictable. Furthermore, the data are collected from various sources such as physical, geological, environmental, chemical, and biological. A relational database management system (RDBMS) provides a high level data interface. Inside RDBMS sources and intermediate data items are relations, tuples, and attributes. In the context of data provenance, this paper describes how data are produced. When data needs to be retrieved from RDBMS using queries, sometimes it is necessary to check the output data product back to its source values if that particular output seems to have an unexpected value. The aim of this paper is to show the source values for output data using query inversion approach, and to propose the technique for creating an inverse query for queries with aggregation functions, multiple (join, set) operations, and sub-queries.

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Acknowledgements

We would like to thank all the colleagues at the School of Software Engineering of NRU HSE for their feedback and useful recommendations that contributed to bringing this paper to its final form.

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Authors and Affiliations

  1. Faculty of Computer Science, School of Software Engineering, National Research University Higher School of Economics (NRU HSE), Kochnovskiy Proezd 3, 125319, Moscow, Russian Federation

    Md. Salah Uddin

  2. School of Software Engineering, National Research University Higher School of Economics, Moscow, Russian Federation

    Dmitry V. Alexandrov

  3. Chair of Innovative Entrepreneurship, Bauman Moscow State Technical University, Moscow, Russian Federation

    Dmitry V. Alexandrov

Authors
  1. Md. Salah Uddin
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  2. Dmitry V. Alexandrov
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Corresponding author

Correspondence to Md. Salah Uddin .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, UK

    Rahul Bhatia

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Salah Uddin, M., Alexandrov, D.V. (2019). A Query Inversion Technique for Detection of Unexpected Values in Relational Databases. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 869. Springer, Cham. https://doi.org/10.1007/978-3-030-01057-7_1

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