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Research Article | Open Access |

CdbNorm: An Efficient Library for Automatic Database Normalization

Author 1: Ivan Piza-Davila Author 2: Fernando Gutierrez-Preciado Author 3: Victor Ortega-Guzman Author 4: Mildreth Alcaraz-Mejia
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 17, No. 3 · Published 2026

DOI: https://doi.org/10.14569/IJACSA.2026.0170311

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Abstract

This study introduces CdbNorm, a library that provides efficient implementations of the first three normal forms of relational database normalization. CdbNorm makes it quick and straightforward for a data analyst to divide a large dataset into smaller tables free from database anomalies (insert, update, and delete) and duplicate data. This study describes each of the steps of our normalization algorithm, which includes the discovery of functional dependencies and the population of output normalized datasets. We evaluate the accuracy and efficiency of our algorithm with databases introduced in prior papers and with large datasets available online.

Keywords

Database normalization functional dependency normal form 1NF 2NF 3NF

How to Cite this Article

Piza-Davila, I., Gutierrez-Preciado, F., Ortega-Guzman, V., & Alcaraz-Mejia, M. (2026). CdbNorm: An Efficient Library for Automatic Database Normalization. International Journal of Advanced Computer Science and Applications, 17(3). https://doi.org/10.14569/IJACSA.2026.0170311

Piza-Davila, Ivan, et al.. "CdbNorm: An Efficient Library for Automatic Database Normalization." International Journal of Advanced Computer Science and Applications, vol. 17, no. 3, 2026, https://doi.org/10.14569/IJACSA.2026.0170311.

@article{Piza-Davila2026,
  title     = {CdbNorm: An Efficient Library for Automatic Database Normalization},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {17},
  number    = {3},
  year      = {2026},
  publisher = {The Science and Information Organization},
  author    = {Ivan Piza-Davila and Fernando Gutierrez-Preciado and Victor Ortega-Guzman and Mildreth Alcaraz-Mejia},
  doi       = {10.14569/IJACSA.2026.0170311},
  url       = {https://doi.org/10.14569/IJACSA.2026.0170311}
}

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