conference paper · Euromicro Conference on Software Engineering and Advanced Applications (SEAA) · 2018

Identifying Technical Debt in Database Normalization Using Association Rule Mining

Mashel Albarak, Muna Al‐Razgan, Rami Bahsoon A

Cited by 3Abstract and details only

Abstract

In previous work, we explored a new context of technical debt that relates to database normalization design decisions. We claimed that database normalization debts are likely to be incurred for tables below the fourth normal form. We proposed a method to prioritize the tables that should be normalized based on their impact on data quality and performance. In this study, we propose a framework to identify normalization debt items (i.e. tables below the fourth normal form) by mining the data stored in each table. Our framework makes use of association rule mining to discover functional dependencies between attributes in a table, which will help determine the current normal form of that table and reveal debt tables. To illustrate our method, we use a case study from Microsoft, AdventureWorks database. The results revealed the applicability of our framework to identify debt tables.

Cite this paper

APA 7

Albarak, M., Al‐Razgan, M., & A, R. B. (2018). Identifying Technical Debt in Database Normalization Using Association Rule Mining. Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 437–441. https://doi.org/10.1109/seaa.2018.00077

MLA 9

Albarak, Mashel, et al. “Identifying Technical Debt in Database Normalization Using Association Rule Mining.” Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 2018, pp. 437–41, https://doi.org/10.1109/seaa.2018.00077.

Chicago

Albarak, Mashel, Muna Al‐Razgan, and Rami Bahsoon A. 2018. “Identifying Technical Debt in Database Normalization Using Association Rule Mining.” Euromicro Conference on Software Engineering and Advanced Applications (SEAA): 437–41. https://doi.org/10.1109/seaa.2018.00077.

Harvard

Albarak, M., Al‐Razgan, M. and A, R.B. (2018) ‘Identifying Technical Debt in Database Normalization Using Association Rule Mining’, Euromicro Conference on Software Engineering and Advanced Applications (SEAA), pp. 437–441. Available at: https://doi.org/10.1109/seaa.2018.00077.

BibTeX

@article{albarak2018identifying,
  title = {{Identifying Technical Debt in Database Normalization Using Association Rule Mining}},
  author = {Albarak, Mashel and Al‐Razgan, Muna and A, Rami Bahsoon},
  journal = {Euromicro Conference on Software Engineering and Advanced Applications (SEAA)},
  pages = {437--441},
  year = {2018},
  doi = {10.1109/seaa.2018.00077}
}

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