Technical debt in relational database normalization

The technical debt metaphor describes trade-offs between short-term goals and applying optimal design and development practices. In this thesis, we explore the concept of technical debt in database design and provide an understanding of its causes and types. We focus on a specific type of debt related to database normalization. Database normalization is one of the main principles for designing relational databases, with the objective of improving data and system qualities. However, developers often ignore the normalization process due to the time and expertise it requires, introducing technical debt into the system. Paying the debt and refactoring the database for normalization can be costly, if the benefits of the exercise are not justified. We consider database normalization debts are likely to be incurred for tables below the fourth normal form. To manage the debt, we propose a systematic framework to rank the candidate tables for normalization to the fourth normal form. The ranking is based on the tables estimated impact on data quality, performance, maintainability, and cost. We also propose two approaches to identify potential debt tables below fourth normal form. The techniques are evaluated using an industrial case study of a database-backed web application for human resource management. The results show that the debt-aware approach can provide an informed justification for the inclusion of critical tables to be normalized, while reducing the effort and cost of normalization.