Published August 13, 2020 | Version v1
Journal article Open

Exploring the Relation between Technical Debt Principal and Interest: An Empirical Approach

  • 1. Department of Computer Science, Institute for Mathematics, Computer Science and AI, University of Groningen, Netherlands
  • 2. Department of Chemistry, International Hellenic University, Kavala, Greece
  • 3. Department of Applied Informatics, University of Macedonia, Greece
  • 4. School of Informatics, Aristotle University of Thessaloniki, Greece



The cornerstones of technical debt (TD) are two concepts borrowed from economics: principal and interest. Although in economics the two terms are related, in TD there is no study on this direction so as to validate the strength of the metaphor.


We study the relation between Principal and Interest, and subsequently dig further into the ‘ingredients’ of each concept (since they are multi-faceted). In particular, we investigate if artifacts with similar levels of TD Principal exhibit a similar amount of TD Interest, and vice-versa.


To achieve this goal, we performed an empirical study, analyzing the dataset using the Mantel test. Through the Mantel test, we examined the relation between TD Principal and Interest, and identified aspects that are able to denote proximity of artifacts, with respect to TD. Next, through Linear Mixed Effects (LME) modelling we studied the generalizability of the results.


The results of the study suggest that TD Principal and Interest are related, in the sense that classes with similar levels of TD Principal tend to have similar levels of Interest. Additionally, we have reached the conclusion that aggregated measures of TD Principal or Interest are more capable of identifying proximate artifacts, compared to isolated metrics. Finally, we have provided empirical evidence on the fact that improving certain quality properties (e.g., size and coupling) should be prioritized while ranking refactoring opportunities in the sense that high values of these properties are in most of the cases related to artifacts with higher levels of TD Principal.


The findings shed light on the relations between the two concepts, and can be useful for both researchers and practitioners: the former can get a deeper understanding of the concepts, whereas the latter can use our findings to guide their TD management processes such as prioritization and repayment.



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SDK4ED – Software Development toolKit for Energy optimization and technical Debt elimination 780572
European Commission