Software Engineering and Architecture

Software Engineering and Architecture Group (SEARCH) > CS > Bernoulli Institute > FSE > RUG

Technical Debt

General Introduction

Technical debt, which refers to immature software artifacts that fail to meet the required level of quality, has recently been attracted increasing attention from both academic and industry in software engineering field. To date, little work has been done on technical debt at architecture level, i.e., architectural debt. In the short term, architectural debt may be incurred to fulfill specific business advantages; and, in the long term, architectural debt can to a great extent reduce the maintainability and evolvability of a software system. Our group focuses on architectural debt management which main goal is to achieve the balance between value and cost of architectural debt. Until now, we have proposed a conceptual model of architectural debt and an architectural technical debt management process applying this ATD conceptual model in order to facilitate the decision-making in a value-oriented perspective of architecting. Our current work is focusing on identifying, measuring, and documenting architectural debt.

Research Projects

  • STAND (Semantic-enabled collaboration Towards Analysis, Negotiation and Documentation on distributed requirements engineering)
    Grant: AFR
    Period: 2010-2014
  • SDK4ED (Software Development ToolKit for Energy Optimization and Technical Debt Elimination)
    Grant: H2020 - N. 780572
    Period: 2018-2021

Tools and Demos

For tools and demos regarding this research area, please visit our Resources page.

Recent Publications

(For more publications go to the publications page for Technical Debt.)

  1. Paris Avgeriou, Davide Taibi, Apostolos Ampatzoglou, Francesca Arcelli Fontana, Terese Besker, Alexander Chatzigeorgiou, Valentina Lenarduzzi, Antonio Martini, Athanasia Moschou, Ilaria Pigazzini, Nyyti Saarimaki, Darius Sas, Saulo S. de Toledo and Angeliki-Agathi Tsintzira (2021) An Overview and Comparison of Technical Debt Measurement Tools. In IEEE Software, pages 38(3):61-71. IEEE. (URL) (BibTeX)
  2. Darius Sas, Paris Avgeriou, Ronald Kruizinga and Ruben Scheedler (2021) Exploring the Relation Between Co-changes and Architectural Smells. In SN Computer Science, 2(1):13. Springer. (URL) (BibTeX)
  3. Georgios Digkas, Apostolos Ampatzoglou, Alexander Chatzigeorgiou, Paris Avgeriou, Oliviu Matei and Robert Heb (2021) The Risk of Generating Technical Debt Interest: A Case Study. In SN Computer Science, 2(1):12. Springer. (URL) (BibTeX)
  4. Daniel Feitosa, Apostolos Ampatzoglou, Antonios Gkortzis, Stamatia Bibi and Alexander Chatzigeorgiou (2020) CODE reuse in practice: Benefiting or harming technical debt. In Journal of Systems and Software, 167:110618.. (URL) (BibTeX)
  5. Jie Tan, Daniel Feitosa and Paris Avgeriou (2020) An Empirical Study on Self-Fixed Technical Debt. In Proceedings of the 3rd International Conference on Technical Debt (TechDebt '20). Seoul, Republic of Korea. ACM. (BibTeX)
  6. Jie Tan, Daniel Feitosa and Paris Avgeriou (2020) Investigating the Relationship between Co-occurring Technical Debt in Python. In Proceedings of the 46th EUROMICRO conference on Software Engineering and Advanced Applications (SEAA '20). Portoroz, Slovenia. IEEE. (BibTeX)