Technical Debt Prioritization: State of the Art. A Systematic Literature Review
Journal article, 2020

Background. Software companies need to manage and refactor Technical Debt issues. Therefore, it is necessary to understand if and when refactoring of Technical Debt should be prioritized with respect to developing features or fixing bugs.

Objective. The goal of this study is to investigate the existing body of knowledge in software engineering to understand what Technical Debt prioritization approaches have been proposed in research and industry. Method. We conducted a Systematic Literature Review of 557 unique papers published until 2019, following a consolidated methodology applied in software engineering. We included 44 primary studies.

Results. Different approaches have been proposed for Technical Debt prioritization, all having different goals and proposing optimization regarding different criteria. The proposed measures capture only a small part of the plethora of factors used to prioritize Technical Debt qualitatively in practice. We present an impact map of such factors. However, there is a lack of empirical and validated set of tools.

Conclusion. We observed that Technical Debt prioritization research is preliminary and there is no consensus on what the important factors are and how to measure them. Consequently, we cannot consider current research conclusive. In this paper, we therefore outline different directions for necessary future investigations.

Technical Debt

Systematic Literature Review

Technical Debt Prioritization

Author

Valentina Lenarduzzi

Lappeenranta-Lahti University of Technology (LUT)

Terese Besker

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)

Davide Taibi

University of Tampere

Antonio Martini

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)

Francesca Arcelli Fontana

University of Milano-Bicocca

Journal of Systems and Software

0164-1212 (ISSN)

Vol. 171 110827

Subject Categories

Embedded Systems

Computer Science

Computer Systems

DOI

10.1016/j.jss.2020.110827

More information

Latest update

2/17/2021