A systematic literature review on Technical Debt prioritization: Strategies, processes, factors, and tools

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 2020, 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. (c) 2020 Elsevier Inc. All rights reserved.

Automated summary

This study investigated existing knowledge and methods in software engineering regarding prioritization of technical debt, finding different approaches but a lack of empirical and validated toolsets. Future research directions include further investigation into important factors and measurement methods.