Technical debt and agile software development practices and processes: An industry practitioner survey
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Abstract (arXiv)
Context: Contemporary software development is typically conducted in dynamic, resource-scarce environments that are prone to the accumulation of technical debt. While this general phenomenon is acknowledged, what remains unknown is how technical debt specifically manifests in and affects software processes, and how the software development techniques employed accommodate or mitigate the presence of this debt. Objectives: We sought to draw on practitioner insights and experiences in order to classify the effects of agile method use on technical debt management. We explore the breadth of practitioners' knowledge about technical debt; how technical debt is manifested across the software process; and the perceived effects of common agile software development practices and processes on technical debt. In doing so, we address a research gap in technical debt knowledge and provide novel and actionable managerial recommendations. Method: We designed, tested and executed a multi-national survey questionnaire to address our objectives, receiving 184 responses from practitioners in Brazil, Finland, and New Zealand. Results: Our findings indicate that: 1) Practitioners are aware of technical debt, although, there was under utilization of the concept, 2) Technical debt commonly resides in legacy systems, however, concrete instances of technical debt are hard to conceptualize which makes it problematic to manage, 3) Queried agile practices and processes help to reduce technical debt; particularly, techniques that verify and maintain the structure and clarity of implemented artifacts. Conclusions: The fact that technical debt instances tend to have characteristics in common means that a systematic approach to its management is feasible. However, notwithstanding the positive effects of some agile practices on technical debt management, competing stakeholders' interests remain a concern.(Abridged)
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Apr 2021.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 1.
4 papers.
- 2023LLM Interactive Optimization of Open Source Python Libraries -- Case Studies and Generalizationcited by 3
- 2022End-of-Life of Software How is it Defined and Managed?cited by 0
- 2024Identifying Technical Debt and Its Types Across Diverse Software Projects Issuescited by 0
- 2025Detection, Classification and Prevalence of Self-Admitted Aging Debtcited by 0
- 2025Detection, Classification and Prevalence of Self-Admitted Aging Debt24 Apr 2025
- 2024Identifying Technical Debt and Its Types Across Diverse Software Projects Issues17 Aug 2024
- 2023LLM Interactive Optimization of Open Source Python Libraries -- Case Studies and Generalization8 Dec 2023
- 2022End-of-Life of Software How is it Defined and Managed?8 Apr 2022