Managing technical debt in software-reliant systems
Abstract
Delivering increasingly complex software-reliant systems demands better ways to manage the long-term effects of short-term expedients. The technical debt metaphor is gaining significant traction in the agile development community as a way to understand and communicate such issues. The idea is that developers sometimes accept compromises in a system in one dimension (e.g., modularity) to meet an urgent demand in some other dimension (e.g., a deadline), and that such compromises incur a "debt": on which "interest" has to be paid and which the "principal" should be repaid at some point for the long-term health of the project. We argue that the software engineering research community has an opportunity to study and improve this concept. We can offer software engineers a foundation for managing such trade-offs based on models of their economic impacts. Therefore, we propose managing technical debt as a part of the future research agenda for the software engineering field.
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Technical debt is characterized as 'quick and dirty' software customizations made without a complete understanding of their future implications, undermining system reliability and imposing long-term maintenance obligations.
“Extant literature characterizes 'quick and dirty' software customizations made without a complete understanding of their future implications as technical debt, as they undermine system reliability and impose long-term maintenance obligations (Kruchten et al. 2012, Brown et al. 2010, Banker et al. 2021).”
From AI-Assisted Programming Decreases the Productivity of Experienced Developers by Increasing the Technical Debt and Maintenance Burden (2025) · cites this paper as Brown et al. 2010
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An exploration of technical debt
Tom, E., Aurum, A., & Vidgen, R. (2013) · Journal of Systems and Software · doi:10.1016/j.jss.2012.12.052 · Cited by 438 · see citing works
Kruchten, P., Nord, R. L., Ozkaya, I., & Falessi, D. (2013) · ACM SIGSOFT Software Engineering Notes · doi:10.1145/2507288.2507326 · Cited by 87 · see citing works
Self-citationDesign Rule Spaces: A New Model for Representing and Analyzing Software Architecture
Cai, Y., Xiao, L., Kazman, R., Mo, R., & Feng, Q. (2019) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2018.2797899 · Cited by 39 · see citing works
Self-citationXu, F., Medappa, P. K., Tunc, M. M., Vroegindeweij, M., & Fransoo, J. C. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5521379 · Cited by 2 · see citing works
Xu, F., Medappa, P. K., Tunc, M. M., Vroegindeweij, M., & Fransoo, J. C. (2025) · arXiv · doi:10.48550/arxiv.2510.10165 · Cited by 1 · see citing works
- Authors
- Brown, N., Cai, Y., Guo, Y., Kazman, R., Kim, M., Kruchten, P., Lim, E., MacCormack, A., Nord, R., Ozkaya, I., Sangwan, R., Seaman, C., Sullivan, K., & Zazworka, N.
- Affiliations
- Carnegie Mellon University (US)
- Drexel University (US)
- University of Maryland, Baltimore County (US)
- University of Hawaiʻi at Mānoa (US)
- The University of Texas at Austin (US)
- University of British Columbia (CA)
- Massachusetts Institute of Technology (US)
- Carnegie Mellon University, Pittsnurgh, PA, USA
- Pennsylvania State University (US)
- University of Virginia (US)
- ORCID
- Venue
- Proceedings of the FSE/SDP workshop on Future of software engineering research
- Publisher
- ACM
- Published
- 2010-11-07
- Pages
- 47-52
- OpenAlex
- W2057433090
- Cited by
- 432
- References
- 0
- Citations by year
- 2026: 14 · 2025: 24 · 2024: 27 · 2023: 17 · 2022: 31 · 2021: 35 · 2020: 32 · 2019: 28 · 2018: 27 · 2017: 29 · 2016: 32 · 2015: 39 · 2014: 29 · 2013: 29 · 2012: 28
- FWCI
- 15.23
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- FSE/SDP Workshop on Future of Software Engineering Research (FoSER) (publishedVersion)
- Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) (submittedVersion)
- Fraunhofer-Publica (Fraunhofer-Gesellschaft) (submittedVersion)
- Funders
- National Science Foundation
- U.S. Department of Defense
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Software Engineering Methodologies
- Keywords
- technical debt, modularity, economic impact model, agile software development, software maintenance, research agenda
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