10 years of software architecture knowledge management: Practice and future
Open accessAbstract
The importance of architectural knowledge (AK) management for software development has been highlighted over the past ten years, where a significant amount of research has been done. Since the first systems using design rationale in the seventies and eighties to the more modern approaches using AK for designing software architectures, a variety of models, approaches, and research tools have leveraged the interests of researchers and practitioners in AK management (AKM). Capturing, sharing, and using AK has many benefits for software designers and maintainers, but the cost to capture this relevant knowledge hampers a widespread use by software companies. However, as the improvements made over the last decade didn't boost a wider adoption of AKM approaches, there is a need to identify the successes and shortcomings of current AK approaches and know what industry needs from AK. Therefore, as researchers and promoters of many of the AK research tools in the early stages where AK became relevant for the software architecture community, and based on our experience and observations, we provide in this research an informal retrospective analysis of what has been done and the challenges and trends for a future research agenda to promote AK use in modern software development practices.
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Despite abundant research on architecture knowledge management, little is used in practice to ensure the completeness, up-to-dateness, and traceability of architecture documentation.
“Despite abundant research on architecture knowledge management [17], little is used in practice to ensure the completeness, upto-dateness, and traceability of architecture documentation.”
From Software Architecture in Practice: Challenges and Opportunities (2023) · cites this paper as [17]
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Software Architecture in Practice: Challenges and Opportunities
Wan, Z., Zhang, Y., Xia, X., Jiang, Y., & Lo, D. (2023) · Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering · doi:10.1145/3611643.3616367 · Cited by 30 · see citing works
“The discovery of architecture knowledge allows reasoning and uncovering design problems and alternatives [16].”
BackgroundMethodInfluential
- Authors
- Capilla, R., Jansen, A., Tang, A., Avgeriou, P., & Babar, M. A.
- Affiliations
- Universidad Rey Juan Carlos (ES)
- Philips (Netherlands) (NL)
- Swinburne University of Technology (AU)
- University of Groningen (NL)
- The University of Adelaide (AU)
- Corresponding author
- Capilla, Rafael
- Venue
- Journal of Systems and Software
- Publisher
- Elsevier BV
- Published
- 2016-06
- Volume
- 116
- Pages
- 191-205
- ISSN
- 0164-1212 (ISSN-L)
- OpenAlex
- W1668578304
- Cited by
- 160
- References
- 103
- Citations by year
- 2026: 11 · 2025: 11 · 2024: 16 · 2023: 12 · 2022: 9 · 2021: 20 · 2020: 20 · 2019: 19 · 2018: 19 · 2017: 17 · 2016: 6
- FWCI
- 13.70
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Systems and Software (publishedVersion, other-oa)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Swinburne figshare (Swinburne University of Technology) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Software Engineering Methodologies
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Keywords
- architectural knowledge management, software architecture, design rationale, knowledge capture, knowledge sharing, software design, software maintenance, research agenda, industrial adoption
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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