Application of knowledge-based approaches in software architecture: A systematic mapping study
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A number of meta-models aim at representing design decisions and rationale.
“We have seen a number of meta-models that aim at representing design decisions and rationale [52, 99].”
From Software Architecture in Practice: Challenges and Opportunities (2023) · cites this paper as [52]
Section 3.3 describes a meta-model that makes architectural design-decision knowledge explicit, supporting the design-decision part of the claim. Section 2.1.2 discusses decision rationale, but our copy does not establish that multiple meta-models aim to represent both decisions and their rationale. No page number is available in the indexed passages. (LLM, conf=0.82)
Experimental — accuracy not yet measuredTraceability of architecture knowledge improves understandability, helps locate relevant knowledge, enables impact analysis, and facilitates design review, evaluation and assessment.
“Traceability of architecture knowledge improves understandability of software architectures, helps to locate relevant knowledge, enables impact analysis of architectural changes, and facilitates design review, evaluation and assessment [52, 80].”
From Software Architecture in Practice: Challenges and Opportunities (2023) · cites this paper as [52]
Section 3.3 reports that making architectural design decisions and their relationships explicit can improve impact analysis. Section 2.1.1 also discusses architecture understanding, but the paper does not establish that traceability itself improves understanding or helps locate relevant knowledge, nor that it facilitates design review, evaluation, and assessment. No page numbers are available in our copy. (LLM, conf=0.78)
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- Authors
- Li, Z., Liang, P., & Avgeriou, P.
- Affiliations
- University of Groningen (NL)
- Wuhan University (CN)
- Corresponding author
- Li, Zengyang
- Venue
- Information and Software Technology
- Publisher
- Elsevier BV
- Published
- 2013-05
- Volume
- 55
- Issue
- 5
- Pages
- 777-794
- ISSN
- 0950-5849 (ISSN-L)
- OpenAlex
- W2148849527
- Cited by
- 74
- References
- 89
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 3 · 2023: 4 · 2022: 3 · 2021: 5 · 2020: 5 · 2019: 8 · 2018: 11 · 2017: 5 · 2016: 7 · 2015: 6 · 2014: 14
- FWCI
- 6.30
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Information and Software Technology (publishedVersion)
- VU Research Portal (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- VU Research Portal (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- National Natural Science Foundation of China
- 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 › Software › Model-Driven Software Engineering Techniques
- Keywords
- knowledge-based approach, software architecture, knowledge management, knowledge reuse, knowledge capture, knowledge representation, ontology (information science), architecture evaluation, knowledge recovery, embedded software
About these checks
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.
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