Design Rule Spaces: A New Model for Representing and Analyzing Software Architecture
Abstract
In this paper, we propose an architecture model called Design Rule Space (DRSpace). We model the architecture of a software system as multiple overlapping DRSpaces, reflecting the fact that any complex software system must contain multiple aspects, features, patterns, etc. We show that this model provides new ways to analyze software quality. In particular, we introduce an Architecture Root detection algorithm that captures DRSpaces containing large numbers of a project's bug-prone files, which are called Architecture Roots (ArchRoots). After investigating ArchRoots calculated from 15 open source projects, the following observations become clear: from 35 to 91 percent of a project's most bug-prone files can be captured by just 5 ArchRoots, meaning that bug-prone files are likely to be architecturally connected. Furthermore, these ArchRoots tend to live in the system for significant periods of time, serving as the major source of bug-proneness and high maintainability costs. Moreover, each ArchRoot reveals multiple architectural flaws that propagate bugs among files and this will incur high maintenance costs over time. The implication of our study is that the quality, in terms of bug-proneness, of a large, complex software project cannot be fundamentally improved without first fixing its architectural flaws.
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A Framework for Obtaining the Ground-Truth in Architectural Recovery
Garcia, J., Krka, I., Medvidović, N., et al. (2012) · doi:10.1109/wicsa-ecsa.212.48 · Cited by 14 · see citing works
Peters, L. J. (2014) · doi:10.1109/mtd.2014.7 · Cited by 14 · see citing works
An Aspect-Based Feature Model for Architecting Component Product Lines
Tizzei, L. P., Rubira, C. M. F., & Lee, J. (2012) · Euromicro Conference on Software Engineering and Advanced Applications (SEAA) · doi:10.1109/seaa.2012.64 · Cited by 13 · see citing works
On the Relation of Refactoring and Software Defects
Ratzinger, J., Sigmund, T., & Gall, H. C. (2008) · Cited by 12 · see citing works
Seaman, C. B., Nord, R. L., Kruchten, P. B., & Özkaya, İ. (2015) · ACM SIGSOFT Software Engineering Notes · doi:10.1145/2735399.2735419 · Cited by 11 · see citing works
A learning algorithm for change impact prediction
Musco, V., Carette, A., Monperrus, M., et al. (2016) · doi:10.1145/2896995.2896996 · Cited by 8 · see citing works
Ripple: a test-aware architecture modeling framework
Xiao, L., & Yu, T. (2017) · doi:10.5555/3101282.3101286 · Cited by 2 · see citing works
Self-citationRipple: A Test-Aware Architecture Modeling Framework
Xiao, L., & Yu, T. (2017) · doi:10.1109/ecase.2017.2 · Cited by 2 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
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
“Previous studies have put effort into developing methods and tools for architecture representation and documentation [15, 38], analysis and evaluation [41, 73], recovery and optimization [2, 30, 54], as well as knowledge management and decision making [16, 100] to support software architecture…”
Method
- Authors
- Cai, Y., Xiao, L., Kazman, R., Mo, R., & Feng, Q.
- Affiliations
- Drexel University (US)
- Stevens Institute of Technology (US)
- University of Hawaiʻi at Mānoa (US)
- Venue
- IEEE Transactions on Software Engineering
- Published
- 2019-07-01
- Volume
- 45
- Issue
- 7
- Pages
- 657-682
- ISSN
- 0098-5589 (ISSN-L)
- 1939-3520
- 2326-3881
- OpenAlex
- W2792459140
- Cited by
- 39
- References
- 124
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 2 · 2023: 9 · 2022: 3 · 2021: 6 · 2020: 9 · 2019: 4 · 2018: 1
- FWCI
- 8.06
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Software Engineering (publishedVersion)
- Funders
- Division of Computing and Communication Foundations (1514315)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Software Engineering Methodologies
- Physical Sciences › Computer Science › Computer Networks and Communications › Software System Performance and Reliability
- Keywords
- software architecture modeling, software quality, bug propagation, open source projects, software architecture evaluation
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.
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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