The DOI matches its Crossref record; 254 of the 254 references it cites were found in a registry or an index.
Software Architecture Optimization Methods: A Systematic Literature Review
Open accessAbstract
Due to significant industrial demands toward software systems with increasing complexity and challenging quality requirements, software architecture design has become an important development activity and the research domain is rapidly evolving. In the last decades, software architecture optimization methods, which aim to automate the search for an optimal architecture design with respect to a (set of) quality attribute(s), have proliferated. However, the reported results are fragmented over different research communities, multiple system domains, and multiple quality attributes. To integrate the existing research results, we have performed a systematic literature review and analyzed the results of 188 research papers from the different research communities. Based on this survey, a taxonomy has been created which is used to classify the existing research. Furthermore, the systematic analysis of the research literature provided in this review aims to help the research community in consolidating the existing research efforts and deriving a research agenda for future developments.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
Genetic algorithms in search, optimization, and machine learning
(1989) · Choice Reviews Online · doi:10.5860/choice.27-0936 · Cited by 49,178
Content Analysis: An Introduction to its Methodology.
Shelley, M., & Krippendorff, K. (1984) · Journal of the American Statistical Association · doi:10.2307/2288384 · Cited by 24,346
Goldberg, D. E., & Shakespeare, W. (2002) · Cited by 16,088
Content Analysis: An Introduction to Its Methodology
Krippendorff, K. (2019) · doi:10.4135/9781071878781 · Cited by 15,448
Multi-Objective Optimization Using Evolutionary Algorithms
Deb, K., & Kalyanmoy, D. (2001) · Andalas University Repository (Andalas University) · Cited by 14,936
Basic concepts and taxonomy of dependable and secure computing
Avižienis, A., Laprie, J.-C., Randell, B., & Landwehr, C. E. (2004) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2004.2 · Cited by 5,246
(2004) · Cited by 5,198
Evolutionary Algorithms in Theory and Practice
Bäck, T. (1996) · Oxford University Press eBooks · doi:10.1093/oso/9780195099713.001.0001 · Cited by 5,123
Software Architecture in Practice
Bass, L., Clements, P., & Kazman, R. (1997) · Cited by 5,033
Metaheuristics in combinatorial optimization
Blum, C., & Roli, A. (2003) · ACM Computing Surveys · doi:10.1145/937503.937505 · Cited by 3,250
Research works printed but not linked: 8
- Coello, A Survey of Constraint Handling Techniques Used with Evolutionary Algorithms, 20, 1245
- Coit, Multi-Criteria Optimization: Maximization of a System Reliability Estimate & Minimization of the Estimate Variance, 1
- Glaser, Grounded Theory: The Discovery of Grounded Theory
- Glaß, Lifetime Reliability Optimization for Embedded Systems: A System-Level Approach, 17
- ISO/IEC Standard for Software Engineering Product Quality
- 2007, ISO/IEC Standard for Systems and Software Engineering—Recommended Practice for Architectural Description of Software-Intensive Systems Int’l Standards Organization, c1-24
- Menasce, 2004, Performance by Design
- Wang, A New Approach for Task Level Computational Resource Bi-Partitioning
Cited by
Sorted by citations
Ampatzoglou, A., Bibi, S., Avgeriou, P., Verbeek, M., & Chatzigeorgiou, A. (2019) · Information and Software Technology · doi:10.1016/j.infsof.2018.10.006 · Cited by 305
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
“…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 practice.”
Method
Metadata
- Authors
- Aleti, A., Buhnova, B., Grunske, L., Koziolek, A., & Meedeniya, I.
- Affiliations
- Monash University (AU)
- University of Kaiserslautern (DE)
- University of Zurich (CH)
- Swinburne University of Technology (AU)
- Venue
- IEEE Transactions on Software Engineering
- Published
- 2013-05
- Volume
- 39
- Issue
- 5
- Pages
- 658-683
- ISSN
- 0098-5589 (ISSN-L)
- 1939-3520
- OpenAlex
- W2023331046
- Cited by
- 293
- References
- 254
- Citations by year
- 2026: 4 · 2025: 18 · 2024: 8 · 2023: 19 · 2022: 17 · 2021: 18 · 2020: 18 · 2019: 18 · 2018: 28 · 2017: 34 · 2016: 34 · 2015: 30 · 2014: 28 · 2013: 19
- FWCI
- 6.96
- Type
- journal article
- Language
- en
- Open access
- green
- www.zora.uzh.ch
- Locations
- IEEE Transactions on Software Engineering (publishedVersion)
- Swinburne figshare (Swinburne University of Technology) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Software › Advanced Software Engineering Methodologies
- Physical Sciences › Computer Science › Software › Model-Driven Software Engineering Techniques
- Physical Sciences › Computer Science › Computer Networks and Communications › Software System Performance and Reliability
- Keywords
- software architecture optimization, automated architecture design, quality attributes, research agenda
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 ›
Are you an author, or do you see a problem with this page? Request a review
