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Identifying "good" architectural design alternatives with multi-objective optimization strategies
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Source International Conference on Software Engineering archive
Proceedings of the 28th international conference on Software engineering table of contents
Shanghai, China
SESSION: Emerging results: architecture table of contents
Pages: 849 - 852  
Year of Publication: 2006
ISBN:1-59593-375-1
Author
Lars Grunske  University of Queensland, St Lucia, Brisbane, Australia
Sponsors
ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering
Publisher
ACM  New York, NY, USA
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ABSTRACT

Architecture trade-off analysis methods are appropriate techniques to evaluate design decisions and design alternatives with respect to conflicting quality requirements. However, the identification of good design alternatives is a time consuming task, which is currently performed manually. To automate this task, this paper proposes to use evolutionary algorithms and multi-objective optimization strategies based on architecture refactorings to identify a sufficient set of design alternatives. This approach will reduce development costs and improve the quality of the final system, because an automated and systematic search will identify more and better design alternatives.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
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J. Bosch and P. Molin. Software architecture design: Evaluation and transformation. In Proceedings of the ECBS 99, 4--10. IEEE Computer Society, 1999.
 
3
K. Briess, H. Jahn, E. Lorenz, D. Oertel, W. Skrbek, and B. Zhukov. Fire recognition potential of the bi-spectral infrared detection (BIRD) satellite. Int. J. Remote Sensing, 24(4):865--872, 2003.
 
4
P. C. Clements, R. Kazman, and M. Klein. Evaluating Software Architectures: Methods and Case Studies. Addison Wesley Longman, 2001.
 
5
C. A. Coello Coello. A Comprehensive Survey of Evolutionary-Based Multiobjective Optimization Techniques. Knowledge and Information Systems. An International Journal, 1(3):269--308, Aug. 1999.
 
6
K. Deb. Evolutionary Algorithms for Multi-Criterion Optimization in Engineering Design. In Evolutionary Algorithms in Engineering and Computer Science, 135--161. John Wiley & Sons, Chichester, UK, 1999.
 
7
8
 
9
 
10
 
11
L. Grunske. Transformational patterns for the improvement of safety properties in architectural specifications. In Proceedings of the VikingPLoP 03, Bergen, Norway, Oct 3-5 2003.
 
12
 
13
L. Grunske, B. Kaiser, and Y. Papadopoulos. Model-driven safety evaluation with state-event-based component failure annotations. In Proceedings of the 8th International Symposium on Component-Based Software Engineering (CBSE 2005), 33--48, 2005.
 
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L. Grunske, B. Kaiser, and R. H. Reussner. Specification and evaluation of safety properties in a component-based software engineering process. In Embedded Software Development with Components -- An Overview on Current Research Trends, 737--738. Springer-Verlag, 2005.
 
15
 
16
T. Saridakis. A system of patterns for fault tolerance. In Proceedings of the EuroPlop, 2002.