Techniques for Component-Based Software Architecture Optimization

Adil Ali Abdelaziz; Wan Nasir

doi:10.18495/comengapp.v1i1.4

[1] Voas, J., COTS software: the economical choice?Software, IEEE, 1998. 15(2): p. 16-19
[2] D. Hoch, et al., The race to master automotive embedded systems development.2006, McKinsey Company, Automotive and assembly sector business technology office: Germany.
[3] Martens, A. and H. Koziolek, Automatic, Model-Based Software Performance Improvement for Component-based Software Designs.Electronic Notes in Theoretical Computer Science, 2009. 253(1): p. 77-93.[4] Cortellessa, V. and L. Frittella, A framework for automated generation of architectural feedback from software performance analysis, in Proceedings of the 4th European performance engineering conference on Formal methods and stochastic models for performance evaluation. 2007, Springer-Verlag: Berlin, Germany. p. 171-185.
[5] Xu, J., Rule-based automatic software performance diagnosis and improvement, in Proceedings of the 7th international workshop on Software and performance. 2008, ACM: Princeton, NJ, USA. p. 1-12.
[6] website. Swarm and Evolutionary Computation. 2011 [cited 2011 13-11-2011]; Available from: http://web.mysites.ntu.edu.sg/epnsugan/PublicSite/Shared%20Documents/Swarm%20and%20Evolutionary%20Computation_2.pdf.
[7] Gudise, V.G. and G.K. Venayagamoorthy. Comparison of particle swarm optimization and backpropagation as training algorithms for neural networks. in Proceedings of the Swarm Intelligence Symposium. SIS '03. IEEE. 2003.
[8] Boeringer, D.W. and D.H. Werner, Particle swarm optimization versus genetic algorithms for phased array synthesis.Antennas and Propagation, IEEE Transactions on, 2004. 52(3): p. 771-779.
[9] Eberhart, R. and Y. Shi, Comparison between genetic algorithms and particle swarm optimization Evolutionary Programming VII, V. Porto, et al., Editors. 1998, Springer Berlin / Heidelberg. p. 611-616.
[10] Liang, J.J., et al., Comprehensive learning particle swarm optimizer for global optimization of multimodal functions.IEEE Transactions on Evolutionary Computation, 2006. 10(3): p. 281-295.
[11] Qasem, S.N. and S.M. Shamsuddin, Radial basis function network based on time variant multi-objective particle swarm optimization for medical diseases diagnosis.Applied Soft Computing, 2011. 11(1): p. 1427-1438.

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Affiliations

Adil Ali Abdelaziz
University Technology Malaysia

Wan Nasir
Department of Software Engineering University Technology Malaysia

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Techniques for Component-Based Software Architecture Optimization

Adil Ali Abdelaziz ,
Wan Nasir

Vol 1 No 1 (2012)

DOI 10.18495/comengapp.v1i1.4

Submitted: Feb 8, 2012

Published: Jun 25, 2012

Abstract

Although Component-Based System (CBS) increases the efficiency of development and reduces the need for maintenance, but even good quality components could fail to compose good product if the composition is not managed appropriately. In real world, such as industrial automation domain, this probability is unacceptable because additional measures, time, efforts, and costs are required to minimize its impacts. Many general optimization approaches have been proposed in literature to manage the composition of system at early stage of development. This paper investigates recent approach es used to optimize software architecture. The results of this study are important since it will be used to develop an efficient optimization framework to optimize software architecture in next step of our ongoing research.