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A Hybrid Evolutionary Multiobjective Approach for the Component Selection Problem

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Hybrid Artificial Intelligence Systems (HAIS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5271))

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Abstract

Component selection is a crucial problem in Component Based Software Engineering (CBSE). CBSE is concerned with the assembly of pre-existing software components that leads to a software system that responds to client-specific requirements. We formulate the problem as multiobjective, involving 3 objectives. The approach used in this paper is an evolutionary computation technique combined with a greedy algorithm which is used to fine tune the solutions after the application of the genetic operators. The experiments and comparisons with Greedy technique show the effectiveness of the proposed approach.

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References

  1. Crnkovic, I., Larsson, M.: Building Reliable Component-Based Software Systems. Artech House publisher (2002)

    Google Scholar 

  2. Mancebo, E., Andrews, A.: A strategy for selecting multiple components. In: ACM Symposium on Applied Computing, pp. 1505–1510. ACM Press, New York (2005)

    Google Scholar 

  3. Gesellensetter, L., Glesner, S.: Only the Best Can Make It: Optimal Component Selection. Electron. Notes Theor. Comput. Sci. 176, 105–124 (2007)

    Article  Google Scholar 

  4. Haghpanah, N., Moaven, S., Habibi, J., Kargar, M., Yeganeh, S.H.: Approximation Algorithms for Software Component Selection Problem. In: The 14th Asia-Pacific Software Engineering Conference, pp. 159–166. IEEE Press, Los Alamitos (2007)

    Chapter  Google Scholar 

  5. Alves, C., Castro, J.: Pore: Procurement-oriented requirements engineering method for the component based systems engineering development paradigm. In: International Workshop on Component Based Software Engineering, pp. 7–18 (1999)

    Google Scholar 

  6. Alves, C., Castro, J.: CRE: A systematic method for cots component selection. In: Brazilian Symposium on Software Engineering, pp. 193–207 (2001)

    Google Scholar 

  7. Fox, M.R., Brogan, D.C., Reynolds, P.F.: Approximating component selection. In: The 36th conference on Winter simulation, pp. 429–434. ACM Press, New York (2004)

    Google Scholar 

  8. Baker, P., Harman, M., Steinhofel, K., Skaliotis, A.: Search Based Approaches to Component Selection and Prioritization for the Next Release Problem. In: The 22nd International Conference on Software Maintenance, pp. 176–185. IEEE Press, Los Alamitos (2006)

    Chapter  Google Scholar 

  9. Grosan, C.: A comparison of several evolutionary models and representations for multiobjective optimization. In: ISE Book Series on Real Word Multi-Objective System Engineering, ch. 3. Nova Science (2005)

    Google Scholar 

  10. Abraham, A., Jain, L., Goldberg, R.: Evolutionary Multiobjective Optimization: Theoretical Advances and Applications. Springer, London (2005)

    MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Computer Science Department, Babes-Bolyai University, Kogalniceanu 1, 400084, Cluj-Napoca, Romania

    Andreea Vescan & Crina Grosan

Authors
  1. Andreea Vescan
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  2. Crina Grosan
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Editor information

Editors and Affiliations

  1. Escuela Politécnica Superior, GICAP Research Group, Universidad de Burgo, Calle Francisco de Vitoria S/N, Edifico C, Campus Vena, 09006, Burgos, Spain

    Emilio Corchado

  2. Center of Excellence for Quantifiable Quality of Service, Norwegian University of Science and Technology, 7491, Trondheim, Norway

    Ajith Abraham

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton,, T6G 2V4, Alberta, Canada

    Witold Pedrycz

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© 2008 Springer-Verlag Berlin Heidelberg

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Vescan, A., Grosan, C. (2008). A Hybrid Evolutionary Multiobjective Approach for the Component Selection Problem. In: Corchado, E., Abraham, A., Pedrycz, W. (eds) Hybrid Artificial Intelligence Systems. HAIS 2008. Lecture Notes in Computer Science(), vol 5271. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87656-4_21

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  • DOI: https://doi.org/10.1007/978-3-540-87656-4_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87655-7

  • Online ISBN: 978-3-540-87656-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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