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Multi-objective Optimization for Object-oriented Testing Using Stage-Based Genetic Algorithm

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Advances in Communication, Network, and Computing (CNC 2012)

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Abstract

A multi-objective optimization involves optimizing a number of objectives simultaneously. The Multi-Objective Optimization Problem has a set of solutions, each of which satisfies the objectives at an acceptable level. An optimization algorithm named SBGA (stage-based genetic algorithm), with new GA operators is attempted. The multiple objectives considered for optimization are maximum path coverage with minimum execution time and test-suite minimization. The coverage and the no. of test cases generated using SBGA are experimented with simple object-oriented programs. The data flow testing of OOPs in terms of path coverage are resulted with almost 88%. Thus, the efficiency of generated testcases has been improved in terms of path coverage with minimum execution time.

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References

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Authors and Affiliations

  1. Department of Information Technology, Pondicherry Engineering College, Puducherry, India

    P. Maragathavalli & S. Kanmani

Authors
  1. P. Maragathavalli
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  2. S. Kanmani
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Editor information

Editors and Affiliations

  1. Network Security Group, Institute of Doctors Engineering and Scientists (The IDES), Ouderkerk aan de Amstel, 1191 GT, Amsterdam, The Netherlands

    Vinu V. Das

  2. Ilahia College of Engineering, Kothamangalam, India

    Janahanlal Stephen

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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Maragathavalli, P., Kanmani, S. (2012). Multi-objective Optimization for Object-oriented Testing Using Stage-Based Genetic Algorithm. In: Das, V.V., Stephen, J. (eds) Advances in Communication, Network, and Computing. CNC 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 108. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35615-5_37

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  • DOI: https://doi.org/10.1007/978-3-642-35615-5_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35614-8

  • Online ISBN: 978-3-642-35615-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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