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Multi-objective optimization algorithms applied to the class integration and test order problem

  • ICTSS 2010
  • Published:
International Journal on Software Tools for Technology Transfer Aims and scope Submit manuscript

Abstract

In the context of object-oriented software, a common problem is the determination of test orders for the integration test of classes, known as the class integration and test order (CITO) problem. The existing approaches, based on graphs, usually generate solutions that are sub-optimal, and do not consider the different factors and measures that can affect the construction of stubs. To overcome this limitation, solutions based on genetic algorithms (GA) have presented promising results. However, the determination of a cost function, which is able to generate the best solution, is not always a trivial task, mainly for complex systems. Therefore, to better represent the CITO problem, we introduce, in this paper, a multi-objective optimization approach, to generate a set of good solutions that achieve a balanced compromise between the different measures (objectives). Three different multi-objective optimization algorithms (MOA) were implemented: Pareto ant colony, multi-objective Tabu search and non-dominated sorting GA. The approach is applied to real programs and the obtained results allow comparison with the simple GA approach and evaluation of the different MOA.

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Authors and Affiliations

  1. Computer Science Department, Federal University of Paraná, DInf-UFPR, CP 19081, Curitiba, 19031-970, Brazil

    Silvia Regina Vergilio, Aurora Pozo, João Carlos Garcia Árias, Rafael da Veiga Cabral & Tiago Nobre

Authors
  1. Silvia Regina Vergilio
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  2. Aurora Pozo
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  3. João Carlos Garcia Árias
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  4. Rafael da Veiga Cabral
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  5. Tiago Nobre
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Correspondence to Silvia Regina Vergilio.

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Vergilio, S.R., Pozo, A., Árias, J.C.G. et al. Multi-objective optimization algorithms applied to the class integration and test order problem. Int J Softw Tools Technol Transfer 14, 461–475 (2012). https://doi.org/10.1007/s10009-012-0226-1

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