Abstract
In the context of Object-Oriented software, many works have investigated the Class Integration and Test Order (CITO) problem, proposing solutions to determine test orders for the integration test of the program classes. The existing approaches based on graphs can generate solutions that are sub-optimal, and do not consider the different factors and measures that can affect the stubbing process. 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 solutions, is not always a trivial task, mainly for complex systems with a great number of measures. Therefore, we introduce, in this paper, a multi-objective optimization approach to better represent the CITO problem. The approach generates a set of good solutions that achieve a balanced compromise between the different measures (objectives). It was implemented by a Pareto Ant Colony (P-ACO) algorithm, which is described in detail. The algorithm was used in a set of real programs and the obtained results are compared to the GA results. The results allow discussing the difference between single and multi-objective approaches especially for complex systems with a greater number of dependencies among the classes.
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References
Abdurazik, A., Offutt, J.: Coupling-based class integration and test order. In: International Workshop on Automation of Software Test. ACM, Shanghai (May 2006)
Binder, R.V.: Testing Object-Oriented Systems: Models, Patterns, and Tools. Addison-Wesley, Reading (2000)
Briand, L.C., Feng, J., Labiche, Y.: Experimenting with Genetic Algorithms and Coupling Measures to Devise Optimal Integration Test Orders. Carleton University, Technical Report SCE-02-03 (October 2002)
Briand, L.C., Feng, J., Labiche, Y.: Using genetic algorithms and coupling measures to devise optimal integration test orders. In: 14th International Conference on Software Engineering and Knowledge Engineering, Ischia, Italy (July 2002)
Briand, L.C., Feng, J., Labiche, Y.: Experimenting with genetic algorithms and coupling measures to devise optimal integration test orders. In: Proceedings of Software Engineeing with Computational Intelligence, pp. 204–234. Kluwer Academic Publishers, Dordrecht (2003)
Briand, L.C., Labiche, Y.: An investigation of graph-based class integration test order strategies. IEEE Transactions on Software Engineering 29(7), 594–607 (2003)
Doerner, K., Gutjahr, W.J., Hartl, R.F., Strauss, C., Stummer, C.: Pareto ant colony optimization: A metaheuristic approach to multiobjective portfolio selection. Annals of Operation Research (131), 79–99 (2004)
Dorigom, M., Socha, K.: An Introduction to Ant Colony Optimization. No. TR/IRIDIA/2006-010., Technical Report - IRIDIA (April 2006)
Harman, M.: The current state and future of search based software engineering. In: Proceedings of International Conference on Software Engineering / Future of Software Engineering 2007 (ICSE/FOSE 2007), May 20-26, pp. 342–357. IEEE Computer Society, Minneapolis (2007)
Harrold, M.J., McGregor, J.D., Fitzpatrick, K.J.: Incremental testing of object-oriented class structures. In: 14th International Conference on Software Engineering, pp. 68–80. IEEE Computer Society, Melbourne (May 1992)
Knowles, J., Thiele, L., Zitzler, E.: A Tutorial on the Performance Assessment of Stochastic Multiobjective Optimizer. 214, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, Switzerland (February 2006)
Kung, D., Gao, J., Hsia, P., Toyoshima, Y., Chen, C.: A test strategy for object-oriented programs. In: 19th International Computer Software and Applications Conference. IEEE Computer Society, Los Alamitos (August 1995)
Melton, H., Tempero, E.: An empirical study of cycles among classes in Java. Empirical Software Engineering 12, 389–415 (2007)
Pareto, V.: Manuel D’Economie Politique. Ams Press, Paris (1927)
Pasia, J.M., Hart, R., Doerner, K.F.: Solving a bi-objective flowshop scheduling problem by Pareto-ant colony optimization. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds.) ANTS 2006. LNCS, vol. 4150, pp. 294–305. Springer, Heidelberg (2006)
Pressman, R.: Software Engineering: A Practitioner’s Approach. McGraw-Hill, New York (2006)
Tai, K.C., Daniels, F.J.: Test order for inter-class integration testing of object-oriented software. In: 21st International Computer Software and Applications Conference, pp. 602–607. IEEE Computer Society, Los Alamitos (August 1997)
Traon, Y.L., Jéron, T., Jézéquel, J.M., Morel, P.: Efficient object-oriented integration and regression testing. IEEE Transactions on Reliability, 12–25 (2000)
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da Veiga Cabral, R., Pozo, A., Vergilio, S.R. (2010). A Pareto Ant Colony Algorithm Applied to the Class Integration and Test Order Problem. In: Petrenko, A., Simão, A., Maldonado, J.C. (eds) Testing Software and Systems. ICTSS 2010. Lecture Notes in Computer Science, vol 6435. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16573-3_3
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DOI: https://doi.org/10.1007/978-3-642-16573-3_3
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