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Sei nella pagina indice --> Eventi e News --> Using Genetic Algorithms and Coupling Measures to Devise Optimal Integration Test Orders

Using Genetic Algorithms and Coupling Measures
to Devise Optimal Integration Test Orders
prof. Lionel BRIAND

13 maggio 2002 ore 15.00
R-COST - Palazzo ex Poste
Via Traiano, 1
82100 Benevento

per informazioni
prof. Gerardo Canfora - R-COST Research Centre on Software Tecnology
pbx 0824305804 - fax 0824305840
e-mail gerardo.canfora [at] unisannio.it

We present here an improved strategy to devise optimal integration test orders in object-oriented systems. Our goal is to minimize the complexity of stubbing during integration testing as this has been shown to be a major source of expenditure. Our strategy to do so is based on the combined use of inter-class coupling measurement and genetic algorithms. The former is used to assess the complexity of stubs and the latter is used to minimize complex cost functions based on coupling measurement. Using a precisely defined procedure, we investigate this approach in a case study investigating a real system. Results are very encouraging as the approach clearly helps obtaining systematic and optimal results. Acknowledgments: This work is supported by NSERC and Mitel Networks, and was done in collaboration with Yvan Labiche and Jie Feng.


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