Using genetic algorithms and coupling measures to devise optimal integration test orders
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 involving a real system. Results are very encouraging as the approach clearly helps obtaining systematic and optimal results. Copyright 2002 ACM.
|genetic algorithms, integration order, integration testing, object-oriented software engineering|
|14th International Conference on Software Engineering and Knowledge Engineering, SEKE '02|
|Organisation||Department of Systems and Computer Engineering|
Briand, L.C. (Lionel C.), Feng, J. (Jie), & Labiche, Y. (2002). Using genetic algorithms and coupling measures to devise optimal integration test orders. Presented at the 14th International Conference on Software Engineering and Knowledge Engineering, SEKE '02. doi:10.1145/568760.568769