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GECCO
2007
Springer

Automatic mutation test input data generation via ant colony

9 years 5 months ago
Automatic mutation test input data generation via ant colony
Fault-based testing is often advocated to overcome limitations of other testing approaches; however it is also recognized as being expensive. On the other hand, evolutionary algorithms have been proved suitable for reducing the cost of data generation in the context of coverage based testing. In this paper, we propose a new evolutionary approach based on ant colony optimization for automatic test input data generation in the context of mutation testing to reduce the cost of such a test strategy. In our approach the ant colony optimization algorithm is enhanced by a probability density estimation technique. We compare our proposal with other evolutionary algorithms, e.g., Genetic Algorithm. Our preliminary results on JAVA testbeds show that our approach performed significantly better than other alternatives. Categories and Subject Descriptors D [Software]: Miscellaneous; D.2.5 [Software Engineering]: Testing and Debugging —Testing tools (e.g., data generators, coverage testing) Gener...
Kamel Ayari, Salah Bouktif, Giuliano Antoniol
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where GECCO
Authors Kamel Ayari, Salah Bouktif, Giuliano Antoniol
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