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GECCO
2007
Springer

Applying particle swarm optimization to software testing

9 years 5 months ago
Applying particle swarm optimization to software testing
Evolutionary structural testing is an approach to automatically generating test cases that achieve high structural code coverage. It typically uses genetic algorithms (GAs) to search for relevant test cases. In recent investigations particle swarm optimization (PSO), an alternative search technique, often outperformed GAs when applied to various problems. This raises the question of how PSO competes with GAs in the context of evolutionary structural testing. In order to contribute to an answer to this question, we performed experiments with 25 small artificial test objects and 13 more complex industrial test objects taken from various development projects. The results show that PSO outperforms GAs for most code elements to be covered in terms of effectiveness and efficiency. Categories and Subject Descriptors D.2.5 [Software Engineering]: Testing and Debugging — Test coverage of code, Testing tools General Terms Verification Keywords evolutionary testing, genetic algorithm, parti...
Andreas Windisch, Stefan Wappler, Joachim Wegener
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where GECCO
Authors Andreas Windisch, Stefan Wappler, Joachim Wegener
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