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The crossover operation is an important component of genetic algorithms for test case generation. The usefulness of crossover, however, is not really clear, especially for industrial settings. This research applies EvoSuite, a well-known searchbased test case generator, to both open-source and industrial Java programs, and investigates the impact of the use of crossover on the code coverage achieved by the generated test cases. Our empirical study shows that the usefulness of the crossover operation varies for open-source and industrial code, and that the crossover operation may not necessarily be good, especially for some industrial programs. We further analyze (un)favorable conditions/code features for the use of crossover operations, providing hints for effective test case generation. ....

Automated Unit Test Generation , Genetic Algorithm , Earch Based Testing ,