Automatic Test Data Generation Based on Ant Colony Optimization

Software testing is a crucial measure used to assure the quality of software. Path testing can detect bugs earlier because of it performs higher error coverage. This paper presents a model of generating test data based on an improved ant colony optimization and path coverage criteria. Experiments show that the algorithm has a better performance than other two algorithms and improve the efficiency of test data generation notably.

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