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Automatic Test Data Generation using Metaheuristic Cuckoo Search Algorithm

机译:使用元启发式布谷鸟搜索算法自动生成测试数据

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The proposed work emphasizes on the automated process of test data generation for unit testing of structured programs, targeting complete path coverage of the software under test. In recent years, Cuckoo Search (CS) has been successfully applied in many engineering applications because of its high convergence rate to the global solution. The authors motivated with the performance of Cuckoo search, utilized it to generate test suits for the standard benchmark problems, covering entire search space of the input data in less iterations. The experimental results reveal that the proposed approach covers entire search space generating test data for all feasible paths of the problem in few number of generations. It is observed that proposed approach gives promising results and outperforms other reported algorithms and it can be an alternative approach in the field of test data generation.
机译:拟议的工作着重于针对结构化程序的单元测试的测试数据生成的自动化过程,其目标是覆盖被测软件的完整路径。近年来,由于布谷鸟搜索(CS)与全球解决方案的融合速度很高,因此已成功应用于许多工程应用中。作者受Cuckoo搜索性能的启发,利用它来生成标准基准问题的测试服,从而以较少的迭代次数覆盖了输入数据的整个搜索空间。实验结果表明,所提出的方法涵盖了整个搜索空间,生成了几代问题的所有可行路径的测试数据。可以看出,所提出的方法给出了令人鼓舞的结果,并且优于其他报告的算法,并且它可以成为测试数据生成领域中的另一种方法。

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