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Automatic Test Data Generation using Metaheuristic Cuckoo Search Algorithm

Automatic Test Data Generation using Metaheuristic Cuckoo Search Algorithm

Madhumita Panda, Partha Pratim Sarangi, Sujata Dash
Copyright: © 2015 |Volume: 5 |Issue: 2 |Pages: 14
ISSN: 1947-9115|EISSN: 1947-9123|EISBN13: 9781466678095|DOI: 10.4018/IJKDB.2015070102
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MLA

Panda, Madhumita, et al. "Automatic Test Data Generation using Metaheuristic Cuckoo Search Algorithm." IJKDB vol.5, no.2 2015: pp.16-29. http://doi.org/10.4018/IJKDB.2015070102

APA

Panda, M., Sarangi, P. P., & Dash, S. (2015). Automatic Test Data Generation using Metaheuristic Cuckoo Search Algorithm. International Journal of Knowledge Discovery in Bioinformatics (IJKDB), 5(2), 16-29. http://doi.org/10.4018/IJKDB.2015070102

Chicago

Panda, Madhumita, Partha Pratim Sarangi, and Sujata Dash. "Automatic Test Data Generation using Metaheuristic Cuckoo Search Algorithm," International Journal of Knowledge Discovery in Bioinformatics (IJKDB) 5, no.2: 16-29. http://doi.org/10.4018/IJKDB.2015070102

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Abstract

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.

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