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tReductSA – Test Redundancy Reduction Strategy Based on Simulated Annealing

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Intelligent Software Methodologies, Tools and Techniques (SoMeT 2014)

Abstract

Software testing relates to the process of accessing the functionality of a program against some defined specifications. To ensure conformance, test engineers often generate a set of test cases to validate against the user requirements. When dealing with large line of codes (LOCs), there are potentially issue of redundancies as new test cases may be added and old test cases may be deleted during the whole testing process. In order to address this issue, we have developed a new strategy, called tReductSA, to systematically minimize test cases for testing consideration. Unlike existing works which rely on the Greedy approaches, our work adopts the random sequence permutation and optimization algorithm based on Simulated Annealing with systematic merging technique. Our benchmark experiments demonstrate that tReductSA scales well with existing works (including that of GE, GRE and HGS) as far as optimality is concerned. On the other note, tReductSA also offers more diversified solutions as compared to existing work.

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Acknowledgements

This research work involves collaborative efforts between Universiti Malaysia Pahang and Umm Al-Qura University. The work is funded by grant number 11-INF1674-10 from the Long-Term National Plan for Science, Technology and Innovation (LT-NPSTI), the King Abdul-Aziz City for Science and Technology (KACST), Kingdom of Saudi Arabia. We thank the Innovation Office, UMP and the Science and Technology Unit at Umm Al-Qura University for their continued logistics support.

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Correspondence to Kamal Z. Zamli .

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Zamli, K.Z., Mohd Hassin, M.H., Al-Kazemi, B. (2015). tReductSA – Test Redundancy Reduction Strategy Based on Simulated Annealing. In: Fujita, H., Selamat, A. (eds) Intelligent Software Methodologies, Tools and Techniques. SoMeT 2014. Communications in Computer and Information Science, vol 513. Springer, Cham. https://doi.org/10.1007/978-3-319-17530-0_16

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  • DOI: https://doi.org/10.1007/978-3-319-17530-0_16

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-17530-0

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