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Derivation of Test Cases for Model-based Testing of Software Product Line with Hybrid Heuristic Approach

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Abstract

In Model-based testing (MBT) for Software Product Lines (SPLs), many algorithms have been proposed for test case generation. The test case is generated based on a test model which aims to achieve optimization. The heuristic search algorithm is one of the techniques that can be used to traverse the test model with a good quality of solutions. This paper describes our experience in using three types of search algorithm, which are Floyd’s Warshall, Branch and Bound algorithm and Best First Search (FWA-BBA-BFS) which were integrated and hybridized in order to fully explore the test model. In this paper, this algorithm is validated based on test case results measured according to coverage criteria, generation time and size of test suite. Based on the experimental results, it is established that our proposed algorithm can generate test cases with reasonable cover-age, minimal execution time and appropriate size of test suite.

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Acknowledgement

This research is fully funded by Ministry of Higher Education Malaysia (MOHE) for FRGS Grant Vot No.5F117 and University Teknologi Malaysia for UTM-TDR Grant Vot No.06G23, which made this research endeavor possible.

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Correspondence to D. N. A. Jawawi .

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Aduni Sulaiman, R., Jawawi, D.N.A., Halim, S.A. (2020). Derivation of Test Cases for Model-based Testing of Software Product Line with Hybrid Heuristic Approach. In: Saeed, F., Mohammed, F., Gazem, N. (eds) Emerging Trends in Intelligent Computing and Informatics. IRICT 2019. Advances in Intelligent Systems and Computing, vol 1073. Springer, Cham. https://doi.org/10.1007/978-3-030-33582-3_19

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