Abstract
We propose a multi-objective genetic algorithm method to prioritize state-based test cases to achieve several competing objectives such as budget and coverage of data flow information, while hopefully detecting faults as early as possible when executing prioritized test cases. The experimental results indicate that our approach is useful and effective: prioritizations quickly achieve maximum data flow coverage and this results in early fault detection; prioritizations perform much better than random orders with much smaller variance.
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Briand, L., Labiche, Y., Chen, K. (2013). A Multi-objective Genetic Algorithm to Rank State-Based Test Cases. In: Ruhe, G., Zhang, Y. (eds) Search Based Software Engineering. SSBSE 2013. Lecture Notes in Computer Science, vol 8084. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39742-4_7
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DOI: https://doi.org/10.1007/978-3-642-39742-4_7
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