Yang Shi*, Xiaoyu Song, Marek Perkowski, Fu Li
CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2191-2207, 2022, DOI:10.32604/cmc.2022.018718
Abstract Search-based statistical structural testing (SBSST) is a promising technique that uses automated search to construct input distributions for statistical structural testing. It has been proved that a simple search algorithm, for example, the hill-climber is able to optimize an input distribution. However, due to the noisy fitness estimation of the minimum triggering probability among all cover elements (Tri-Low-Bound), the existing approach does not show a satisfactory efficiency. Constructing input distributions to satisfy the Tri-Low-Bound criterion requires an extensive computation time. Tri-Low-Bound is considered a strong criterion, and it is demonstrated to sustain a high fault-detecting ability. This article tries to… More >
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