Model-based diversity-driven learn-to-rank test case prioritization

Ting Shu, Zhanxiang He, Xuesong Yin, Zuohua Ding, Mengchu Zhou

Abstract: Highlights•A novel approach, named DLTCP, optimizes model-based test case prioritization.•A fusion framework is proposed to combine multiple similarity metrics.•A Learn-to-rank model is constructed to improve early fault detection performance.•The superiority of DLTCP is verified on five classic benchmark models.