Studies have shown that combinatorial testing can help programs detect hard-to-find software bugs that may not be revealed by test cases generated using other testing techniques. The first part of this talk focuses on traditional black-box requirements-based combinatorial testing. In particular, I will discuss results and lessons learned from two real-life industry applications: a control panel of a rail-road system and a Linux system. The second part extends the concept of combinatorial testing to a white-box structure-based setting. I will present an advanced coverage criterion, Combinatorial Decision Coverage, in conjunction with symbolic execution to achieve high coverage cost-effectively without suffering from potential space exploration. Finally, I will explain how combinatorial testing can be applied to a graph-based methodology for testing IoT (Internet of Things).
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