Automated Differential Testing for Energy-Efficient Control Software

Cyber-physical systems (CPS) are integrated systems of computerbased algorithms and physical components interacting with en­ vironmental effects. In such systems, autonomous behaviors and overall performance mainly depend on a control software. Thus, it is crucial to test and analyze the control software of the CPS in various perspectives. One of the critical perspectives is energy efficiency because many cyber-physical systems (e.g. unmanned aerial vehicles, autonomous cars, health-care devices) operate with limited energy sources such as batteries. In this paper, we pro­ pose CPSDiff: an energy-aware differential testing framework that generates test inputs to expose the maximal difference between two control programs in energy consumption. Our test generation technique uses meta-heuristic searching to find the input that max­ imizes the energy consumption difference. The difference-revealing ability of our technique outperforms the random search algorithm and hill-climbing search algorithm. Our evaluation on two popu­ lar unmanned aerial vehicle control programs provides a detailed comparison of their energy consumption under the same condition with a universal robotics simulator; CPSDiff found the input which exposes maximum battery consumption difference of around 47%.