Software testing for cyber-physical systems suffering uncertainty

Abstract

Cyber-physical systems (CPS) represent an important part of the software infrastructure in the ternary human-cyber-physical universe. In this new era, the CPS software should be continually adapting and evolving. Such constantly-growing CPS software is capable of handling emerging software environments, developing models, and executing platforms. However, environmental uncertainty poses challenges to CPS testing. In this article, the challenges of CPS testing caused by environmental uncertainty are studied. A comprehensive analysis of the impact of environmental uncertainty on CPS testing is conducted, and a research framework for effective and efficient testing CPS is proposed. Based on the proposed framework, the state-of-the-art testing CPS software is discussed, and three testing techniques that address environmental uncertainty are introduced, including a test input generation approach (SIT), a test oracle generation approach (CoMID), and an environmental suitability evaluation approach (SynEva). The experiments are conducted using an illustrative self-adaptive robot car, and the obtained experimental results show that the three proposed approaches can provide effective CPS testing.