|Title||Advancing Testing Methods with the Explicit Consideration of Environmental Uncertainty|
|Project(s)||MBT4CPS: Model-Based Testing For Cyber-Physical Systems|
|Publication Type||Talk, keynote|
|Year of Publication||2017|
|Location of Talk||MBSE Seminar on Uncertainty, Nanjing University|
As compared with classical software/system testing, uncertainty-wise testing explicitly addresses known uncertainty about the behavior of a System Under Test (SUT), its operating environment, and interactions between the SUT and its operational environment, across all testing phases, including test design, test generation, test optimization, and test execution, with the aim to mainly achieve the following two goals. First, uncertainty-wise testing aims to ensure that the SUT deals with known uncertainty adequately. Second, uncertainty-wise testing should also be capable of learning new (previously unknown) uncertainties such that the SUT’s implementation can be improved to guard against newly learned uncertainties during its operation. The necessity to integrate uncertainty in testing is becoming imperative because of the emergence of new types of intelligent and communicating software-based systems such as Cyber-Physical Systems (CPSs). Intrinsically, such systems are exposed to uncertainty because of their interactions with highly indeterminate physical environments. In this talk, I will provide the experience of applying uncertainty-wise testing techniques that rely on modeling and search algorithms in several industrial contexts. Furthermore, the vision about this new testing paradigm and its plausible future research directions will be presented.