|Title||Prevent: a Predictive Run-time Verification Framework Using Statistical Learning|
|Publication Type||Conference Paper|
|Year of Publication||2018|
|Authors||Babaee, R., A. Gurfinkel, and S. Fischmeister|
|Conference Name||16th International Conference on Software Engineering and Formal Methods|
|Conference Location||Toulouse, France|
Run-time Verification (RV) is an essential component of developing cyber-physical systems, where often the actual model of the system is infeasible to obtain or is not available. In the absence of a model, i.e., black-box systems, RV techniques evaluate a property on the execution path of the system and reach a verdict that the current state of the system satisfies or violates a given property.