New Opportunities for Integrated Formal Methods Formal methods have provided approaches for investigating software engineering fundamentals and also have high potential to improve current practices in dependability assurance. In this article, we summarise known strengths and weaknesses of formal methods. From the perspective of the assurance of robots and autonomous systems(RAS), we highlight new opportunities for integrated formal methods and identify threats to their adoption to be mitigated. Based on these opportunities and threats, we develop an agenda for fundamental and empirical research on integrated formal methods and for successful transfer of validated research to RAS assurance. Furthermore, we outline our expectations on useful outcomes of such an agenda.

Incremental reasoning in probabilistic Signal Temporal Logic Abstract   Robot safety is of growing concern given recent developments in intelligent autonomous systems. For complex agents operating in uncertain, complex and rapidlychanging environments it is difficult to guarantee safety without imposing unrealistic assumptions and restrictions. It is therefore necessary to complement traditional formal verification with monitoring of the running system after deployment. Runtime verification can be used to monitor that an agent behaves according to a formal specification. The specification can contain safetyrelated requirements and assumptions about the environment, environmentagent interactions and agentagent interactions. A key problem is the uncertain and changing nature of the environment. This necessitates requirements on how probable a certain outcome is and on predictions of future states. We propose Probabilistic Signal Temporal Logic (ProbSTL) by extending Signal Temporal Logic with a sublanguage to allow statements over probabilities, observations and predictions. We further introduce and prove the correctness of the incremental stream reasoning technique progression over wellformed formulas in ProbSTL. Experimental evaluations demonstrate the applicability and benefits of ProbSTL for robot safety.