Yes / In the automotive industry, modern cyber-physical systems feature cooperation and autonomy. Such systems share information to enable collaborative functions, allowing dynamic component integration and architecture reconfiguration. Given the safety-critical nature of the applications involved, an approach for addressing safety in the context of reconfiguration impacting functional and non-functional properties at runtime is needed. In this paper, we introduce a concept for runtime safety analysis and decision input for open adaptive systems. We combine static safety analysis and evidence collected during operation to analyse, reason and provide online recommendations to minimize deviation from a system’s safe states. We illustrate our concept via an abstract vehicle platooning system use case. / DEIS H2020 Project under Grant 732242.

No / In the automotive industry, modern cyber-physical systems feature cooperation and autonomy. Such systems share information to enable collaborative functions, allowing dynamic component integration and architecture reconfiguration. Given the safety-critical nature of the applications involved, an approach for addressing safety in the context of reconfiguration impacting functional and non-functional properties at runtime is needed. In this paper, we introduce a concept for runtime safety analysis and decision input for open adaptive systems. We combine static safety analysis and evidence collected during operation to analyse, reason and provide online recommendations to minimize deviation from a system’s safe states. We illustrate our concept via an abstract vehicle platooning system use case. / This conference paper is available to view at http://hdl.handle.net/10454/17415.

No

Yes / Fault Tree Analysis (FTA) is a well-established and well-understood technique, widely used for dependability evaluation of a wide range of systems. Although many extensions of fault trees have been proposed, they suffer from a variety of shortcomings. In particular, even where software tool support exists, these analyses require a lot of manual effort. Over the past two decades, research has focused on simplifying dependability analysis by looking at how we can synthesise dependability information from system models automatically. This has led to the field of model-based dependability analysis (MBDA). Different tools and techniques have been developed as part of MBDA to automate the generation of dependability analysis artefacts such as fault trees. Firstly, this paper reviews the standard fault tree with its limitations. Secondly, different extensions of standard fault trees are reviewed. Thirdly, this paper reviews a number of prominent MBDA techniques where fault trees are used as a means for system dependability analysis and provides an insight into their working mechanism, applicability, strengths and challenges. Finally, the future outlook for MBDA is outlined, which includes the prospect of developing expert and intelligent systems for dependability analysis of complex open systems under the conditions of uncertainty.