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Machine learning enables systems to build and update domain models based on runtime observations. In this paper, we study statistical model checking and runtime verification for systems with this ability. Two challenges arise: (1) Models built from limited runtime data yield uncertainty to be dealt with. (2) There is no definition of satisfaction w.r.t. uncertain hypotheses. We propose such a definition...
We introduce Stacked Thompson Bandits (STB) for efficiently generating plans that are likely to satisfy a given bounded temporal logic requirement. STB uses a simulation for evaluation of plans, and takes a Bayesian approach to using the resulting information to guide its search. In particular, we show that stacking multiarmed bandits and using Thompson sampling to guide the action selection process...
Virtualization technology has the potential to notably advance the automation process in the domain of cyber-physical systems (CPS). It can improve both dependability and availability as well as significantly reduce the procurement, operation and maintenance costs of such systems. However, in the context of virtualization, research has put the most emphasis on topics of hardware utilization and fault-tolerance...
We discuss key challenges of software engineering for distributed autonomous real-time systems and introduce a taxonomy for areas of interest with respect to the development of such systems.
Motivated by runtime verification of QoS requirements in self-adaptive and self-organizing systems that are able to reconfigure their structure and behavior in response to runtime data, we propose a QoS-aware variant of Thompson sampling for multi-armed bandits. It is applicable in settings where QoS satisfaction of an arm has to be ensured with high confidence efficiently, rather than finding the...
In order to accurately predict future states of a smart cyber-physical system, which can change its behavior to a large degree in response to environmental influences, the existence of precise models of the system and its surroundings is demandable. In machine engineering, ultra-high fidelity simulations have been developed to better understand both constraints in system design and possible consequences...
The need to interact with complex environments that are often not well understood at design time makes the development of smart cyber-physical systems (sCPS) a challenging endeavor. We propose a set of practices and tools that support the design and implementation of sCPS using continuous collaboration -- a development lifecycle and architecture to continuously incorporate data gained from the operation...
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