Context: Safety is of paramount importance for cyber–physical systems in domains such as
automotive, robotics, and avionics. Formal methods such as model checking are one way to …

The complexity of industrial processes imposes a lot of challenges in building accurate and
representative causal models for abnormal events diagnosis, control and maintenance of …

This paper is an introductory survey of available methods for the computation and
representation of probabilistic counterexamples for discrete-time Markov chains and …

Industries with safety-critical systems increasingly collect data on events occurring at the
level of system components, thus capturing instances of system failure or malfunction. With …

Hyperproperties relate multiple computation traces to each other. Model checkers for
hyperproperties thus return, in case a system model violates the specification, a set of traces …

For deterministic systems, a counterexample to a property can simply be an error trace,
whereas counterexamples in probabilistic systems are necessarily more complex. For …

Cyber-physical systems come with increasingly complex architectures and failure modes,
which complicates the task of obtaining accurate system reliability models. At the same time …

In precursory work we have developed causality checking, a fault localization method for
concurrent system models relying on the Halpern and Pearl counterfactual model of …

In addition to rigorously checking whether a system conforms to a specification, model
checking can provide valuable feedback in the form of succinct and understandable …

This article introduces a general framework for fault ascription, which consists in identifying,
within a multi-component system, the components whose faulty behavior has caused the …