Causality Analysis for Concurrent Reactive Systems (Extended Abstract)
This work addresses causality analysis for debugging, error resilience, and liability resolution in concurrent reactive systems, offering a formal framework that integrates previously independent notions, but it appears incremental as it builds on prior work in AI and formal methods.
The authors tackled the problem of explaining safety property violations in concurrent reactive systems by developing a comprehensive language-theoretic causality analysis framework, which uniformly expresses existing causality notions and defines new ones, with automata-based algorithms provided for computing causal sets and their complexities.
We present a comprehensive language theoretic causality analysis framework for explaining safety property violations in the setting of concurrent reactive systems. Our framework allows us to uniformly express a number of causality notions studied in the areas of artificial intelligence and formal methods, as well as define new ones that are of potential interest in these areas. Furthermore, our formalization provides means for reasoning about the relationships between individual notions which have mostly been considered independently in prior work; and allows us to judge the appropriateness of the different definitions for various applications in system design. In particular, we consider causality analysis notions for debugging, error resilience, and liability resolution in concurrent reactive systems. Finally, we present automata-based algorithms for computing various causal sets based on our language-theoretic encoding, and derive the algorithmic complexities.