Causality-based Model Checking

Bernd Finkbeiner and Andrey Kupriyanov

Model checking is usually based on a comprehensive traversal of the state space. Causality-based model checking is a radically different approach that instead analyzes the cause-effect relationships in a program. We give an overview on a new class of model checking algorithms that capture the causal relationships in a special data structure called concurrent traces. Concurrent traces identify key events in an execution history and link them through their cause-effect relationships. The model checker builds a tableau of concurrent traces, where the case splits represent different causal explanations of a hypothetical error. Causality-based model checking has been implemented in the ARCTOR tool, and applied to previously intractable multi-threaded benchmarks.

Second International Workshop on Causal Reasoning for Embedded and Safety-critical Systems Technologies (CREST 2017).