Causality analysis and fault ascription in component-based systems - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles Theoretical Computer Science Year : 2020

Causality analysis and fault ascription in component-based systems


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 failure of said system. Our framework uses configuration structures as a general semantical model to handle truly concurrent executions, partial and distributed observations in a uniform way. As a first contribution, and in contrast with most of the current literature on counterfactual analysis which relies heavily on a set of toy examples, we first define a set of expected formal properties for counterfactual builders, i.e. operators that build counterfactual executions. We then show that causality analyses that satisfy our requirements meet a set of elementary soundness and completeness properties. Finally we present a concrete causality analysis meeting all our requirements, and we show that it behaves well under refinement. We present several examples illustrating various phenomena such as causal over-determination or observational determinism, and we discuss the relationship of our approach with Halpern and Pearl's actual causality analysis. This article is the published version of
Fichier principal
Vignette du fichier
S0304397520303510.pdf (822.43 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02927216 , version 1 (22-08-2022)


Attribution - NonCommercial



Gregor Gössler, Jean-Bernard Stefani. Causality analysis and fault ascription in component-based systems. Theoretical Computer Science, 2020, 837, pp.158-180. ⟨10.1016/j.tcs.2020.06.010⟩. ⟨hal-02927216⟩
97 View
44 Download



Gmail Facebook X LinkedIn More