A General Trace-Based Framework of Logical Causality

Gößler, Gregor; Métayer, Daniel Le

doi:10.1007/978-3-319-07602-7_11

Cited by 20 publications

(41 citation statements)

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“…, C J is essentially a refinement of the system property. This is also an equivalent assumption as in [8,18] which stipulates that when a system property violation occurs, there must be at least one component property violation among C 1 , . .…”

Section: Definition 4 (System)mentioning

confidence: 99%

“…Trace Reconstruction with Separable Components. We use the construction of cone of influence, adapted from [8], to over-approximate the impact of the faulty components on the rest of the system. Informally, when a value has changed in a snapshot on a system trace, then the ones in the cone of influence must be updated accordingly to reflect the impact of this change.…”

Section: Separable Componentsmentioning

confidence: 99%

“…Our line of work [9,18,8,19,7] starts with preliminary definitions of causalities for component-based systems [9,18] and extends to real-time settings for system definitions with logical constraints [19], synchronous systems [8], and timed automata [7]. A salient difference of our work from existing ones is that, although we assume components are black-boxes, we take expected component behaviors specified in component properties as guidelines for trace reconstruction.…”

Section: Related Workmentioning

confidence: 99%

“…In our previous work in [9,18,8], we took a step further and considered the problem of causality analysis for componentbased systems. We formalized counterfactual reasoning ("what would the system execution be should a component have behaved correctly?")…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, we proposed a general causality analysis framework in [18,8], and identified four major steps in causality analysis. First, the set F of all faulty components with respect to their corresponding component properties are identified.…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid Approach to Causality Analysis

Wang

Geoffroy

Gößler

et al. 2015

Runtime Verification

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In component-based safety-critical systems, when a system safety property is violated, it is necessary to analyze which components are the cause. Given a system execution trace that exhibits component faults leading to a property violation, our causality analysis formalizes a notion of counterfactual reasoning (\what would the system behavior be if a component had been correct?") and algorithmically derives such alternative system behaviors, without re-executing the system itself. In this paper, we show that we can improve precision of the analysis if 1) we can emulate execution of components instead of relying on their contracts, and 2) take into consideration input/output dependencies between components to avoid blaming components for faults induced by other components. We demonstrate the utility of the extended analysis with a case study for a closed-loop patient-controlled analgesia system. Abstract. In component-based safety-critical systems, when a system safety property is violated, it is necessary to analyze which components are the cause. Given a system execution trace that exhibits component faults leading to a property violation, our causality analysis formalizes a notion of counterfactual reasoning ("what would the system behavior be if a component had been correct?") and algorithmically derives such alternative system behaviors, without re-executing the system itself. In this paper, we show that we can improve precision of the analysis if 1) we can emulate execution of components instead of relying on their contracts, and 2) take into consideration input/output dependencies between components to avoid blaming components for faults induced by other components. We demonstrate the utility of the extended analysis with a case study for a closed-loop patient-controlled analgesia system.

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Section: Definition 4 (System)mentioning

confidence: 99%

Section: Separable Componentsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Hybrid Approach to Causality Analysis

Wang

Geoffroy

Gößler

et al. 2015

Runtime Verification

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Explaining Hyperproperty Violations

Coenen

Dachselt

Finkbeiner

et al. 2022

Lecture Notes in Computer Science

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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 as a counterexample. Fixing the erroneous relations between traces in the system that led to the counterexample is a difficult manual effort that highly benefits from additional explanations. In this paper, we present an explanation method for counterexamples to hyperproperties described in the specification logic HyperLTL. We extend Halpern and Pearl’s definition of actual causality to sets of traces witnessing the violation of a HyperLTL formula, which allows us to identify the events that caused the violation. We report on the implementation of our method and show that it significantly improves on previous approaches for analyzing counterexamples returned by HyperLTL model checkers.

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