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A Hybrid Approach to Causality Analysis

  • Shaohui Wang
  • Yoann Geoffroy
  • Gregor Gössler
  • Oleg Sokolsky
  • Insup Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9333)

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.

Keywords

Patient Control Analgesia Causality Analysis Separable Component System Execution System Trace 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Shaohui Wang
    • 1
  • Yoann Geoffroy
    • 2
  • Gregor Gössler
    • 2
  • Oleg Sokolsky
    • 1
  • Insup Lee
    • 1
  1. 1.Department of Computer and Information ScienceUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.INRIA Grenoble – Rhône-Alpes and Univ. Grenoble AlpesGrenobleFrance

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