21,087 research outputs found
Counterfactual Causality from First Principles?
In this position paper we discuss three main shortcomings of existing
approaches to counterfactual causality from the computer science perspective,
and sketch lines of work to try and overcome these issues: (1) causality
definitions should be driven by a set of precisely specified requirements
rather than specific examples; (2) causality frameworks should support system
dynamics; (3) causality analysis should have a well-understood behavior in
presence of abstraction.Comment: In Proceedings CREST 2017, arXiv:1710.0277
Causality and Temporal Dependencies in the Design of Fault Management Systems
Reasoning about causes and effects naturally arises in the engineering of
safety-critical systems. A classical example is Fault Tree Analysis, a
deductive technique used for system safety assessment, whereby an undesired
state is reduced to the set of its immediate causes. The design of fault
management systems also requires reasoning on causality relationships. In
particular, a fail-operational system needs to ensure timely detection and
identification of faults, i.e. recognize the occurrence of run-time faults
through their observable effects on the system. Even more complex scenarios
arise when multiple faults are involved and may interact in subtle ways.
In this work, we propose a formal approach to fault management for complex
systems. We first introduce the notions of fault tree and minimal cut sets. We
then present a formal framework for the specification and analysis of
diagnosability, and for the design of fault detection and identification (FDI)
components. Finally, we review recent advances in fault propagation analysis,
based on the Timed Failure Propagation Graphs (TFPG) formalism.Comment: In Proceedings CREST 2017, arXiv:1710.0277
The xSAP Safety Analysis Platform
This paper describes the xSAP safety analysis platform. xSAP provides several
model-based safety analysis features for finite- and infinite-state synchronous
transition systems. In particular, it supports library-based definition of
fault modes, an automatic model extension facility, generation of safety
analysis artifacts such as Dynamic Fault Trees (DFTs) and Failure Mode and
Effects Analysis (FMEA) tables. Moreover, it supports probabilistic evaluation
of Fault Trees, failure propagation analysis using Timed Failure Propagation
Graphs (TFPGs), and Common Cause Analysis (CCA). xSAP has been used in several
industrial projects as verification back-end, and is currently being evaluated
in a joint R&D Project involving FBK and The Boeing Company
QuantUM: Quantitative Safety Analysis of UML Models
When developing a safety-critical system it is essential to obtain an
assessment of different design alternatives. In particular, an early safety
assessment of the architectural design of a system is desirable. In spite of
the plethora of available formal quantitative analysis methods it is still
difficult for software and system architects to integrate these techniques into
their every day work. This is mainly due to the lack of methods that can be
directly applied to architecture level models, for instance given as UML
diagrams. Also, it is necessary that the description methods used do not
require a profound knowledge of formal methods. Our approach bridges this gap
and improves the integration of quantitative safety analysis methods into the
development process. All inputs of the analysis are specified at the level of a
UML model. This model is then automatically translated into the analysis model,
and the results of the analysis are consequently represented on the level of
the UML model. Thus the analysis model and the formal methods used during the
analysis are hidden from the user. We illustrate the usefulness of our approach
using an industrial strength case study.Comment: In Proceedings QAPL 2011, arXiv:1107.074
Environmental Audit improvements in industrial systems through FRAM
Environmental risk management requires specific methodologies to focus audit activities on the most critical elements of production systems. Limited resources require a clear motivation to put attention on specific technological, human, organizational components, and often should address the monitor of interactions among these elements. Recent research in environmental risk looks at methods to deal with complexity as interesting tools to reduce real impacts on pollution and consumption. In this paper, we provide evidence of the advantage in using the Functional Resonance Analysis Method (FRAM), not only to identify the criticalities of a complex production system but to provide a methodology to continuously improve the audit activities in parallel with the introduction of technique to reduce environmental risk. The case study presents the evolution of environmental audit in a sinter plant, proving the need for a review of the criticality list and the successful application of FRAM to refocus the control activities
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