The xSAP Safety Analysis Platform

Bittner, Benjamin; Bozzano, Marco; Cavada, Roberto; Cimatti, Alessandro; Gario, Marco; Griggio, Alberto; Mattarei, Cristian; Micheli, Andrea; Zampedri, Gianni

doi:10.1007/978-3-662-49674-9_31

Cited by 55 publications

(38 citation statements)

References 31 publications

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“…The analyses are supported by the following verification engines: nuXmv [9] for correctness checking; OCRA [10] for contract-based analysis; IMCA [19] and MRMC [20] for performance analysis by probabilistic model checking; slimsim [8] for statistical model checking and xSAP [1] for safety analysis.…”

Section: Toolset Overviewmentioning

confidence: 99%

“…In a recent effort funded by ESA, the results of this work have been thoroughly consolidated into a single release, which is now available. COMPASS 3.0 includes features originally included in distinct tool releases that diverged from the original development trunk 1 . The AUTOGEF and FAME projects focused on Fault Detection, Identification, and Recovery (FDIR) requirements modeling and development, and on fault propagation analysis; HASDEL extended formal analysis techniques to deal with the specific needs of launcher systems, with a strong focus on timed aspects of the model; and finally CATSY had the goal of improving the requirements specification process.…”

Section: Introductionmentioning

confidence: 99%

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COMPASS 3.0

Bozzano

Bruintjes

Cimatti

et al. 2019

Tools and Algorithms for the Construction and Analysis of Systems

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COMPASS (COrrectness, Modeling and Performance of AeroSpace Systems) is an international research effort aiming to ensure system-level correctness, safety, dependability and performability of onboard computer-based aerospace systems. In this paper we present COMPASS 3.0, which brings together the results of various development projects since the original inception of COMPASS. Improvements have been made both to the frontend, supporting an updated modeling language and user interface, as well as to the backend, by adding new functionalities and improving the existing ones. New features include Timed Failure Propagation Graphs, contract-based analysis, hierarchical fault tree generation, probabilistic analysis of non-deterministic models and statistical model checking.

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Section: Toolset Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

COMPASS 3.0

Bozzano

Bruintjes

Cimatti

et al. 2019

Tools and Algorithms for the Construction and Analysis of Systems

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“…It is derived from the standardized Aadl language and offers native fault modeling. xSAP is an extension of the NuSMV language that allows the explicit modeling of faults in NuSMV and allows the automatic calculation of Minimal Cut Sets …”

Section: Related Workmentioning

confidence: 99%

Quantitative and qualitative safety analysis of a hemodialysis machine with S#

Leupolz

Habermaier

Reif

2018

J Software Evolu Process

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This paper reports on our experiences of applying S# ("safety sharp") to model and analyze the case study "hemodialysis machine." The S# safety analysis approach focuses on the question, what happens if we place a controller with correct software into an unreliable environment. To answer that question, the S# toolchain natively supports the Deductive Cause Consequence Analysis, a fully automatic model checking-based safety analysis technique that determines all sets of component faults with the potential of causing a system hazard. Furthermore, S# can give an approximate estimate of the hazard's probability. To demonstrate our approach, we created a model with a simplified controller of the hemodialysis machine and relevant parts of its environment and performed a safety analysis using Deductive Cause Consequence Analysis. KEYWORDSdeductive cause consequence analysis, design tools and techniques, embedded domain specific language, executable models, formal methods, hemodialysis, model checking, quantitative analysis, safety analysis, simulation

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“…Cut sets are assignments to such variables that lead to the violation of the top level event. Formal verification tools for MBSA include xSAP [7].…”

Section: Fault Tree Analysismentioning

confidence: 99%

Causality and Temporal Dependencies in the Design of Fault Management Systems

Bozzano¹

2017

Electron. Proc. Theor. Comput. Sci.

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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.

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The xSAP Safety Analysis Platform

Cited by 55 publications

References 31 publications

COMPASS 3.0

COMPASS 3.0

Quantitative and qualitative safety analysis of a hemodialysis machine with S#

Causality and Temporal Dependencies in the Design of Fault Management Systems

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