Fault Tree Analysis of Software-Controlled Component Systems Based on Second-Order Probabilities

Forster, Marc R.; Trapp, Mario

doi:10.1109/issre.2009.22

Cited by 13 publications

(7 citation statements)

References 33 publications

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“…More generally, Forster and Trapp [149] suggest that BE probabilities can be specified as intervals, within which the actual probabilities are sure to lie. Their method uses Monte Carlo simulation treating these intervals as bounds on a uniform distribution (although they mention that arbitrary distributions may be used) to compute the second-order probability mass function for the TE probability.…”

Section: Fta With Fuzzy Numbersmentioning

confidence: 99%

Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools

Ruijters

Stoelinga

2015

Computer Science Review

583

368

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Reliability Risk analysis Dynamic Fault Trees Graphical models Dependability evaluation A B S T R A C T Fault tree analysis (FTA) is a very prominent method to analyze the risks related to safety and economically critical assets, like power plants, airplanes, data centers and web shops. FTA methods comprise of a wide variety of modeling and analysis techniques, supported by a wide range of software tools. This paper surveys over 150 papers on fault tree analysis, providing an in-depth overview of the state-of-the-art in FTA. Concretely, we review standard fault trees, as well as extensions such as dynamic FT, repairable FT, and extended FT. For these models, we review both qualitative analysis methods, like cut sets and common cause failures, and quantitative techniques, including a wide variety of stochastic methods to compute failure probabilities. Numerous examples illustrate the various approaches, and tables present a quick overview of results.

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Section: Fta With Fuzzy Numbersmentioning

confidence: 99%

Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools

Ruijters

Stoelinga

2015

Computer Science Review

583

368

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“…Förster [11] claims: "Software does not fail randomly but will invariably fail again in the same way under the same conditions. While for mass-produced hardware parts it is possible to assign a failure probability, for software a similar assumption does not seem entirely realistic".…”

Section: System Safetymentioning

confidence: 99%

Distributed optimization on super computers

Etemaadi

Chaudron

2014

Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation

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Nowadays advanced software systems need to satisfy large number of quality attributes at the same time. It is a very complex optimization problem which software architects must address. Evolutionary algorithms can help architects to find optimal solutions which meet these conflicting quality attributes. However, these metaheuristic approaches in multiobjective problems especially for high dimensions mostly take so long time to be executed. One of the best solutions to speed up this process is distributing execution of evolutionary algorithm on multiple nodes of a super computer or on the cloud. This paper presents the results of distributed execution of evolutionary algorithm for multiobjective optimization of software architecture. We report implementation of two different ways for distributed execution of evolutionary algorithm: (1) Actor-based approach, (2) MapReduce approach. The case study in this experiment is an industrial software system which is derived from a real world automotive embedded system.The results of this computationally-intensive experiment on a super computer give us 81.27% parallelization efficiency for distribution among 5 nodes.

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“…Förster and Trapp [2] developed a Fault Tree based method to cope with the problem of few or no information about failures early in the development. They base the analysis on Component Fault Trees (CFT) [4] to model system composition.…”

Section: Related Workmentioning

confidence: 99%

Modeling the Effects of Software on Safety and Reliability in Complex Embedded Systems

Steiner

Keller

Liggesmeyer

2012

Lecture Notes in Computer Science

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Abstract. The development of autonomous vehicle systems demands the increased usage of software based control mechanisms. Generally, this leads to very complex systems, whose proper functioning has to be ensured. In our work we aim at investigating and assessing the potential effects of software issues on the safety, reliability and availability of complex embedded autonomous systems. One of the key aspects of the research concerns the mapping of functional descriptions in form of integrated behavior-based control networks to State-Event Fault Tree models.

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Fault Tree Analysis of Software-Controlled Component Systems Based on Second-Order Probabilities

Cited by 13 publications

References 33 publications

Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools

Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools

Distributed optimization on super computers

Modeling the Effects of Software on Safety and Reliability in Complex Embedded Systems

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