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Applying PNZ Model in Reliability Prediction of Component-Based Systems and Fault Tolerance Structures Technique

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Abstract

Reliability is the chief quality that one wishes for in anything. Reliability is also the main issue with computer systems. One of the purposes of system reliability analysis is to identify the weakness in a system and to quantify the impact of component failures. However, existing reliability prediction approaches for component-based software systems are limited in their applicability because they either neglect or do not support modeling explicitly several factors like error propagation, software fault tolerance mechanisms. In this paper, we evaluate reliability prediction of component-based system and fault tolerance structures technique by applying Pham Nordmann Zhang (PNZ) model, one of the best models based on non homogeneous Poisson process. Our approach uses a reliability modeling schema whose models are automatically transformed by a reliability prediction tool into PNZ models for reliability predictions and sensitivity analyses. Via these our case studies, we demonstrate its applicability and introduce how much reliability of software system can be improved by using fault tolerance structures technique.

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Acknowledgement

This research was supported by The National Foundation for Science and Technology Development (NAFOSTED) under Grant 102.03-2013.39: Automated verification and error localization methods for component-based software.

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Correspondence to Pham Binh .

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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Binh, P., Quyet-Thang, H., Thanh-Hung, N., Hung-Cuong, N. (2016). Applying PNZ Model in Reliability Prediction of Component-Based Systems and Fault Tolerance Structures Technique. In: Vinh, P., Alagar, V. (eds) Context-Aware Systems and Applications. ICCASA 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 165. Springer, Cham. https://doi.org/10.1007/978-3-319-29236-6_27

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  • DOI: https://doi.org/10.1007/978-3-319-29236-6_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29235-9

  • Online ISBN: 978-3-319-29236-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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