Relevant bibliographies by topics / Imperfect Fault Coverage

Academic literature on the topic 'Imperfect Fault Coverage'

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Published: 10 March 2023

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Journal articles on the topic "Imperfect Fault Coverage"

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Dugan, J. B. "Fault trees and imperfect coverage." IEEE Transactions on Reliability 38, no. 2 (June 1989): 177–85. http://dx.doi.org/10.1109/24.31102.

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Li, Qiuying, and Hoang Pham. "Software Reliability Modeling Incorporating Fault Detection and Fault Correction Processes with Testing Coverage and Fault Amount Dependency." Mathematics 10, no. 1 (December 24, 2021): 60. http://dx.doi.org/10.3390/math10010060.

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This paper presents a general testing coverage software reliability modeling framework that covers imperfect debugging and considers not only fault detection processes (FDP) but also fault correction processes (FCP). Numerous software reliability growth models have evaluated the reliability of software over the last few decades, but most of them attached importance to modeling the fault detection process rather than modeling the fault correction process. Previous studies analyzed the time dependency between the fault detection and correction processes and modeled the fault correction process as a delayed detection process with a random or deterministic time delay. We study the quantitative dependency between dual processes from the viewpoint of fault amount dependency instead of time dependency, then propose a generalized modeling framework along with imperfect debugging and testing coverage. New models are derived by adopting different testing coverage functions. We compared the performance of these proposed models with existing models under the context of two kinds of failure data, one of which only includes observations of faults detected, and the other includes not only fault detection but also fault correction data. Different parameter estimation methods and performance comparison criteria are presented according to the characteristics of different kinds of datasets. No matter what kind of data, the comparison results reveal that the proposed models generally give improved descriptive and predictive performance than existing models.
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XIANG, Jianwen, Fumio MACHIDA, Kumiko TADANO, Yoshiharu MAENO, and Kazuo YANOO. "Coverage of Irrelevant Components in Systems with Imperfect Fault Coverage." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E96.A, no. 7 (2013): 1649–52. http://dx.doi.org/10.1587/transfun.e96.a.1649.

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Xiang, Jianwen, Fumio Machida, Kumiko Tadano, and Yoshiharu Maeno. "An Imperfect Fault Coverage Model With Coverage of Irrelevant Components." IEEE Transactions on Reliability 64, no. 1 (March 2015): 320–32. http://dx.doi.org/10.1109/tr.2014.2363155.

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Amari, S. V., J. B. Dugan, and R. B. Misra. "Optimal reliability of systems subject to imperfect fault-coverage." IEEE Transactions on Reliability 48, no. 3 (1999): 275–84. http://dx.doi.org/10.1109/24.799899.

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Tannous, Ola, Liudong Xing, Rui Peng, and Min Xie. "Reliability of warm-standby systems subject to imperfect fault coverage." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 228, no. 6 (July 14, 2014): 606–20. http://dx.doi.org/10.1177/1748006x14541255.

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Jain, Madhu, and Rakesh Kumar Meena. "Fault tolerant system with imperfect coverage, reboot and server vacation." Journal of Industrial Engineering International 13, no. 2 (December 26, 2016): 171–80. http://dx.doi.org/10.1007/s40092-016-0180-8.

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Peng, Rui, Qing Qing Zhai, Lei Shi, and Jun Yang. "Multi-Valued Decision Diagram Based Reliability Analysis of Demand-Based Warm Standby Systems with Imperfect Fault Coverage." Applied Mechanics and Materials 513-517 (February 2014): 4161–66. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.4161.

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In many real-world applications, warm standby redundancy is a commonly applied technique that can compromise recovery time and energy consumption in the fault-tolerant system design. It is considered as a generalization of cold standby and hot standby techniques and has attracted lots of research attentions. In this paper, a demand-based warm standby system subject to imperfect fault coverage is studied. The demand-based system consists of components with different capacities and fails if the cumulative capacity of working components is lower than the desired system demand. To adapt to different fault covering mechanisms, this paper considers two different kinds of fault coverage models, i.e. element level coverage and fault level coverage. A multi-valued decision diagram based approach is proposed to analyze the system reliability. The suggested method is combinatorial and has no limitation on the type of time-to-failure distributions for system components. An example is presented to illustrate the application and advantage of the proposed method.
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Akhtar, S. "Reliability of k-out-of-n:G systems with imperfect fault-coverage." IEEE Transactions on Reliability 43, no. 1 (March 1994): 101–6. http://dx.doi.org/10.1109/24.285121.

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Amari, S. V., J. B. Dugan, and R. B. Misra. "A separable method for incorporating imperfect fault-coverage into combinatorial models." IEEE Transactions on Reliability 48, no. 3 (1999): 267–74. http://dx.doi.org/10.1109/24.799898.

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Dissertations / Theses on the topic "Imperfect Fault Coverage"

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Ye, Luyao. "Analysis of the Components and Systems Relevance." Doctoral thesis, 2021. http://hdl.handle.net/2158/1251754.

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In systems with Imperfect Fault Coverage (IFC), all components are subject to uncovered failures, possibly threatening the whole system. Therefore, to improve the system reliability, it is important to timely detect, identify, and shut down the components that are no more relevant for the system operation. Thus, the Irrelevance Coverage Model (ICM) was proposed based on the Imperfect Fault Coverage Model (IFCM). In the ICM, any component detected as irrelevant can be safely shut down without reducing the system reliability and preventing the case where its eventual failure may remain uncovered and cause a direct system failure. This not only improves the system reliability but also saves energy. This thesis solves the problem of quantitative evaluation of component relevance. It assumes that components have independent and identically distributed~(i.i.d.) lifetimes to describe only the impact of the system design on the system reliability and energy consumption. To this end, the Component Relevance is proposed to represent the probability that a component can keep its relevance throughout the system lifetime. Then, the Birnbaum Importance (BI) measure is applied to the system with ICM. The BI measure with ICM considers the relevance of the components while considering the reliability of the components. At the same time, the changes of the importance of the components in three different models, i.e., Perfect Fault Coverage Model (PFCM), Imperfect Fault Coverage Model (IFCM), and ICM, are analyzed. Moreover, the Dynamic Relevance Measure~(DRM) is defined to characterize the irrelevant components in different stages of the system lifetime depending on the number of occurred component failures, supporting the evaluation of the probability that the system fails due to uncovered failures of irrelevant components. Also, the gain in shutting down the irrelevant components in the ICM can be evaluated both in terms of the energy saved and the fraction of the average system lifetime during the system is not coherent. Finally, the system reliability over time is also efficiently derived, both in the case that irrelevance is not considered and in the case that irrelevant components can be immediately isolated, notably supporting any general (i.e.,~non-Markovian) distribution for the failure time of components. The feasibility and effectiveness of the proposed analysis methods are assessed on two real-scale case studies addressing the reliability evaluation of a flight control system and a multi-hop Wireless Sensor Network~(WSN). I have obtained the most important components for the left edge flap of the F18 flight control system to improve the component reliability, which improves system reliability more obviously. For the different topologies of WSN, the reliability and relevance of the Diagonal topology are better than the Orthogonal topology. So the WSN with Diagonal topology should be given priority in the system phase.
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Books on the topic "Imperfect Fault Coverage"

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Myers, Albert. Complex system reliability: Multichannel systems with imperfect fault coverage. 2nd ed. [London: Springer, 2010.

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Myers, Albert. Complex System Reliability: Multichannel Systems with Imperfect Fault Coverage. Springer London, Limited, 2014.

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Myers, Albert. Complex System Reliability: Multichannel Systems with Imperfect Fault Coverage. Springer London, Limited, 2010.

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Myers, Albert. Complex System Reliability: Multichannel Systems with Imperfect Fault Coverage. Springer, 2011.

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Book chapters on the topic "Imperfect Fault Coverage"

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Levitin, G., S. H. Ng, R. Peng, and M. Xie. "Reliability of Systems Subjected to Imperfect Fault Coverage." In Springer Series in Reliability Engineering, 159–77. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4971-2_8.

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Peng, Rui, Ola Tannous, Liudong Xing, and Min Xie. "Reliability of Warm Standby Systems with Imperfect Fault Coverage." In Applied Reliability Engineering and Risk Analysis, 246–55. Chichester, UK: John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118701881.ch18.

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Xiang, Jianwen, Fumio Machida, Kumiko Tadano, and Yoshiharu Maeno. "Analysis of Persistence of Relevance in Systems with Imperfect Fault Coverage." In Lecture Notes in Computer Science, 109–24. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10506-2_8.

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Peng, Rui, Qingqing Zhai, and Jun Yang. "Reliability of Warm Standby Systems with Imperfect Fault Coverage and Switching Failure." In Reliability Modelling and Optimization of Warm Standby Systems, 59–78. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1792-8_5.

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Postma, André, Gerie Hartman, and Thijs Krol. "Removal of all faulty nodes from a fault-tolerant service by means of distributed diagnosis with imperfect fault coverage." In Dependable Computing — EDCC-2, 383–402. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61772-8_50.

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Jain, Madhu, and Pankaj Kumar. "Availability Prediction of Repairable Fault-Tolerant System with Imperfect Coverage, Reboot, and Common Cause Failure." In Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models, 93–103. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0857-4_6.

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"Imperfect Fault Coverage." In Springer Series in Reliability Engineering, 39–64. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-414-2_4.

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"Imperfect Fault Coverage." In Dynamic System Reliability, 27–47. Chichester, UK: John Wiley & Sons, Ltd, 2019. http://dx.doi.org/10.1002/9781119507642.ch3.

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Manglik, Monika, and Mangey Ram. "Multistate Multifailures System Analysis With Reworking Strategy and Imperfect Fault Coverage." In Advances in System Reliability Engineering, 243–65. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-815906-4.00010-5.

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Conference papers on the topic "Imperfect Fault Coverage"

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Khosravi, Faramarz, Hananeh Aliee, and Jürgen Teich. "System-level reliability analysis considering imperfect fault coverage." In ESWEEK'17: THIRTEENTH EMBEDDED SYSTEM WEEK. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3139315.3141787.

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Wang, Zixiang, Siwei Zhou, Dongdong Zhao, and Jianwen Xiang. "Reliability-redundancy allocation problem considering imperfect fault coverage." In 2021 IEEE 21st International Conference on Software Quality, Reliability and Security (QRS). IEEE, 2021. http://dx.doi.org/10.1109/qrs54544.2021.00051.

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Amari, Suprasad, Albert Myers, and Antoine Rauzy. "An Efficient Algorithm To Analyze New Imperfect Fault Coverage Models." In 2007 Proceedings Annual Reliability and Maintainability Sympsoium. IEEE, 2007. http://dx.doi.org/10.1109/rams.2007.328078.

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Rani, Poonam, and G. L. Pahuja. "Reliability Analysis of Flight Control System under Perfect and Imperfect Fault Coverage." In 2018 3rd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT). IEEE, 2018. http://dx.doi.org/10.1109/rteict42901.2018.9012397.

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Fernández, Álvaro, and Norvald Stol. "Influence of software and hardware failures with imperfect fault coverage on PONs OPEX." In 2015 International Conference on Optical Network Design and Modeling (ONDM). IEEE, 2015. http://dx.doi.org/10.1109/ondm.2015.7127269.

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Xiong, Xiao, and Ping Zhang. "Reliability analysis of flight control system for large civil aircraft with Imperfect Fault Coverage Model." In 2012 Prognostics and System Health Management Conference (PHM). IEEE, 2012. http://dx.doi.org/10.1109/phm.2012.6228935.

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Song, Xiaogang, Zhengjun Zhai, Peican Zhu, Yangming Guo, and Yunpeng Zhang. "A stochastic approach for evaluating the reliability of multi-stated phased-mission systems with imperfect fault coverage." In 2017 Prognostics and System Health Management Conference (PHM-Harbin). IEEE, 2017. http://dx.doi.org/10.1109/phm.2017.8079163.

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Li, Xiaopeng, Hu Wan, Zhean Gong, Zhonglai Wang, and Hong-Zhong Huang. "Flight control system reliability study based on hIdden Markov Model imperfect fault coverage model-Hidden Markov Model." In 2011 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE). IEEE, 2011. http://dx.doi.org/10.1109/icqr2mse.2011.5976582.

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Li, Qiuying, and Chengyong Mao. "Considering Testing-Coverage and Fault Removal Efficiency Subject to the Random Field Environments with Imperfect Debugging in Software Reliability Assessment." In 2016 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW). IEEE, 2016. http://dx.doi.org/10.1109/issrew.2016.13.

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