The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Neste artigo, construímos um modelo de disponibilidade de software considerando o número de ações de restauração. Correlacionamos as características de falha e restauração do sistema de software com o número cumulativo de falhas corrigidas. Além disso, consideramos um ambiente de depuração imperfeito onde as falhas detectadas nem sempre são corrigidas e removidas do sistema. O comportamento dependente do tempo do sistema alternando entre estados ascendentes e descendentes é descrito por um processo de Markov. A partir deste modelo, podemos derivar medidas quantitativas para avaliação da disponibilidade de software considerando o número de ações de restauração. Por fim, mostramos exemplos numéricos de análise de disponibilidade de software.
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Koichi TOKUNO, Shigeru YAMADA, "Markovian Software Availability Measurement Based on the Number of Restoration Actions" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 5, pp. 835-841, May 2000, doi: .
Abstract: In this paper, we construct a software availability model considering the number of restoration actions. We correlate the failure and restoration characteristics of the software system with the cumulative number of corrected faults. Furthermore, we consider an imperfect debugging environment where the detected faults are not always corrected and removed from the system. The time-dependent behavior of the system alternating between up and down states is described by a Markov process. From this model, we can derive quantitative measures for software availability assessment considering the number of restoration actions. Finally, we show numerical examples of software availability analysis.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_5_835/_p
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@ARTICLE{e83-a_5_835,
author={Koichi TOKUNO, Shigeru YAMADA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Markovian Software Availability Measurement Based on the Number of Restoration Actions},
year={2000},
volume={E83-A},
number={5},
pages={835-841},
abstract={In this paper, we construct a software availability model considering the number of restoration actions. We correlate the failure and restoration characteristics of the software system with the cumulative number of corrected faults. Furthermore, we consider an imperfect debugging environment where the detected faults are not always corrected and removed from the system. The time-dependent behavior of the system alternating between up and down states is described by a Markov process. From this model, we can derive quantitative measures for software availability assessment considering the number of restoration actions. Finally, we show numerical examples of software availability analysis.},
keywords={},
doi={},
ISSN={},
month={May},}
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TY - JOUR
TI - Markovian Software Availability Measurement Based on the Number of Restoration Actions
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 835
EP - 841
AU - Koichi TOKUNO
AU - Shigeru YAMADA
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 5
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - May 2000
AB - In this paper, we construct a software availability model considering the number of restoration actions. We correlate the failure and restoration characteristics of the software system with the cumulative number of corrected faults. Furthermore, we consider an imperfect debugging environment where the detected faults are not always corrected and removed from the system. The time-dependent behavior of the system alternating between up and down states is described by a Markov process. From this model, we can derive quantitative measures for software availability assessment considering the number of restoration actions. Finally, we show numerical examples of software availability analysis.
ER -