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
Dans cet article, nous construisons un modèle de disponibilité logicielle en considérant le nombre d'actions de restauration. Nous corrélons les caractéristiques de défaillance et de restauration du système logiciel avec le nombre cumulé de défauts corrigés. De plus, nous considérons un environnement de débogage imparfait où les défauts détectés ne sont pas toujours corrigés et supprimés du système. Le comportement du système en fonction du temps, alternant entre des états haut et bas, est décrit par un processus de Markov. À partir de ce modèle, nous pouvons déduire des mesures quantitatives pour l'évaluation de la disponibilité des logiciels en tenant compte du nombre d'actions de restauration. Enfin, nous montrons des exemples numériques d’analyse de disponibilité de logiciels.
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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 -