NHPP-Based Software Reliability Model with Marshall-Olkin Failure Time Distribution

Xiao XIAO

doi:10.1587/transfun.E98.A.2060

NHPP-Based Software Reliability Model with Marshall-Olkin Failure Time Distribution

Xiao XIAO

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A new modeling approach for the non-homogeneous Poisson processes (NHPPs) based software reliability modeling is proposed to describe the stochastic behavior of software fault-detection processes, of which the failure rate is not monotonic. The fundamental idea is to apply the Marshall-Olkin distribution to the software fault-detection time distribution. The applicability of Marshall-Olkin distribution in software reliability modeling is studied. The data fitting abilities of the proposed NHPP-based software reliability model is compared with the existing typical ones through real software project data analysis.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E98-A No.10 pp.2060-2068

Publication Date: 2015/10/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E98.A.2060

Type of Manuscript: Special Section PAPER (Special Section on Recent Developments on Reliability, Maintainability and Dependability)

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Xiao XIAO
Tokyo Metropolitan University

Keyword

failure rate, NHPP, Marshall-Olkin distribution, software fault count data, real data analysis

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Xiao XIAO, "NHPP-Based Software Reliability Model with Marshall-Olkin Failure Time Distribution" in IEICE TRANSACTIONS on Fundamentals, vol. E98-A, no. 10, pp. 2060-2068, October 2015, doi: 10.1587/transfun.E98.A.2060.
Abstract: A new modeling approach for the non-homogeneous Poisson processes (NHPPs) based software reliability modeling is proposed to describe the stochastic behavior of software fault-detection processes, of which the failure rate is not monotonic. The fundamental idea is to apply the Marshall-Olkin distribution to the software fault-detection time distribution. The applicability of Marshall-Olkin distribution in software reliability modeling is studied. The data fitting abilities of the proposed NHPP-based software reliability model is compared with the existing typical ones through real software project data analysis.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/transfun.E98.A.2060/_p

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@ARTICLE{e98-a_10_2060,
author={Xiao XIAO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={NHPP-Based Software Reliability Model with Marshall-Olkin Failure Time Distribution},
year={2015},
volume={E98-A},
number={10},
pages={2060-2068},
abstract={A new modeling approach for the non-homogeneous Poisson processes (NHPPs) based software reliability modeling is proposed to describe the stochastic behavior of software fault-detection processes, of which the failure rate is not monotonic. The fundamental idea is to apply the Marshall-Olkin distribution to the software fault-detection time distribution. The applicability of Marshall-Olkin distribution in software reliability modeling is studied. The data fitting abilities of the proposed NHPP-based software reliability model is compared with the existing typical ones through real software project data analysis.},
keywords={},
doi={10.1587/transfun.E98.A.2060},
ISSN={1745-1337},
month={October},}

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TY - JOUR
TI - NHPP-Based Software Reliability Model with Marshall-Olkin Failure Time Distribution
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2060
EP - 2068
AU - Xiao XIAO
PY - 2015
DO - 10.1587/transfun.E98.A.2060
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E98-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2015
AB - A new modeling approach for the non-homogeneous Poisson processes (NHPPs) based software reliability modeling is proposed to describe the stochastic behavior of software fault-detection processes, of which the failure rate is not monotonic. The fundamental idea is to apply the Marshall-Olkin distribution to the software fault-detection time distribution. The applicability of Marshall-Olkin distribution in software reliability modeling is studied. The data fitting abilities of the proposed NHPP-based software reliability model is compared with the existing typical ones through real software project data analysis.
ER -