In this paper we extend non-homogeneous gamma process (NHGP)-based software reliability models (SRMs) by Ishii and Dohi (2008) from both view points of modeling and parameter estimation. In modeling, we generalize the underlying NHGP-based SRMs to those for eleven kinds of trend function, which can characterize a variety of software fault-detection patterns. In parameter estimation, we develop a non-parametric maximum likelihood estimation method without the complete knowledge on trend functions, and compare it with the parametric maximum likelihood estimation method. Since an NHGP involves a non-homogeneous Poisson processes (NHPPs) as the simplest case, it is shown that NHGP-based SRMs are much more robust than the common NHPP-based SRMs and that our non-parametric method can improve the goodness-of-fit performance of the conventional parametric one.
机构:
Hung Vuong Univ, Fac Engn Technol, Viet Tri City, Phu Tho Provinc, VietnamHung Vuong Univ, Fac Engn Technol, Viet Tri City, Phu Tho Provinc, Vietnam
机构:
Columbia Univ, Int Res Inst Climate & Soc Earth & Environm Engn, New York, NY 10027 USAColumbia Univ, Int Res Inst Climate & Soc Earth & Environm Engn, New York, NY 10027 USA
Khalil, Abedalrazq F.
Kwon, Hyun-Han
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Chonbuk Natl Univ, Dept Civil Engn, Jeonju 561756, Jeonbuk, South KoreaColumbia Univ, Int Res Inst Climate & Soc Earth & Environm Engn, New York, NY 10027 USA
Kwon, Hyun-Han
Lall, Upmanu
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Columbia Univ, Int Res Inst Climate & Soc Earth & Environm Engn, New York, NY 10027 USAColumbia Univ, Int Res Inst Climate & Soc Earth & Environm Engn, New York, NY 10027 USA
Lall, Upmanu
Kaheil, Yasir H.
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Columbia Univ, Int Res Inst Climate & Soc Earth & Environm Engn, New York, NY 10027 USAColumbia Univ, Int Res Inst Climate & Soc Earth & Environm Engn, New York, NY 10027 USA