A Useful Parametric Family to Characterize NHPP-based Software Reliability Models

被引：1
|
作者：
Li, Siqiao [1 ]
机构：
[1] Hiroshima Univ, Grad Sch Adv Sci & Engn, Higashihiroshima, Japan
来源：
51ST ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS - SUPPLEMENTAL VOL (DSN 2021) | 2021年
关键词：
software reliability models; non-homogeneous Poisson processes; Burr-type distributions; goodness-of-fit performance; BURR;
D O I：
10.1109/DSN-S52858.2021.00022
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this note, we attempt to use the Burr-type distributions to describe the software fault-detection time distribution, and develop somewhat different non-homogeneous Poisson process (NHPP)-based software reliability models (SRMs). From the viewpoints of the goodness-of-fit and predictive performances, we compare Burr-type NHPP-based SRMs with the existing ones having the well-known fault-detection time distributions. Throughout numerical examples with 16 software fault count data (8 time data and 8 group data) observed in actual software development projects, we show the usefulness of the Burr-type NHPP-based SRMs.
引用
收藏
页码：23 / 24
页数：2
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