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

页码：23 / 24

页数：2

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