文献类型：会议论文

英文题名：A New Framework and Application of Software Reliability Estimation based on Fault Detection and Correction Processes

作者：Liu, Yu Xie, Min Yang, Jianfeng Zhao, Ming

第一作者：Liu, Yu

通信作者：Liu, Y[1]

机构：[1]City Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Hong Kong, Peoples R China;[2]Guizhou Inst Technol, Fac Informat Engn, Guiyang, Peoples R China;[3]Univ Gavle, Fac Engn & Sustaible Dev, Gavle, Sweden

第一机构：City Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Hong Kong, Peoples R China

通信机构：corresponding author), City Univ Hong Kong, Dept Syst Engn & Engn Management, Hong Kong, Hong Kong, Peoples R China.

会议论文集：IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)

会议日期：AUG 03-05, 2015

会议地点：Vancouver, CANADA

语种：英文

外文关键词：Software reliability; queuing model; fault correction process; Non-Homogenous Poisson Process; maximum likelihood estimation

年份：2015

摘要：Software reliability growth modeling plays an important role in software reliability evaluation. To incorporate more information and provide more accurate analysis, modeling software fault detection and correction processes has attracted widespread research attention recently. However, the assumption of the stochastic fault correction time delay brings more difficulties in modeling and estimating the parameters. In practice, other than the grouped fault data, software test records often include some more detailed information, such as the rough time when one fault is detected or corrected. Such semi-grouped dataset contains more information about fault removal processes than commonly used grouped dataset. Using the semi-grouped datasets can improve the accuracy of time delayed models. In this paper, a fault removal modelling framework for software reliability with semi-grouped data is studied and extended into multi-released software. Also, the corresponding parameter estimation is carried out with Maximum Likelihood estimation method. One test dataset with three releases from a practical software project is applied with the proposed framework, which shows satisfactory performance with the results.