文献类型：期刊文献

英文题名：Open-source Software Reliability Modeling with Stochastic Impulsive Differential Equations

作者：Zheng, Zhoutao Yang, Jianfeng Hu, Yao Wang, Xibing

第一作者：Zheng, Zhoutao

通信作者：Yang, JF[1];Yang, JF[2]

机构：[1]Guizhou Univ, Sch Math & Stat, Guizhou, Peoples R China;[2]Guizhou Inst Technol, Sch Data Sci, Guizhou, Peoples R China

第一机构：Guizhou Univ, Sch Math & Stat, Guizhou, Peoples R China

通信机构：corresponding author), Guizhou Univ, Sch Math & Stat, Guizhou, Peoples R China;corresponding author), Guizhou Inst Technol, Sch Data Sci, Guizhou, Peoples R China.|贵州理工学院;

年份：2023

卷号：25

期号：2

外文期刊名：EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY

收录：;EI(收录号：20232514258024);Scopus(收录号：2-s2.0-85161853951);WOS:【SCI-EXPANDED(收录号:WOS:001001106500003)】；

基金：This work was supported by National Natural Science Foundation of China (No.71901078, 72161005) , Science and Technology Foundation of Guizhou (No. QianKeHeJiChu-ZK [2022] -General184) , Guizhou Internet + Industrial Technology Research Institute and Key Laboratory of Electric Power Big Data of Guizhou Province.

语种：英文

外文关键词：open-source software; reliability modeling; random impulse; stochastic impulsive differential equations

摘要：In reality, sudden updates of software, attacks of hackers, influence of the Internet market, etc. can cause a surge in the number of open-source software (OSS) faults (this moment is the time when impulse occurs), which results in impulsive phenomenon. For the existing software reliability models, dynamic process of software fault is considered to be continuous when assessing reliability, but continuity of the process can be disrupted with appearance of random impulses. Thus, to more accurately assess software reliability, we proposed an OSS reliability model with SIDE. In the model, dynamic process of software fault is divided into a continuous and a skipped part, described the continuous part of the process with SDE, and described destruction of the continuity caused by unpredictable random events with random impulses. Finally, the proposed model is verified with two datasets from real OSS project, and the results show that the proposed model is more in line with reality and has better fitting effect than the existing models.