Open-source Software Reliability Modeling with Stochastic Impulsive Differential Equations

• Autorzy: Zheng Zhoutao , Yang Jianfeng , Hu Yao , Wang Xibing

Identyfikatory

DOI

10.17531/ein/166342

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

open-source software; reliability modeling; random impulse; stochastic impulsive differential equations

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2023
• Tom: Vol. 25, no. 2
• Strony: art. no. 166342
• Opis fizyczny: Bibliogr. 30 poz., tab., wykr.

Twórcy

autor

Zheng Zhoutao

• School of Mathematics and Statistics, Guizhou University, China

• https://orcid.org/0000-0002-9211-3621

autor

Yang Jianfeng

• School of Mathematics and Statistics, Guizhou University, China
• School of Data Science, Guizhou Institute of Technology, China

• https://orcid.org/0000-0003-3486-9604

autor

Hu Yao

• School of Mathematics and Statistics, Guizhou University, China

autor

Wang Xibing

• School of Data Science, Guizhou Institute of Technology, China

• https://orcid.org/0000-0003-1831-9872

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