OSS Sustainability Assessment Based on the Deep Learning Considering Effort Wiener Process Data
Yoshinobu Tamura, Shoichiro Miyamoto, Lei Zhou, Shigeru Yamada · International Journal of Reliability Quality and Safety Engineering · 2023
This paper focuses on the sustainability based on the effort by using the fault big data of open source software (OSS). The fault detection phenomenon depends on the maintenance effort, because the number of software fault is influenced by the effort expenditure. Actually, the software reliability growth models with testing-effort have been proposed in the past. In this paper, we apply the deep learning approach to the OSS fault big data. Also, we propose the reliability assessment measure of sustainability. Then, we show several sustainability assessment measure based on the deep learning. Moreover, several numerical illustrations based on the proposed deep learning model are shown in this paper.