Prototype of 3D Reliability Assessment Tool Based on the Deep Learning Considering OSS Effort Wiener Process Data

At present, the fault big data of open source software are opened as the open data set. In particular, the fault detection phenomenon depends on various situation of operation in OSS. Actually, various software reliability growth models have been actively proposed by several researchers in the past. This paper applies the deep learning approach to the OSS fault big data. Then, we propose several reliability assessment measures based on the deep learning. As an approach, the range of estimate expands by the Wiener process embedded for the data preprocessing. Furthermore, this paper proposes the performability as novel reliability assessment measure from the proposed deep learning model. In particular, we develop the prototype of 3D reliability assessment tool. Several illustration examples based on the developed prototype of 3D reliability assessment tool by using the actual fault big data sets are shown in this paper.