TITLE:
OSS Project Assessment Based on Discriminant Analysis and Jump Diffusion Process Model for Fault Big Data
AUTHORS:
Yoshinobu Tamura, Hayato Watanabe, Shigeru Yamada
KEYWORDS:
Open Source Software, Big Fault Data, Discriminant Analysis, Open Source Project
JOURNAL NAME:
American Journal of Operations Research,
Vol.10 No.6,
November
9,
2020
ABSTRACT: The bug
tracking system is well known as the project support tool of open source
software. There are many categorical data sets recorded on the bug tracking
system. In the past, many reliability assessment methods have been proposed in
the research area of software reliability. Also, there are several software
project analyses based on the software effort data such as the earned value
management. In particular, the software reliability growth models can apply to the system testing phase of software
development. On the other hand, the software effort analysis can apply
to all development phase, because the fault data is only recorded on the
testing phase. We focus on the big fault data and effort data of open source
software. Then, it is difficult to assess by using the typical statistical
assessment method, because the data recorded on the bug tracking system is
large scale. Also, we discuss the jump diffusion process model based on the
estimation method of jump parameters by using the discriminant analysis. Moreover,
we analyze actual big fault data to show numerical examples of software effort
assessment considering many categorical data set.