Tamura, Y. and Yamada, S. (2020) Large Scale Fault Data Analysis and OSS Reliability Assessment Based on Quantification Method of the First Type, Machine Learning and Knowledge Extraction, 2, 436-452.
https://doi.org/10.3390/make2040024

has been cited by the following article:

• TITLE: A Software Reliability Model for OSS Including Various Fault Data Based on Proportional Hazard-Rate Model

  AUTHORS: Taku Yanagisawa, Yoshinobu Tamura, Adarsh Anand, Shigeru Yamada

  KEYWORDS: Open Source Software, Fault Data, Software Reliability, Cox Proportional Hazard-Rate Model

  JOURNAL NAME: American Journal of Operations Research, Vol.12 No.1, January 5, 2022

  ABSTRACT: The software reliability model is the stochastic model to measure the software reliability quantitatively. A Hazard-Rate Model is the well-known one as the typical software reliability model. We propose Hazard-Rate Models Considering Fault Severity Levels (CFSL) for Open Source Software (OSS). The purpose of this research is to make the Hazard-Rate Model considering CFSL adapt to baseline hazard function and 2 kinds of faults data in Bug Tracking System (BTS), i.e., we use the covariate vectors in Cox proportional Hazard-Rate Model. Also, we show the numerical examples by evaluating the performance of our proposed model. As the result, we compare the performance of our model with the Hazard-Rate Model CFSL.