OSS Effort Expense Optimization Based on Wiener Process Model and GA  

作　　者：Kodai Sugisaki Yoshinobu Tamura Shigeru Yamada Kodai Sugisaki;Yoshinobu Tamura;Shigeru Yamada(Tokyo City University, Tokyo, Japan;Tottori University, Tottori, Japan)

机构地区：[1]Tokyo City University, Tokyo, Japan [2]Tottori University, Tottori, Japan

出　　处：《Journal of Software Engineering and Applications》2021年第1期11-25,共15页软件工程与应用（英文）

摘　　要：<div style="text-align:justify;"> <span style="font-family:Verdana;">Various open source software are managed by using several bug tracking systems. In particular, the open source software extends to the cloud service and edge computing. Recently, OSF Edge Computing Group is launched by OpenStack. There are big data behind the internet services such as cloud and edge computing. Then, it is important to consider the impact of big data in order to assess the reliability of open source software. Various optimal software release problems have been proposed by specific researchers. In the typical optimal software release problems, the cost parameters are defined as the known parameter. However, it is difficult to decide the cost parameter because of the uncertainty. The purpose of our research is to estimate the effort parameters included in our models. In this paper, we propose an estimation method of effort parameter by using the genetic algorithm. Then, we show the estimation method in section 3. Moreover, we analyze actual data to show numerical examples for the estimation method of effort parameter. As the research results, we found that the OSS managers would be able to comprehend the human resources required before the OSS project in advance by using our method.</span> </div><div style="text-align:justify;"> <span style="font-family:Verdana;">Various open source software are managed by using several bug tracking systems. In particular, the open source software extends to the cloud service and edge computing. Recently, OSF Edge Computing Group is launched by OpenStack. There are big data behind the internet services such as cloud and edge computing. Then, it is important to consider the impact of big data in order to assess the reliability of open source software. Various optimal software release problems have been proposed by specific researchers. In the typical optimal software release problems, the cost parameters are defined as the known parameter. However, it is difficult to decide the cost parameter because of the uncertainty. The purpose of our research is to estimate the effort parameters included in our models. In this paper, we propose an estimation method of effort parameter by using the genetic algorithm. Then, we show the estimation method in section 3. Moreover, we analyze actual data to show numerical examples for the estimation method of effort parameter. As the research results, we found that the OSS managers would be able to comprehend the human resources required before the OSS project in advance by using our method.</span> </div>

关 键 词：Fault Big Data Cost Optimization Reliability Analysis Wiener Process Model Open Source Project 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]