A statistical model for estimating size and productivity ratio in SDLC

{"title":"A statistical model for estimating size and productivity ratio in SDLC","authors":"","doi":"10.46860/cgcijctr.2024.04.10.370","DOIUrl":null,"url":null,"abstract":"During a software development life cycle, one has to estimate the effort and schedule required to produce a software unit. Estimates for The effort and schedule are derived from other measurements such as size and productivity Ratio. Size may be estimated using methods such as Function Point, WBS, LOC, etc., and the Productivity Ratio is expressed as Size / Time to complete the Unit of Software. Such estimates are static and do not consider real-time Parameters which cause variations from the estimate. In this paper, a statistical model for Size and Productivity Ratios is derived using Historical values after considering several factors influencing the size and the productivity ratio of produced software. Typically, an estimate of the effort and schedule is required to complete. A software work product an enhancement request or a software fix. We use Function Points or WBS to estimate the size of the software in consideration. We use baseline values for estimating productivity Ratios. Real-time values however differ from Baseline values as they are influenced by several factors. Here are some factors which would influence the Actual Size of the software Later on we will use Statistical techniques of Multivariable Parameter estimation and logistic Regression to derive run time equations of Size and Productivity Ratio.","PeriodicalId":373538,"journal":{"name":"CGC International Journal of Contemporary Technology and Research","volume":"2007 7","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CGC International Journal of Contemporary Technology and Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46860/cgcijctr.2024.04.10.370","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

During a software development life cycle, one has to estimate the effort and schedule required to produce a software unit. Estimates for The effort and schedule are derived from other measurements such as size and productivity Ratio. Size may be estimated using methods such as Function Point, WBS, LOC, etc., and the Productivity Ratio is expressed as Size / Time to complete the Unit of Software. Such estimates are static and do not consider real-time Parameters which cause variations from the estimate. In this paper, a statistical model for Size and Productivity Ratios is derived using Historical values after considering several factors influencing the size and the productivity ratio of produced software. Typically, an estimate of the effort and schedule is required to complete. A software work product an enhancement request or a software fix. We use Function Points or WBS to estimate the size of the software in consideration. We use baseline values for estimating productivity Ratios. Real-time values however differ from Baseline values as they are influenced by several factors. Here are some factors which would influence the Actual Size of the software Later on we will use Statistical techniques of Multivariable Parameter estimation and logistic Regression to derive run time equations of Size and Productivity Ratio.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用于估算 SDLC 中规模与生产率比率的统计模型
在软件开发生命周期中,我们必须估算制作一个软件单元所需的工作量和进度。对工作量和进度的估算来自于其他测量指标,如规模和生产率。规模可以用功能点、WBS、LOC 等方法估算,生产率则用规模/完成软件单元所需的时间来表示。这种估算是静态的,没有考虑导致估算值变化的实时参数。本文在考虑了影响软件规模和生产率的几个因素后,利用历史值推导出了规模和生产率的统计模型。通常情况下,需要对完成工作的工作量和进度进行估算。软件工作产品是一种增强请求或软件修复。我们使用功能点或 WBS 来估算软件的大小。我们使用基准值来估算生产率。然而,实时值与基准值不同,因为它们受到多种因素的影响。以下是影响软件实际大小的一些因素。稍后,我们将使用多变量参数估计和逻辑回归的统计技术,得出大小和生产率比率的运行时间方程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A statistical model for estimating size and productivity ratio in SDLC Recent Advancement in Blockchain: A study Smart Antennas for Various Applications The Role of Excipients in Liquisolid Technology Comparative Research on the Techniques of Electricity Fraud Detection Using Different Machine Learning Techniques
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1