使用硬限制技术的软件工作量估算,特别适用于小型技术和分析项目

T. Kumar, M. Jayaram
{"title":"使用硬限制技术的软件工作量估算,特别适用于小型技术和分析项目","authors":"T. Kumar, M. Jayaram","doi":"10.1109/ICERECT56837.2022.10060696","DOIUrl":null,"url":null,"abstract":"Effort estimation is the process of predicting a software's likely cost and development time. Estimating software development effort is still a complex problem that receives a lot of research attention. The accuracy with which the effort necessary for software development is estimated, and it is a significant success element in software project management. The estimated effort should be roughly equal to the actual effort in a good software estimation model. Accurate estimation enables managers to allocate resources for the planning and coordination of all activities. In this paper the effort estimation for small size projects involving technical and analytical aspects of engineering intent. The estimation of time resources is done in three steps firstly Identification of seven novel traits of software (LOC, N&C, CGPA, R, CC, AC, FP). Secondly PCA was implemented to decide the significant parameters among the software features. Lastly linear regression and polynomial regression models were developed using the significant features predicted by the PCA. The result of evaluation of the two models are encouraging with the minimum RMSE of 32-204 minutes and maximum regression coefficients(r2) of 0.95-0.98","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"187 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Software Effort Estimation Using Hard Limiting Techniques with Special Reference to Small Size Technical &Analytical Projects\",\"authors\":\"T. Kumar, M. Jayaram\",\"doi\":\"10.1109/ICERECT56837.2022.10060696\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Effort estimation is the process of predicting a software's likely cost and development time. Estimating software development effort is still a complex problem that receives a lot of research attention. The accuracy with which the effort necessary for software development is estimated, and it is a significant success element in software project management. The estimated effort should be roughly equal to the actual effort in a good software estimation model. Accurate estimation enables managers to allocate resources for the planning and coordination of all activities. In this paper the effort estimation for small size projects involving technical and analytical aspects of engineering intent. The estimation of time resources is done in three steps firstly Identification of seven novel traits of software (LOC, N&C, CGPA, R, CC, AC, FP). Secondly PCA was implemented to decide the significant parameters among the software features. Lastly linear regression and polynomial regression models were developed using the significant features predicted by the PCA. The result of evaluation of the two models are encouraging with the minimum RMSE of 32-204 minutes and maximum regression coefficients(r2) of 0.95-0.98\",\"PeriodicalId\":205485,\"journal\":{\"name\":\"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)\",\"volume\":\"187 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICERECT56837.2022.10060696\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICERECT56837.2022.10060696","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

工作量估算是预测软件可能的成本和开发时间的过程。评估软件开发工作量仍然是一个复杂的问题,受到了许多研究的关注。评估软件开发所需工作的准确性,它是软件项目管理中重要的成功因素。在一个好的软件评估模型中,估计的工作量应该大致等于实际的工作量。准确的评估使管理人员能够为所有活动的计划和协调分配资源。本文从工程意图的技术和分析两个方面对小型项目进行了工作量估算。时间资源估计分三步进行:首先,识别软件的7个新特征(LOC、N&C、CGPA、R、CC、AC、FP);其次,采用主成分分析法确定软件特征之间的重要参数;最后利用主成分分析预测的显著性特征建立了线性回归模型和多项式回归模型。两种模型的评价结果令人鼓舞,最小RMSE为32 ~ 204 min,最大回归系数(r2)为0.95 ~ 0.98
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Software Effort Estimation Using Hard Limiting Techniques with Special Reference to Small Size Technical &Analytical Projects
Effort estimation is the process of predicting a software's likely cost and development time. Estimating software development effort is still a complex problem that receives a lot of research attention. The accuracy with which the effort necessary for software development is estimated, and it is a significant success element in software project management. The estimated effort should be roughly equal to the actual effort in a good software estimation model. Accurate estimation enables managers to allocate resources for the planning and coordination of all activities. In this paper the effort estimation for small size projects involving technical and analytical aspects of engineering intent. The estimation of time resources is done in three steps firstly Identification of seven novel traits of software (LOC, N&C, CGPA, R, CC, AC, FP). Secondly PCA was implemented to decide the significant parameters among the software features. Lastly linear regression and polynomial regression models were developed using the significant features predicted by the PCA. The result of evaluation of the two models are encouraging with the minimum RMSE of 32-204 minutes and maximum regression coefficients(r2) of 0.95-0.98
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Research of Computer Simulation based on Digital Design in the Design Application A Novel Study on EVs Smart Charging Optimization Modelling of Eye Blink Monitoring Mechanism utilizing ML Techniques Performance Evaluation of a Network on Chip Based on Ghz Throughput and Low Power for Streaming Data Transmission on FPGA Way Forward to Digital Society – Digital Transformation of Msmes from Industry 4.0 to Industry 5.0
×
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