Anemic Domain Model vs Rich Domain Model to Improve the Two-Hemisphere Model-Driven Approach

IF 0.5 Q4 COMPUTER SCIENCE, THEORY & METHODS Applied Computer Systems Pub Date : 2020-05-01 DOI:10.2478/acss-2020-0006
O. Ņikiforova, Konstantins Gusarovs
{"title":"Anemic Domain Model vs Rich Domain Model to Improve the Two-Hemisphere Model-Driven Approach","authors":"O. Ņikiforova, Konstantins Gusarovs","doi":"10.2478/acss-2020-0006","DOIUrl":null,"url":null,"abstract":"Abstract Evolution of software development process and increasing complexity of software systems calls for developers to pay great attention to the evolution of CASE tools for software development. This, in turn, causes explosion for appearance of a new wave (or new generation) of such CASE tools. The authors of the paper have been working on the development of the so-called two-hemisphere model-driven approach and its supporting BrainTool for the past 10 years. This paper is a step forward in the research on the ability to use the two-hemisphere model driven approach for system modelling at the problem domain level and to generate UML diagrams and software code from the two-hemisphere model. The paper discusses the usage of anemic domain model instead of rich domain model and offers the main principle of transformation of the two-hemisphere model into the first one.","PeriodicalId":41960,"journal":{"name":"Applied Computer Systems","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Computer Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/acss-2020-0006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 2

Abstract

Abstract Evolution of software development process and increasing complexity of software systems calls for developers to pay great attention to the evolution of CASE tools for software development. This, in turn, causes explosion for appearance of a new wave (or new generation) of such CASE tools. The authors of the paper have been working on the development of the so-called two-hemisphere model-driven approach and its supporting BrainTool for the past 10 years. This paper is a step forward in the research on the ability to use the two-hemisphere model driven approach for system modelling at the problem domain level and to generate UML diagrams and software code from the two-hemisphere model. The paper discusses the usage of anemic domain model instead of rich domain model and offers the main principle of transformation of the two-hemisphere model into the first one.
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
贫域模型与富域模型改进双半球模型驱动方法
软件开发过程的演变和软件系统复杂性的增加要求开发人员高度关注软件开发用例工具的演变。这反过来又导致了这种CASE工具的新浪潮(或新一代)的出现。这篇论文的作者在过去的10年里一直致力于所谓的双半球模型驱动方法及其支持的BrainTool的发展。本文研究了在问题域级别使用双半球模型驱动方法进行系统建模,并从双半球模型生成UML图和软件代码的能力。本文讨论了贫域模型代替富域模型的用法,并提出了由双半球模型转换为第一半球模型的主要原理。
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
Applied Computer Systems
Applied Computer Systems COMPUTER SCIENCE, THEORY & METHODS-
自引率
10.00%
发文量
9
审稿时长
30 weeks
期刊最新文献
Multimodal Biometric System Based on the Fusion in Score of Fingerprint and Online Handwritten Signature Multichannel Approach for Sentiment Analysis Using Stack of Neural Network with Lexicon Based Padding and Attention Mechanism BRS-based Model for the Specification of Multi-view Point Ontology Empirical Analysis of Supervised and Unsupervised Machine Learning Algorithms with Aspect-Based Sentiment Analysis Approximate Nearest Neighbour-based Index Tree: A Case Study for Instrumental Music Search
×
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