基于早期度量的概念数据模型质量保证

M. Genero, M. Piattini, C. Calero
{"title":"基于早期度量的概念数据模型质量保证","authors":"M. Genero, M. Piattini, C. Calero","doi":"10.1109/APAQS.2001.990007","DOIUrl":null,"url":null,"abstract":"The increasing demand for quality information systems (IS), has become quality the most pressing challenge facing IS development organisations. In the IS development field it is generally accepted that the quality of an IS is highly dependent on decisions made early in its development. Given the relevant role that data itself plays in an IS, conceptual data models are a key artifact of the IS design: Therefore, in order to build \"better quality \" IS it is necessary to assess and to improve the quality of conceptual data models based on quantitative criteria. It is in this context where software measurement can help IS designers to make better decision during design activities. We focus this work on the empirical validation of the metrics proposed by Genero et al. for measuring the structural complexity of entity relationship diagrams (ERDs). Through a controlled experiment we will demonstrate that these metrics seem to be heavily correlated with three of the sub-factors that characterise the maintainability of an ERD, such as understandability, analysability and modifiability.","PeriodicalId":145151,"journal":{"name":"Proceedings Second Asia-Pacific Conference on Quality Software","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Assurance of conceptual data model quality based on early measures\",\"authors\":\"M. Genero, M. Piattini, C. Calero\",\"doi\":\"10.1109/APAQS.2001.990007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increasing demand for quality information systems (IS), has become quality the most pressing challenge facing IS development organisations. In the IS development field it is generally accepted that the quality of an IS is highly dependent on decisions made early in its development. Given the relevant role that data itself plays in an IS, conceptual data models are a key artifact of the IS design: Therefore, in order to build \\\"better quality \\\" IS it is necessary to assess and to improve the quality of conceptual data models based on quantitative criteria. It is in this context where software measurement can help IS designers to make better decision during design activities. We focus this work on the empirical validation of the metrics proposed by Genero et al. for measuring the structural complexity of entity relationship diagrams (ERDs). Through a controlled experiment we will demonstrate that these metrics seem to be heavily correlated with three of the sub-factors that characterise the maintainability of an ERD, such as understandability, analysability and modifiability.\",\"PeriodicalId\":145151,\"journal\":{\"name\":\"Proceedings Second Asia-Pacific Conference on Quality Software\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Second Asia-Pacific Conference on Quality Software\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APAQS.2001.990007\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Second Asia-Pacific Conference on Quality Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APAQS.2001.990007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

摘要

对高质量信息系统(IS)的需求日益增长,质量已成为IS开发组织面临的最紧迫的挑战。在信息系统开发领域,人们普遍认为信息系统的质量高度依赖于其开发早期所做的决策。考虑到数据本身在信息系统中扮演的相关角色,概念数据模型是信息系统设计的关键工件:因此,为了构建“更好质量”的信息系统,有必要根据定量标准评估和改进概念数据模型的质量。正是在这种情况下,软件测量可以帮助信息系统设计师在设计活动中做出更好的决策。我们将这项工作的重点放在Genero等人提出的度量实体关系图(erd)结构复杂性的度量的实证验证上。通过一个受控实验,我们将证明这些度量似乎与表征ERD可维护性的三个子因素密切相关,例如可理解性、可分析性和可修改性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assurance of conceptual data model quality based on early measures
The increasing demand for quality information systems (IS), has become quality the most pressing challenge facing IS development organisations. In the IS development field it is generally accepted that the quality of an IS is highly dependent on decisions made early in its development. Given the relevant role that data itself plays in an IS, conceptual data models are a key artifact of the IS design: Therefore, in order to build "better quality " IS it is necessary to assess and to improve the quality of conceptual data models based on quantitative criteria. It is in this context where software measurement can help IS designers to make better decision during design activities. We focus this work on the empirical validation of the metrics proposed by Genero et al. for measuring the structural complexity of entity relationship diagrams (ERDs). Through a controlled experiment we will demonstrate that these metrics seem to be heavily correlated with three of the sub-factors that characterise the maintainability of an ERD, such as understandability, analysability and modifiability.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信