Parametric Based Clustering of Reusable Components

M. H. Zafar, Muhammad Ilyas, Saad Razzaq, F. Maqbool, W. Ahmad, W. Ahmad, S. M. Adnan
{"title":"Parametric Based Clustering of Reusable Components","authors":"M. H. Zafar, Muhammad Ilyas, Saad Razzaq, F. Maqbool, W. Ahmad, W. Ahmad, S. M. Adnan","doi":"10.26692/SURJ/2019.09.67","DOIUrl":null,"url":null,"abstract":"Building new software by using existing software that has been developed by using reusability principles is known as software reuse. It results in reduction of effort and time to develop software. It also increases reliability, portability, maintainability and productivity of software product. But the problem is a lack to symmetric way to store reusable components so that retrieval of component done with less time. One of the solutions is to classify reusable components. We use clustering technique to classify reusable components because clustering results in reduction of search space by cataloguing similar objects together. In this research we propose a framework that is used to understand the process of clustering and to give a practical shape to this framework. In this framework software reusable components are provide with their associated parameters. On the basis of these parameters, software reusable components are clustered. Finally proposed clustering algorithm is evaluated by applying this algorithm on different software reusable components. Presentation of results is in the form of table and graph which shows the successful clustering of reusable components.","PeriodicalId":21635,"journal":{"name":"SINDH UNIVERSITY RESEARCH JOURNAL -SCIENCE SERIES","volume":"82 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SINDH UNIVERSITY RESEARCH JOURNAL -SCIENCE SERIES","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26692/SURJ/2019.09.67","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

Building new software by using existing software that has been developed by using reusability principles is known as software reuse. It results in reduction of effort and time to develop software. It also increases reliability, portability, maintainability and productivity of software product. But the problem is a lack to symmetric way to store reusable components so that retrieval of component done with less time. One of the solutions is to classify reusable components. We use clustering technique to classify reusable components because clustering results in reduction of search space by cataloguing similar objects together. In this research we propose a framework that is used to understand the process of clustering and to give a practical shape to this framework. In this framework software reusable components are provide with their associated parameters. On the basis of these parameters, software reusable components are clustered. Finally proposed clustering algorithm is evaluated by applying this algorithm on different software reusable components. Presentation of results is in the form of table and graph which shows the successful clustering of reusable components.
基于参数的可重用组件聚类
通过使用根据可重用性原则开发的现有软件来构建新软件被称为软件重用。它减少了开发软件的工作量和时间。它还提高了软件产品的可靠性、可移植性、可维护性和生产力。但问题是缺乏一种对称的方式来存储可重用的组件,使得组件的检索用更少的时间完成。解决方案之一是对可重用组件进行分类。我们使用聚类技术对可重用组件进行分类,因为聚类通过将相似的对象编目在一起来减少搜索空间。在本研究中,我们提出了一个用于理解聚类过程的框架,并给出了该框架的实际形状。在这个框架中,为软件可重用组件提供了相关的参数。在这些参数的基础上,对软件可重用组件进行聚类。最后,将该算法应用于不同的软件可重用组件,对该算法进行了评价。结果以表格和图表的形式显示了可重用组件的成功聚类。
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 求助全文
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:481959085
Book学术官方微信