Building a banking system specification using machine learning

J. Genest
{"title":"Building a banking system specification using machine learning","authors":"J. Genest","doi":"10.1109/AIAWS.1991.236591","DOIUrl":null,"url":null,"abstract":"Transforming user requirements into software specification is a complex and demanding task. Artificial intelligence methods such as machine learning (ML) can assist in the software specification process by providing support to system designers. This paper presents an approach based on explanation-based learning (EBL), a ML technique in which a concept is learned by building an explanation. The approach is presented in the context of the system LISE (Learning in Software Engineering). LISE converts a user requirement for a software module into an operational module definition using EBL with an incomplete theory. An example where LISE is used to build the specification of a banking system is illustrated.<<ETX>>","PeriodicalId":171318,"journal":{"name":"Proceedings First International Conference on Artificial Intelligence Applications on Wall Street","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings First International Conference on Artificial Intelligence Applications on Wall Street","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIAWS.1991.236591","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Transforming user requirements into software specification is a complex and demanding task. Artificial intelligence methods such as machine learning (ML) can assist in the software specification process by providing support to system designers. This paper presents an approach based on explanation-based learning (EBL), a ML technique in which a concept is learned by building an explanation. The approach is presented in the context of the system LISE (Learning in Software Engineering). LISE converts a user requirement for a software module into an operational module definition using EBL with an incomplete theory. An example where LISE is used to build the specification of a banking system is illustrated.<>
使用机器学习构建银行系统规范
将用户需求转换为软件规范是一项复杂而苛刻的任务。机器学习(ML)等人工智能方法可以通过向系统设计人员提供支持来协助软件规范过程。本文提出了一种基于解释学习(EBL)的方法,这是一种通过构建解释来学习概念的机器学习技术。该方法是在LISE(软件工程学习)系统的背景下提出的。LISE使用EBL将用户对软件模块的需求转换为具有不完整理论的可操作模块定义。下面给出了使用LISE构建银行系统规范的示例。
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:604180095
Book学术官方微信
小红书