Towards a Semiautomatic Tool to Support the Integration of Feature Models

Vinícius Bischoff, Kleinner Farias, L. Gonçales, J. Barbosa
{"title":"Towards a Semiautomatic Tool to Support the Integration of Feature Models","authors":"Vinícius Bischoff, Kleinner Farias, L. Gonçales, J. Barbosa","doi":"10.1145/3330204.3330249","DOIUrl":null,"url":null,"abstract":"The integration of feature models plays a key role in many software engineering tasks, e.g., adding new features to software product lines (SPL) of information systems. Previous empirical studies have revealed that integrating design models is still considered a time-consuming and error-prone task. Unfortunately, integration approaches with tool support are still severely lacking. Even worse, little is known about the effort invested by developers to integrate models manually, and how correct the integrated models are. This paper proposes FMIT, which is a semiautomatic tool to support the integration of feature models. It comes up with a strategy-based approach to reduce the effort that developers invest to combine feature models and increase the amount of correctly integrated models. A controlled experiment was run with 10 volunteers through six realistic integration scenarios. Our results, supported by statistical tests, show that our semiautomatic approach not only reduced the integration effort by 73.01%, but also increased the number of correctly integrated feature models by 43.01%, compared with the manual approach. Our main contributions are a semiautomatic, strategy-based approach with tool support, and empirical evidence on its benefits. Our encouraging results open the way for the development of new heuristics and tools to support developers during the evolution of feature models.","PeriodicalId":348938,"journal":{"name":"Proceedings of the XV Brazilian Symposium on Information Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the XV Brazilian Symposium on Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3330204.3330249","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

The integration of feature models plays a key role in many software engineering tasks, e.g., adding new features to software product lines (SPL) of information systems. Previous empirical studies have revealed that integrating design models is still considered a time-consuming and error-prone task. Unfortunately, integration approaches with tool support are still severely lacking. Even worse, little is known about the effort invested by developers to integrate models manually, and how correct the integrated models are. This paper proposes FMIT, which is a semiautomatic tool to support the integration of feature models. It comes up with a strategy-based approach to reduce the effort that developers invest to combine feature models and increase the amount of correctly integrated models. A controlled experiment was run with 10 volunteers through six realistic integration scenarios. Our results, supported by statistical tests, show that our semiautomatic approach not only reduced the integration effort by 73.01%, but also increased the number of correctly integrated feature models by 43.01%, compared with the manual approach. Our main contributions are a semiautomatic, strategy-based approach with tool support, and empirical evidence on its benefits. Our encouraging results open the way for the development of new heuristics and tools to support developers during the evolution of feature models.
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
一个支持特征模型集成的半自动工具
特征模型的集成在许多软件工程任务中起着关键作用,例如,向信息系统的软件产品线(SPL)添加新特性。以往的实证研究表明,集成设计模型仍然被认为是一项耗时且容易出错的任务。不幸的是,带有工具支持的集成方法仍然严重缺乏。更糟糕的是,很少有人知道开发人员为手工集成模型所投入的努力,以及集成模型的正确性。本文提出了一种支持特征模型集成的半自动工具FMIT。它提出了一种基于策略的方法,以减少开发人员为组合特征模型而投入的工作,并增加正确集成模型的数量。一项由10名志愿者参与的对照实验通过6个现实的整合场景进行。统计测试结果表明,与手动方法相比,半自动方法不仅减少了73.01%的集成工作量,而且正确集成的特征模型数量增加了43.01%。我们的主要贡献是一种带有工具支持的半自动、基于策略的方法,以及关于其好处的经验证据。我们令人鼓舞的结果为开发新的启发式方法和工具开辟了道路,以支持开发人员在特征模型的发展过程中。
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
自引率
0.00%
发文量
0
期刊最新文献
Outer-Tuning: an integration of rules, ontology and RDBMS Market Prediction in Criptocurrency: A Systematic Literature Mapping Machine learning techniques for code smells detection: an empirical experiment on a highly imbalanced setup Kairós LifeReview: A model for monitoring people with anxiety disorder
×
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