MetricHaven: More than 23,000 Metrics for Measuring Quality Attributes of Software Product Lines

Sascha El-Sharkawy, Adam Krafczyk, Klaus Schmid
{"title":"MetricHaven: More than 23,000 Metrics for Measuring Quality Attributes of Software Product Lines","authors":"Sascha El-Sharkawy, Adam Krafczyk, Klaus Schmid","doi":"10.1145/3307630.3342384","DOIUrl":null,"url":null,"abstract":"Variability-aware metrics are designed to measure qualitative aspects of software product lines. As we identified in a prior SLR [6], there exist already many metrics that address code or variability separately, while the combination of both has been less researched. MetricHaven fills this gap, as it extensively supports combining information from code files and variability models. Further, we also enable the combination of well established single system metrics with novel variability-aware metrics, going beyond existing variability-aware metrics. Our tool supports most prominent single system and variability-aware code metrics. We provide configuration support for already implemented metrics, resulting in 23,342 metric variations. Further, we present an abstract syntax tree developed for MetricHaven, that allows the realization of additional code metrics. Tool: https://github.com/KernelHaven/MetricHaven Video: https://youtu.be/vPEmD5Sr6gM","PeriodicalId":424711,"journal":{"name":"Proceedings of the 23rd International Systems and Software Product Line Conference - Volume B","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 23rd International Systems and Software Product Line Conference - Volume B","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3307630.3342384","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Variability-aware metrics are designed to measure qualitative aspects of software product lines. As we identified in a prior SLR [6], there exist already many metrics that address code or variability separately, while the combination of both has been less researched. MetricHaven fills this gap, as it extensively supports combining information from code files and variability models. Further, we also enable the combination of well established single system metrics with novel variability-aware metrics, going beyond existing variability-aware metrics. Our tool supports most prominent single system and variability-aware code metrics. We provide configuration support for already implemented metrics, resulting in 23,342 metric variations. Further, we present an abstract syntax tree developed for MetricHaven, that allows the realization of additional code metrics. Tool: https://github.com/KernelHaven/MetricHaven Video: https://youtu.be/vPEmD5Sr6gM
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
MetricHaven:超过23,000个度量软件产品线质量属性的度量
可变性感知度量被设计用来度量软件产品线的定性方面。正如我们在之前的单反中所确定的[6],已经存在许多单独处理代码或可变性的指标,而对两者的组合研究较少。MetricHaven填补了这一空白,因为它广泛地支持从代码文件和可变性模型中组合信息。此外,我们还支持将建立良好的单一系统度量与新颖的可变性感知度量相结合,超越现有的可变性感知度量。我们的工具支持最突出的单系统和可变性代码度量。我们为已经实现的度量提供配置支持,从而产生23,342个度量变化。此外,我们提出了一个为MetricHaven开发的抽象语法树,它允许实现额外的代码度量。工具:https://github.com/KernelHaven/MetricHaven视频:https://youtu.be/vPEmD5Sr6gM
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
Enabling Efficient Automated Configuration Generation and Management Accessibility Variability Model: The UTPL MOOC Case Study symfinder: A Toolchain for the Identification and Visualization of Object-Oriented Variability Implementations Applying the QuARS Tool to Detect Variability Towards Efficient Analysis of Variation in Time and Space
×
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