软件度量在研究软件开发中的应用综述

Nasir U. Eisty, G. Thiruvathukal, Jeffrey C. Carver
{"title":"软件度量在研究软件开发中的应用综述","authors":"Nasir U. Eisty, G. Thiruvathukal, Jeffrey C. Carver","doi":"10.1109/eScience.2018.00036","DOIUrl":null,"url":null,"abstract":"Background: Breakthroughs in research increasingly depend on complex software libraries, tools, and applications aimed at supporting specific science, engineering, business, or humanities disciplines. The complexity and criticality of this software motivate the need for ensuring quality and reliability. Software metrics are a key tool for assessing, measuring, and understanding software quality and reliability. Aims: The goal of this work is to better understand how research software developers use traditional software engineering concepts, like metrics, to support and evaluate both the software and the software development process. One key aspect of this goal is to identify how the set of metrics relevant to research software corresponds to the metrics commonly used in traditional software engineering. Method: We surveyed research software developers to gather information about their knowledge and use of code metrics and software process metrics. We also analyzed the influence of demographics (project size, development role, and development stage) on these metrics. Results: The survey results, from 129 respondents, indicate that respondents have a general knowledge of metrics. However, their knowledge of specific SE metrics is lacking, their use even more limited. The most used metrics relate to performance and testing. Even though code complexity often poses a significant challenge to research software development, respondents did not indicate much use of code metrics. Conclusions: Research software developers appear to be interested and see some value in software metrics but may be encountering roadblocks when trying to use them. Further study is needed to determine the extent to which these metrics could provide value in continuous process improvement.","PeriodicalId":6476,"journal":{"name":"2018 IEEE 14th International Conference on e-Science (e-Science)","volume":"52 1","pages":"212-222"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A Survey of Software Metric Use in Research Software Development\",\"authors\":\"Nasir U. Eisty, G. Thiruvathukal, Jeffrey C. Carver\",\"doi\":\"10.1109/eScience.2018.00036\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Breakthroughs in research increasingly depend on complex software libraries, tools, and applications aimed at supporting specific science, engineering, business, or humanities disciplines. The complexity and criticality of this software motivate the need for ensuring quality and reliability. Software metrics are a key tool for assessing, measuring, and understanding software quality and reliability. Aims: The goal of this work is to better understand how research software developers use traditional software engineering concepts, like metrics, to support and evaluate both the software and the software development process. One key aspect of this goal is to identify how the set of metrics relevant to research software corresponds to the metrics commonly used in traditional software engineering. Method: We surveyed research software developers to gather information about their knowledge and use of code metrics and software process metrics. We also analyzed the influence of demographics (project size, development role, and development stage) on these metrics. Results: The survey results, from 129 respondents, indicate that respondents have a general knowledge of metrics. However, their knowledge of specific SE metrics is lacking, their use even more limited. The most used metrics relate to performance and testing. Even though code complexity often poses a significant challenge to research software development, respondents did not indicate much use of code metrics. Conclusions: Research software developers appear to be interested and see some value in software metrics but may be encountering roadblocks when trying to use them. Further study is needed to determine the extent to which these metrics could provide value in continuous process improvement.\",\"PeriodicalId\":6476,\"journal\":{\"name\":\"2018 IEEE 14th International Conference on e-Science (e-Science)\",\"volume\":\"52 1\",\"pages\":\"212-222\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 14th International Conference on e-Science (e-Science)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/eScience.2018.00036\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 14th International Conference on e-Science (e-Science)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/eScience.2018.00036","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

背景:研究的突破越来越依赖于复杂的软件库、工具和旨在支持特定科学、工程、商业或人文学科的应用程序。该软件的复杂性和关键性激发了确保质量和可靠性的需求。软件度量是评估、度量和理解软件质量和可靠性的关键工具。目的:这项工作的目标是更好地理解研究软件开发人员如何使用传统的软件工程概念,如度量,来支持和评估软件和软件开发过程。该目标的一个关键方面是确定与研究软件相关的度量标准集如何与传统软件工程中常用的度量标准相对应。方法:我们调查了研究软件开发人员,以收集有关他们的知识和使用代码度量和软件过程度量的信息。我们还分析了人口统计数据(项目规模、开发角色和开发阶段)对这些指标的影响。结果:来自129名受访者的调查结果表明,受访者对指标有一般的了解。然而,他们缺乏特定SE度量的知识,他们的使用更加有限。最常用的度量标准与性能和测试有关。即使代码复杂性经常对研究软件开发构成重大挑战,被调查者也没有指出代码度量的使用。结论:研究软件开发人员似乎很感兴趣,并且看到了软件度量的一些价值,但在尝试使用它们时可能会遇到障碍。需要进一步的研究来确定这些量度在持续过程改进中提供价值的程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
A Survey of Software Metric Use in Research Software Development
Background: Breakthroughs in research increasingly depend on complex software libraries, tools, and applications aimed at supporting specific science, engineering, business, or humanities disciplines. The complexity and criticality of this software motivate the need for ensuring quality and reliability. Software metrics are a key tool for assessing, measuring, and understanding software quality and reliability. Aims: The goal of this work is to better understand how research software developers use traditional software engineering concepts, like metrics, to support and evaluate both the software and the software development process. One key aspect of this goal is to identify how the set of metrics relevant to research software corresponds to the metrics commonly used in traditional software engineering. Method: We surveyed research software developers to gather information about their knowledge and use of code metrics and software process metrics. We also analyzed the influence of demographics (project size, development role, and development stage) on these metrics. Results: The survey results, from 129 respondents, indicate that respondents have a general knowledge of metrics. However, their knowledge of specific SE metrics is lacking, their use even more limited. The most used metrics relate to performance and testing. Even though code complexity often poses a significant challenge to research software development, respondents did not indicate much use of code metrics. Conclusions: Research software developers appear to be interested and see some value in software metrics but may be encountering roadblocks when trying to use them. Further study is needed to determine the extent to which these metrics could provide value in continuous process improvement.
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
期刊最新文献
Occam: Software Environment for Creating Reproducible Research Smart Data Scouting in Professional Soccer: Evaluating Passing Performance Based on Position Tracking Data Improving LBFGS Optimizer in PyTorch: Knowledge Transfer from Radio Interferometric Calibration to Machine Learning Nordic Exome Variant Catalogue a Web Resource for Genomic Data Browsing Survey on Research Software Engineering in the Netherlands
×
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