Probabilistic regression suites for functional verification

S. Fine, S. Ur, A. Ziv
{"title":"Probabilistic regression suites for functional verification","authors":"S. Fine, S. Ur, A. Ziv","doi":"10.1145/996566.996581","DOIUrl":null,"url":null,"abstract":"Random test generators are often used to create regression suites on-the-fly. Regression suites are commonly generated by choosing several specifications and generating a number of tests from each one, without reasoning which specification should he used and how many tests should he generated from each specification. This paper describes a technique for building high quality random regression suites. The proposed technique uses information about the probablity of each test specification covering each coverage task. This probability is used, in tun, to determine which test specifications should be included in the regression suite and how many tests should, be generated from each specification. Experimental results show that this practical technique can he used to improve the quality, and reduce the cost, of regression suites. Moreover, it enables better informed decisions regarding the size and distribution of the regression suites, and the risk involved.","PeriodicalId":115059,"journal":{"name":"Proceedings. 41st Design Automation Conference, 2004.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 41st Design Automation Conference, 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/996566.996581","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

Abstract

Random test generators are often used to create regression suites on-the-fly. Regression suites are commonly generated by choosing several specifications and generating a number of tests from each one, without reasoning which specification should he used and how many tests should he generated from each specification. This paper describes a technique for building high quality random regression suites. The proposed technique uses information about the probablity of each test specification covering each coverage task. This probability is used, in tun, to determine which test specifications should be included in the regression suite and how many tests should, be generated from each specification. Experimental results show that this practical technique can he used to improve the quality, and reduce the cost, of regression suites. Moreover, it enables better informed decisions regarding the size and distribution of the regression suites, and the risk involved.
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
用于功能验证的概率回归套件
随机测试生成器通常用于动态创建回归套件。回归套件通常是通过选择几个规范并从每个规范生成许多测试来生成的,而不需要推理应该使用哪个规范以及应该从每个规范生成多少测试。本文描述了一种构建高质量随机回归套件的技术。所建议的技术使用关于每个测试规范覆盖每个覆盖任务的概率的信息。这个概率依次用于确定回归套件中应该包括哪些测试规范,以及应该从每个规范生成多少测试。实验结果表明,这种实用的方法可以提高回归套件的质量,降低回归套件的成本。此外,它支持关于回归套件的大小和分布以及所涉及的风险的更明智的决策。
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
STAC: statistical timing analysis with correlation Large-scale placement by grid-warping Security as a new dimension in embedded system design An integrated hardware/software approach for run-time scratchpad management Reliability-driven layout decompaction for electromigration failure avoidance in complex mixed-signal IC designs
×
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