Using compression algorithms to support the comprehension of program traces

Neil Walkinshaw, S. Afshan, Phil McMinn
{"title":"Using compression algorithms to support the comprehension of program traces","authors":"Neil Walkinshaw, S. Afshan, Phil McMinn","doi":"10.1145/1868321.1868323","DOIUrl":null,"url":null,"abstract":"Several software maintenance tasks such as debugging, phase-identification, or simply the high-level exploration of system functionality, rely on the extensive analysis of program traces. These usually require the developer to manually discern any repeated patterns that may be of interest from some visual representation of the trace. This can be both time-consuming and inaccurate; there is always the danger that visually similar trace-patterns actually represent distinct program behaviours. This paper presents an automated phase-identification technique. It is founded on the observation that the challenge of identifying repeated patterns in a trace is analogous to the challenge faced by data-compression algorithms. This applies an established data compression algorithm to identify repeated phases in traces. The SEQUITUR compression algorithm not only compresses data, but organises the repeated patterns into a hierarchy, which is especially useful from a comprehension standpoint, because it enables the analysis of a trace at at varying levels of abstraction.","PeriodicalId":315305,"journal":{"name":"International Workshop on Dynamic Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Dynamic Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1868321.1868323","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 30

Abstract

Several software maintenance tasks such as debugging, phase-identification, or simply the high-level exploration of system functionality, rely on the extensive analysis of program traces. These usually require the developer to manually discern any repeated patterns that may be of interest from some visual representation of the trace. This can be both time-consuming and inaccurate; there is always the danger that visually similar trace-patterns actually represent distinct program behaviours. This paper presents an automated phase-identification technique. It is founded on the observation that the challenge of identifying repeated patterns in a trace is analogous to the challenge faced by data-compression algorithms. This applies an established data compression algorithm to identify repeated phases in traces. The SEQUITUR compression algorithm not only compresses data, but organises the repeated patterns into a hierarchy, which is especially useful from a comprehension standpoint, because it enables the analysis of a trace at at varying levels of abstraction.
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
使用压缩算法来支持程序跟踪的理解
一些软件维护任务,如调试、阶段识别,或者简单的系统功能的高级探索,都依赖于对程序跟踪的广泛分析。这些通常需要开发人员从跟踪的一些可视化表示中手动识别任何可能感兴趣的重复模式。这既耗时又不准确;视觉上相似的跟踪模式实际上表示不同的程序行为总是存在危险的。本文提出了一种自动相位识别技术。它是建立在这样的观察基础上的:在跟踪中识别重复模式的挑战类似于数据压缩算法所面临的挑战。这应用了一种已建立的数据压缩算法来识别迹线中的重复相位。SEQUITUR压缩算法不仅压缩数据,而且将重复的模式组织到层次结构中,这从理解的角度来看特别有用,因为它支持在不同抽象级别上分析跟踪。
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
Dynamic analysis of inefficiently-used containers Dynamic cost verification for cloud applications Communication-aware HW/SW co-design for heterogeneous multicore platforms Extended program invariants: applications in testing and fault localization Evaluating program analysis and testing tools with the RUGRAT random benchmark application generator
×
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