Android App Merging for Benchmark Speed-Up and Analysis Lift-Up

Felix Pauck, Shikun Zhang
{"title":"Android App Merging for Benchmark Speed-Up and Analysis Lift-Up","authors":"Felix Pauck, Shikun Zhang","doi":"10.1109/ASEW.2019.00019","DOIUrl":null,"url":null,"abstract":"In the field of software analysis a trade-off between scalability and accuracy always exists. In this respect, Android app analysis is no exception, in particular, analyzing large or many apps can be challenging. Dealing with many small apps is a typical challenge when facing micro-benchmarks such as DROIDBENCH or ICC-BENCH. These particular benchmarks are not only used for the evaluation of novel tools but also in continuous integration pipelines of existing mature tools to maintain and guarantee a certain quality-level. Considering this latter usage it becomes very important to be able to achieve benchmark results as fast as possible. Hence, benchmarks have to be optimized for this purpose. One approach to do so is app merging. We implemented the Android Merge Tool (AMT) following this approach and show that its novel aspects can be used to produce scaled up and accurate benchmarks. For such benchmarks Android app analysis tools do not suffer from the scalability-accuracy trade-off anymore. We show this throughout detailed experiments on DROIDBENCH employing three different analysis tools (AMANDROID, ICCTA, FLOWDROID). Benchmark execution times are largely reduced without losing benchmark accuracy. Moreover, we argue why AMT is an advantageous successor of the state-of-the-art app merging tool (APKCOMBINER) in analysis lift-up scenarios.","PeriodicalId":277020,"journal":{"name":"2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASEW.2019.00019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In the field of software analysis a trade-off between scalability and accuracy always exists. In this respect, Android app analysis is no exception, in particular, analyzing large or many apps can be challenging. Dealing with many small apps is a typical challenge when facing micro-benchmarks such as DROIDBENCH or ICC-BENCH. These particular benchmarks are not only used for the evaluation of novel tools but also in continuous integration pipelines of existing mature tools to maintain and guarantee a certain quality-level. Considering this latter usage it becomes very important to be able to achieve benchmark results as fast as possible. Hence, benchmarks have to be optimized for this purpose. One approach to do so is app merging. We implemented the Android Merge Tool (AMT) following this approach and show that its novel aspects can be used to produce scaled up and accurate benchmarks. For such benchmarks Android app analysis tools do not suffer from the scalability-accuracy trade-off anymore. We show this throughout detailed experiments on DROIDBENCH employing three different analysis tools (AMANDROID, ICCTA, FLOWDROID). Benchmark execution times are largely reduced without losing benchmark accuracy. Moreover, we argue why AMT is an advantageous successor of the state-of-the-art app merging tool (APKCOMBINER) in analysis lift-up scenarios.
Android应用合并的基准加速和分析提升
在软件分析领域,始终存在着可扩展性和准确性之间的权衡。在这方面,Android应用分析也不例外,特别是分析大型或许多应用可能具有挑战性。在面对DROIDBENCH或ICC-BENCH等微基准测试时,处理许多小型应用程序是一个典型的挑战。这些特定的基准不仅用于评估新工具,而且还用于现有成熟工具的持续集成管道中,以保持和保证一定的质量水平。考虑到后一种用法,能够尽可能快地获得基准测试结果变得非常重要。因此,必须为此目的对基准进行优化。一种方法是应用合并。我们按照这种方法实现了Android合并工具(AMT),并展示了其新颖的方面可以用于产生缩放和准确的基准。对于这样的基准测试,Android应用程序分析工具不再受到可伸缩性和准确性权衡的影响。我们通过使用三种不同的分析工具(AMANDROID, ICCTA, FLOWDROID)在DROIDBENCH上进行详细的实验来证明这一点。在不损失基准准确性的情况下,大大减少了基准执行时间。此外,我们还讨论了为什么AMT是分析提升场景中最先进的应用合并工具(APKCOMBINER)的有利继承者。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信