IMGDroid:用于检测Android应用程序中图像加载缺陷的静态分析器

Wei Song, Mengqi Han, Jeff Huang
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引用次数: 0

摘要

我们总结了Android应用中图片加载缺陷的五种反模式,包括:意图传递图片、不调整大小的图片解码、未经许可的本地图片加载、不缓存的重复解码、UI线程的图像解码。在反模式的基础上,提出了一种静态分析器IMGDroid来自动有效地检测此类缺陷。读者可以从GitHub和Zenodo访问我们的工件,并可以运行IMGDroid来检测Android应用程序中的图像加载缺陷;所以我们正在申请可重复使用和可用的徽章。我们在Java中实现了IMGDroid,并在Windows 10、JDK 1.8和Android 7.1.1的计算机上进行了实验。因此,审稿人需要熟悉Java并熟练使用Eclipse。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IMGDroid: A Static Analyzer for Detecting Image Loading Defects in Android Applications
We summarize five anti-patterns of image loading defects in Android apps, including image passing by intent, image decoding without resizing, local image loading without permission, repeated decoding without caching, and image decoding in UI thread. Based on the anti-patterns, we propose a static analyzer, IMGDroid, to automatically and effectively detect such defects. Readers can access our artifacts from GitHub and Zenodo, and can run IMGDroid to detect image loading defects in Android apps; so we are applying for Reusable and Available Badges. We implement IMGDroid in Java, and perform the experiments on a computer with Windows 10, JDK 1.8, and Android 7.1.1. Therefore, reviewers are required to be familiar with Java and proficient in using Eclipse.
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