A Framework for the Automatic Execution of Measurement-based Experiments on Android Devices

I. Malavolta, E. M. Grua, Cheng-Yu Lam, R. D. Vries, Franky Tan, Eric Zielinski, Michael Peters, Luuk Kaandorp
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引用次数: 22

Abstract

Conducting measurement-based experiments is fundamental for assessing the quality of Android apps in terms of, e.g., energy consumption, CPU, and memory usage. However, orchestrating such experiments is not trivial as it requires large boilerplate code, careful setup of measurement tools, and the adoption of various empirical best practices scattered across the literature. All together, those factors are slowing down the scientific advancement and harming experiments' replicability in the mobile software engineering area. In this paper we present Android Runner (AR), a framework for automatically executing measurement-based experiments on native and web apps running on Android devices. In AR, an experiment is defined once in a descriptive fashion, and then its execution is fully automatic, customizable, and replicable. AR is implemented in Python and it can be extended with third-party profilers. AR has been used in more than 25 scientific studies primarily targeting performance and energy efficiency.
基于测量的实验在Android设备上自动执行的框架
进行基于测量的实验是评估Android应用质量的基础,例如,能量消耗,CPU和内存使用。然而,编排这样的实验并不是微不足道的,因为它需要大量的样板代码,仔细设置测量工具,并采用分散在文献中的各种经验最佳实践。总之,这些因素正在减缓科学进步,并损害移动软件工程领域实验的可复制性。在本文中,我们介绍了Android Runner (AR),这是一个在Android设备上运行的本机和web应用程序上自动执行基于测量的实验的框架。在AR中,实验以描述性的方式定义一次,然后它的执行是全自动的、可定制的和可复制的。AR是用Python实现的,它可以通过第三方分析器进行扩展。AR已经在超过25项主要针对性能和能源效率的科学研究中使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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