SEOct 19, 2019

On the Energy Footprint of Mobile Testing Frameworks

arXiv:1910.08768v11 citations
Originality Synthesis-oriented
AI Analysis

This addresses the issue of energy overhead in mobile testing frameworks for developers, providing practical guidance to reduce energy consumption, though it is incremental as it focuses on evaluating existing frameworks rather than proposing a new method.

The paper tackled the problem of high energy consumption in mobile applications by evaluating eight popular mobile UI automation frameworks, discovering that some frameworks increase energy consumption by up to roughly 2200%, with Espresso being the most energy-efficient.

High energy consumption is a challenging issue that an ever increasing number of mobile applications face today. However, energy consumption is being tested in an ad hoc way, despite being an important non-functional requirement of an application. Such limitation becomes particularly disconcerting during software testing: on the one hand, developers do not really know how to measure energy; on the other hand, there is no knowledge as to what is the energy overhead imposed by the testing framework. In this paper, as we evaluate eight popular mobile UI automation frameworks, we have discovered that there are automation frameworks that increase energy consumption up to roughly 2200%. While limited in the interactions one can do, Espresso is the most energy efficient framework. However, depending on the needs of the tester, Appium, Monkeyrunner, or UIAutomator are good alternatives. In practice, results show that deciding which is the most suitable framework is vital. We provide a decision tree to help developers make an educated decision on which framework suits best their testing needs.

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