Energy consumption is a major concern when developing and evolving mobile applications. The user wishes to access fast and powerful mobile applications, which is usually in contrast to optimized battery life and heat generation. The software engineering community have acknowledged the relevance of the problem and researchers are investigating ways to reduce energy consumption, for example by examining which library, device configuration, and applications parameters should be used to promote long battery life. We conjecture that these studies are at the border between hardware and software and we must be careful on how the energy consumption is measured and how the energy consumption is attributed to methods and libraries.To the best of our knowledge, no previous work investigates how much energy and power consumption is due to high frequency events missed when sampling at low frequencies such as 10 kHz and verified the error at the precision of method level. Low frequency sampling is a rough approximation that hinders the understanding of fine grain details: the real picture of energy consumption as well as the root causes are missed. This has profound implications on the choice of methods to evolve or components to replace.In this paper, we propose an approach for accurate measurements of the energy consumption of mobile applications. We apply the proposed approach to assess the energy consumption of 21 mobile, closed source, applications and four open source Android applications.We show that by sampling at 10 kHz one may expect a median error of 8%, however, such error may be as high as 50% for short fast executing methods. Finally, we revisit a previous approach that estimates the energy consumption of methods based on execution time and found that it can miss as much as 84% of the energy, with a median of 30%.

In this new version more experiments have been done, considering closed and open source applications.