Green mining: A methodology of relating software change to power consumption

Abstract

Power consumption is becoming more and more important with the increased popularity of smart-phones, tablets and laptops. The threat of reducing a customer's battery-life now hangs over the software developer who asks, "will this next change be the one that causes my software to drain a customer's battery?" One solution is to detect power consumption regressions by measuring the power usage of tests, but this is time-consuming and often noisy. An alternative is to rely on software metrics that allow us to estimate the impact that a change might have on power consumption thus relieving the developer from expensive testing. This paper presents a general methodology for investigating the impact of software change on power consumption, we relate power consumption to software changes, and then investigate the impact of static OO software metrics on power consumption. We demonstrated that software change can effect power consumption using the Firefox web-browser and the Azureus/Vuze BitTorrent client. We found evidence of a potential relationship between some software metrics and power consumption. In conclusion, we explored the effect of software change on power consumption on two projects; and we provide an initial investigation on the impact of software metrics on power consumption.

Mining questions about software energy consumption

“…Energy-efficient solutions are highly sought after across the compute stack, with more established results through innovations in hardware/architecture [2,14,28], operating systems [10,19,24], and runtime systems [8,25,31]. In recent years, there is a growing interest in studying energy consumption from higher layers of the compute stack and most of these studies focus on application software [13,15,18,23,26,29]. These approaches complement prior hardware/OS-centric solutions, so that improvements at the hardware/OS level are not cancelled out at the application level, e.g., due to misuses of language/library/application features.…”

What do programmers know about the energy consumption of software?

“…For question 5, the expected ranking on mobile device is (1) Screen & GPU; (2) CPU; (3) Network; (4) Hard Disk Drive; (5) Memory. These expected rankings are based on current conventional wisdom, backed up by experiments that we have performed over the last three years and recent studies [3,5,9]. As these rankings are not written in stone, they can differ across specific hardware.…”

Empirical Evaluation of the Energy Impact of Refactoring Code Smells

“…As shown by Pinto et al [32], only since recent years the energy efficiency of application software is taken into consideration [47]. It is expected that increasing software energy efficiency can cause major changes in the energy consumption of ICT, thanks to the global scale of software usage [22]. Therefore, the next step in finding significant energy efficient improvements in ICT will most likely be software related.…”