Investigation of the relationship between code change set n-grams and change in energy consumption

TL;DR

This study explores whether source code change set n-gram perplexity correlates with energy consumption changes in mobile software, aiming to develop predictive tools for energy impact of code modifications.

Contribution

It applies Green Mining and n-gram models to analyze the relationship between code changes and energy consumption, revealing weak correlation and suggesting future research directions.

Findings

Weak to no correlation between perplexity and energy change

Potential for developing energy impact prediction tools

Highlights need for further investigation in this area

Abstract

The amount of software running on mobile devices is constantly growing as consumers and industry purchase more battery powered devices. On the other hand, tools that provide developers with feed- back on how their software changes affect battery life are not widely available. This work employs Green Mining, the study of the rela- tionship between energy consumption and software changesets, and n-gram language models to evaluate if source code changeset perplex- ity correlates with change in energy consumption. A correlation be- tween perplexity and change in energy consumption would permit the development of a tool that predicts the impact a code changeset may have on a software applications energy consumption. The case study results show that there is weak to no correlation between cross en- tropy and change in energy consumption. Therefore, future areas of investigation are proposed.