Investigation of the relationship between code change set n-grams and change in energy consumption
This addresses the lack of tools for developers to assess how code changes affect battery life on mobile devices, though it is incremental as it builds on existing Green Mining concepts.
The study investigated whether source code changeset perplexity correlates with changes in energy consumption to aid developers in predicting software energy impact, but found weak to no correlation in the case study.
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.