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

S Romansky - arXiv preprint arXiv:1411.2047, 2014 - arxiv.org
S Romansky
arXiv preprint arXiv:1411.2047, 2014arxiv.org
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 …
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.
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