DOI

This is the artifact for the FSE’18 paper Detection of Energy Inefficiencies in Android Wear Watch Faces by Hailong Zhang, Haowei Wu and Atanas Rountev. It contains the static analysis, testing framework, experimental subjects, materials for app market study, logs generated by the static analysis, and the result of testing. Details on the instructions and usage are in the readme files in each sub-folder.

Cite

@inproceedings{zhang-fse18,
  title = "Detection of Energy Inefficiencies in {Android} {Wear} Watch Faces", 
  author = "Hailong Zhang and Haowei Wu and Atanas Rountev",
  booktitle = "ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering",
  year = 2018
}

Installation

The artifact is available on Zenodo.

Alternatively, the implementation and app market study could be downloaded via GitHub:

git clone https://github.com/presto-osu/fse18.git

Due to GitHub’s limitation on file sizes, all benchmarks have to be downloaded separately elsewhere (~13GB) and extracted to the fse18 folder:

tar xvfJ fse18-benchmark.tar.xz --directory /path/to/fse18

After downloading all necessary files, follow the instructions here to reproduce the results in the paper.

Structure

Others may use the static analysis to detect inefficiencies for any new watch face, use the testing framework to validate the reports by static analysis, as well as utilizing the benchmarks located at apks for further studies.

Please refer to the readme files in each sub-directory for more details.

Questions

If you have any question, please contact the authors of the paper.