This release contains the static analysis, testing framework, experimental subjects, materials for app market study, logs generated by the static analysis, and the result of testing, for our FSE’18 paper:
@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
}
The artifacts are 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
from Zenodo (~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 to reproduce the results in the paper.
analysis
includes the code for static analysis;analysis-logs
contains the log files by running the static analysis against
the 1490 experimental subjects;apks
(download separately) includes all the experimental subjects,
i.e., the APK files for 1490 watch faces, as well as the tool to download them;app-market-study
contains the crawler for app markets and the scripts to
generate statistics in the paper;INSTALL.md
includes the instructions to reproduce the experimental results in
the paper;LICENSE
includes the copyright information;README.md
is this file;testing
contains the testing framework and the results.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.
If you have any question, please contact the authors of the paper.