@inproceedings{bangash2022ICSENIER-blackbox-energy,
 abstract = {Android byte-code transformations are used to optimize applications (apps) in terms of run-time performance and size. But do they affect the energy consumption during this process? If they do, can we employ them to reduce an app’s energy consumption? Given that most existing energy optimization techniques require developers to modify their code, a byte-code level modification technique will save developers’ time and effort. In this paper, we investigate if byte-code transformations combined with genetic search can reduce an app’s energy consumption. After applying our technique on four real-world apps, we find that some combinations of the byte-code transformations reduce the energy consumption by up to 11%.},
 accepted = {2021-12-30},
 author = {Abdul Ali Bangash and Karim Ali and Abram Hindle},
 authors = {Abdul Ali Bangash, Karim Ali, Abram Hindle},
 booktitle = {ICSE-NIER'22},
 code = {bangash2022ICSENIER-blackbox-energy},
 data = {https://github.com/AbdulAli/EnergyDataset-ICSE-NIER22},
 date = {2022-05-21},
 funding = {NSERC Discovery},
 location = {Pittsburgh, United States},
 pagerange = {1--5},
 pages = {1--5},
 rate = {26.8%},
 role = {Co-Author},
 title = {A Black Box Technique to Reduce Energy Consumption of Android Apps},
 type = {inproceedings},
 url = {http://softwareprocess.ca/pubs/bangash2022ICSENIER-blackbox-energy.pdf},
 venue = {ICSE-NIER'22},
 year = {2022}
}