Appcestry
“Appcestry” (a portmanteau of “app” and “ancestry”) is a tool for the study of similarities of Android applications (apps) started by Jason Chao for his Master of Science in Big Data and Digital Futures dissertation. The tool extracts features from Android Application PacKages (APK) and transforms them into a format which this project names “AppGenes”. AppGenes may be used by Appcestry and other machine learning tools to discover similar Android applications.
Video https://youtu.be/QLr-cvRAjio
Demo http://appcestry.jasontc.net/
Presentation on how Appcestry works
Full text of the dissertation DOI 10.13140/RG.2.2.12499.02081
Steps to deploy Appcestry
Clone the Appcestry repo
git clone git@github.com:jason-chao/appcestry.git
Alternatively, if you do not wish to clone the repo, you may just download docker-compose.yml and appcestry_cluster.env.
Pull images from Docker registry
docker pull jasonthc/appcestry:0.0.1b
docker pull jasonthc/appcestry-frontend:0.0.1b
Use Docker to deploy Appcestry
docker stack deploy --compose-file docker-compose.yml appcestry
After deployment, use a browser to open http://localhost:80. By default, port 80 of the web-frontend container is mapped to port 80 of the host machine.
Scale the worker nodes in swarm mode
The number '2' is an example only. It may be changed to a larger number depending on the infrastructure and your need.
docker service scale appcestry_dask-worker=2
docker service scale appcestry_rq-worker-compare=2
docker service scale appcestry_rq-worker-convert=2