S2-group / EASE-2022-energy-web-assembly-rep-pkg

EASE 2022 - Comparing the Energy Efficiency of WebAssembly and JavaScript in Web Applications on Android Mobile Devices

EASE 2022 Replication Package

This repository contains the replication package of the paper titled Comparing the Energy Efficiency of WebAssembly and JavaScript in Web Applications on Android Mobile Devices and published at the 25th International Conference on Evaluation and Assessment in Software Engineering (EASE 2022).

This experiment made use of the Ostrich benchmarking suite, which can be found here. All copyrights of these benchmarking algorithms belong to the license holders of the Ostrich benchmarking suite.

The full dataset including raw data, data analysis scripts and automatization scripts produced during the study are available below.

Structure of the replication package

This replication package contains several directories. The experiment contains the Android Runner configuration, the scripts that were used during the experiment and the subjects. The android-runner directory contains an altered version of Android Runner. This is Android Runner with added support for the Firefox Nightly web browser. The results package contains the unprocessed results of the experiment and a Python script to aggregate the results and calculate the Joules used per run. The figures directory contains all the figures presented in the paper. The rscripts directory contains the R file used to analyse the results.

Dependencies

This experiment uses several Python packages. To install them, use the following command:

$ python3 -m pip install -r requirements.txt

The experiment also depends on adb. Install it on the Pi:

$ sudo apt install adb

Building the subjects

Building the subjects depends on Emscripten. To install Emscripten on your machine, follow these instructions.

To build the subjects, execute the following commands:

$ cd experiments/subjects
$ make

Running the experiment

To run the experiment, a Raspberry Pi should be configured according to the instructions in the Android Runner repostory

The Raspberry Pi should be connected to the same router that the Android device connects to. Place the subjects directory containing the built subjects in a directory on the Pi. To start the webserver, use the following commands:

$ cd subjects
$ python -m http.server 8001

We recommend running these commands in a tmux session, and then detach from the session.

In the config.json file in the experiments directory, change the IP addresses in the "paths" object to the IP address of the Raspberry Pi.

Now, set up the connection to the Android device. The Pi should control the device over WiFi, because the USB connection will get severed during runs. Connect the Android device to the router, and note its IP address.

In the android-runner directory, change the devices.json file so that the entry for "nexus6p" corresponds to ":5555".

Run:

$ adb devices
$ adb tcpip 5555
$ adb connect <ip address of the phone>

Place the android-runner directory and the experiment directory on the Pi, in the same directory and navigate to that directory.

The experiment is now ready to be run. In the root directory of this repository, run the following command.

$ python3 android-runner experiment/config.json

Sometimes the experiment might crash due to a Trepn error. To automate restarting the experiment, interrupt the experiment once and note the path to the progress.xml file. In start.sh, replace the path placeholder to the path that you just noted. Place start.sh in the same directory as the android-runner and experiment directories and run it using:

$ bash start.sh

The experiment will now automatically restart if it crashes.

Aggregating the data

In the results directory, the python script prepare_data.py can be used to aggregate the data of all the runs and convert the measurements to consumed Joules per run. Run it with python3.