Code Monkey home page Code Monkey logo

greenlab-kebab / gl-kebab Goto Github PK

View Code? Open in Web Editor NEW
0.0 2.0 0.0 1.14 GB

Replication package of the paper "An Empirical Analysis of JavaScript Dead Code in the Wild" submitted for the Green Lab course 2019-2020 edition

License: GNU General Public License v3.0

Shell 0.01% Python 0.04% TeX 0.01% R 0.01% CSS 7.82% HTML 34.79% JavaScript 57.14% Stata 0.03% Hack 0.01% PHP 0.09% ASP 0.01% TypeScript 0.06% Perl 6 0.01% Assembly 0.01% Perl 0.01% DIGITAL Command Language 0.01% Roff 0.01% Java 0.01%
empirical-software-engineering green-software

gl-kebab's Introduction

An Empirical Analysis of JavaScript Dead Code in the Wild – Replication Package (Green Lab 2019-2020)

This project refers to the course assignment An Empirical Analysis of JavaScript Dead Code in the Wild of the 2019-2020 edition of the Vrije Universiteit Amsterdam, Computer Science Master Degree, Green Lab course. This repository contains all information required to replicate the experimentation, described by the instructions in this README.

Project Goal

This project goal is to investigate to what extent JavaScript dead code impacts popular mobile web apps in the wild (where in the wild is a synonym for in production) in terms of page load time and energy consumption.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for experiment replication purpose.

Prerequisites

The project makes uses of the following packages

  • Lacuna V2: Provides the analyse and removal JavaScript dead code. Originally forked from Kishanjay repository, for which several adjustements were made.
  • Android Runner: Provides the automation of the experiment execution in Android devices. Forked from S2-group repostiory. No updates were required.
  • GL Kebab R: Provides the randomization in the experiment design and the data analysis of the results produced by Android Runner.
  • GL Kebab Subjects: Provides the experiment subjects and scripts to automate Lacuna V2 execution.
  • GL Kebab Android Runner Scripts: Provides scripts used when running Android Runner for this project.

Android Runner limit the usage of Linux and macOS machines only. As it requires extra effort to running on macOS, this project experiment was executed in a Linux machine.

Each package has its requirements, overall, this project was executed using:

  • Linux distribution -- Ubuntu 18.04 LTS
  • Android device -- LG Nexus 5X -- Android OS v8.1.0
  • Android Studio SDK
  • Python v2.7
  • JDK v8
  • NodeJS v10
  • NPM v6
  • R

While older versions of the linux distribution, Android OS, NodeJS and NPM might work, they were not tested.

It is not recommended the use of Virtual Machines.

Instalation and usage

You can refer to each package readme available at each subpackage for installation process and how to use. They should be used in the following order:

  1. Lacuna V2
  2. GL Kebab Subjects
  3. Android Runner.
  4. GL Kebab Android Runner Scripts
  5. GL Kebab R

Automation scripts

gitsubtree

This project uses git subtree to manage the dependency packages. An automation script is available at gitsubtree.command, which provides the following commands:

  • sh gitsubtree set_git_remote: Save the remote packages URL by executing git remote add <package_name> <package_url> for all packages.
  • sh gitsubtree set_git_remote: Remove the remote packages URLs by executing git remote remove <package_name> for all packages.
  • sh gitsubtree pull_subtrees: Fetch the changes from the remote packages and merge to the local repository by executing git subtree add --prefix=<dest_path> --squash <package_name> master for all packages;

For replication of the experiment, it is not necessary to fetch the packages. The packages should be fetched during development only. Modifications in the packages should be made in the package repository.

Authors

License

This project is licensed under the GPL-3.0 License - see the LICENSE file for details.

Acknowledgments

For the guidance over the project and detailed feedback during the experimentation design, planning and execution, we thank:

For providing the required tools to make this project possible

gl-kebab's People

Contributors

sshann avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.