GHTorrent: Github's data from a firehose

By Georgios Gousios, Diomidis D. Spinellis. IEEE Working Conference on Mining Software Repositories, 2012

318 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/de760552279b241976676f4723a159060a433198

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Information Systems

In Information Systems and Management

Citations in the corpus

Recovering clear, natural identifiers from obfuscated JS names (2017, unknown): “We � rst identi � ed the oldest 100,000 non-fork JavaScript repositories using GHT �� [22] and cloned them from G �� H �� , yielding 5.3 million � les with a extension.”
Mining source code repositories at massive scale using language modeling (2013, background): “Another GitHub dataset, GHTorrent [9] has a different goal compared to our corpus, excluding source code and focusing on users, pull requests and all the issues surrounding social coding.”
A Convolutional Attention Network for Extreme Summarization of Source Code (2016, methodology): “We obtained the most popular projects by taking the sum of thez-scores of the number of watchers and forks of each project, using GHTorrent (Gousios & Spinellis, 2012).”
CURE: Code-Aware Neural Machine Translation for Automatic Program Repair (2021, methodology): “PL Training Data: We download all (1,700) open-source Java projects from GitHub that have at least one commit before the first bug in Defects4J according to GHTorrent [42] and roll them back to a version before 2006 to avoid using future data.”
The promises and perils of mining GitHub (2009, methodology): “The ghtorrent [11] project provides a mirror of the GitHub api data.”
An in-depth study of the promises and perils of mining GitHub (2015, methodology): “We used the GHTorrent (Gousios and Spinellis 2012) Jan 20143 dataset for our study.”
CoCoNuT: combining context-aware neural translation models using ensemble for program repair (2020, methodology): “For Java, we use GHTorrent [21] to collect instances from 59,237 projects that contain commits before 2010.”
CodeFill: Multi-token Code Completion by Jointly learning from Structure and Naming Sequences (2022, methodology): “• TheCodeFill dataset, whichwas collected by queryingGHTorrent [15] for all non-forked Python repositories with more than 20 stars (58k repositories).”
An exploratory study of the pull-based software development model (2014, methodology): “ment forge, as made available through the GHTorrent project [17].”
The GHTorent dataset and tool suite (2013, methodology): “An outline of the project and bits of the implementation were presented in [2].”