activity
20172026
most citedA ground-truth dataset and classification model for detecting bots in GitHub issue and PR comments

78 citations · 107 across the 15 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

cs.SE2021

On the Impact of Security Vulnerabilities in the npm and RubyGems Dependency Networks

Ahmed Zerouali, Tom Mens, Alexandre Decan +1

The increasing interest in open source software has led to the emergence of large language-specific package distributions of reusable software libraries, such as npm and RubyGems.…

cs.SE2021★ 5 cited

Evaluating a bot detection model on git commit messages

Mehdi Golzadeh, Alexandre Decan, Tom Mens

Detecting the presence of bots in distributed software development activity is very important in order to prevent bias in large-scale socio-technical empirical analyses. In previou…

cs.SE2021

A Quantitative Assessment of Package Freshness in Linux Distributions

Damien Legay, Alexandre Decan, Tom Mens

Linux users expect fresh packages in the official repositories of their distributions. Yet, due to philosophical divergences, the packages available in various distributions do not…

cs.SE2021

Identifying bot activity in GitHub pull request and issue comments

Mehdi Golzadeh, Alexandre Decan, Eleni Constantinou +1

Development bots are used on Github to automate repetitive activities. Such bots communicate with human actors via issue comments and pull request comments. Identifying such bot co…

cs.SE2021★ 4 cited

Lost in Zero Space -- An Empirical Comparison of 0.y.z Releases in Software Package Distributions

Alexandre Decan, Tom Mens

Distributions of open source software packages dedicated to specific programming languages facilitate software development by allowing software projects to depend on the functional…