most citedHow Firms Adapt and Interact in Open Source Ecosystems: Analyzing Stakeholder Influence and Collaboration Patterns

27 citations · 34 across the 5 of their papers we have counts for

collaborators

6 papers

cs.SE20231 cited

A Static Analysis Platform for Investigating Security Trends in Repositories

Tim Sonnekalb, Christopher-Tobias Knaust, Bernd Gruner +5

Static analysis tools come in many forms andconfigurations, allowing them to handle various tasks in a (secure) development process: code style linting, bug/vulnerability detection…

cs.SE2022

Generalizability of Code Clone Detection on CodeBERT

Tim Sonnekalb, Bernd Gruner, Clemens-Alexander Brust +1

Transformer networks such as CodeBERT already achieve outstanding results for code clone detection in benchmark datasets, so one could assume that this task has already been solved…

astro-ph.IM20227 cited

Object classification on video data of meteors and meteor-like phenomena: algorithm and data

Rabea Sennlaub, Martin Hofmann, Mike Hankey +4

Every moment, countless meteoroids enter our atmosphere unseen. The detection and measurement of meteors offer the unique opportunity to gain insights into the composition of our s…

cs.LG2022

Dropout is NOT All You Need to Prevent Gradient Leakage

Daniel Scheliga, Patrick Mäder, Marco Seeland

Gradient inversion attacks on federated learning systems reconstruct client training data from exchanged gradient information. To defend against such attacks, a variety of defense…

cs.SE202227 cited

How Firms Adapt and Interact in Open Source Ecosystems: Analyzing Stakeholder Influence and Collaboration Patterns

Johan Linåker, Patrick Rempel, Björn Regnell +1

[Context and motivation] Ecosystems developed as Open Source Software (OSS) are considered to be highly innovative and reactive to new market trends due to their openness and wide-…

physics.flu-dyn2022

Direct data-driven forecast of local turbulent heat flux in Rayleigh-Bénard convection

Sandeep Pandey, Philipp Teutsch, Patrick Mäder +1

A combined convolutional autoencoder-recurrent neural network machine learning model is presented to analyse and forecast the dynamics and low-order statistics of the local convect…