1 citations · 2 across the 5 of their papers we have counts for
5 papers
TIPICAL -- Type Inference for Python In Critical Accuracy Level
Jonathan Elkobi, Bernd Gruner, Tim Sonnekalb +1
Type inference methods based on deep learning are becoming increasingly popular as they aim to compensate for the drawbacks of static and dynamic analysis approaches, such as high…
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…
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…
Cross-Domain Evaluation of a Deep Learning-Based Type Inference System
Bernd Gruner, Tim Sonnekalb, Thomas S. Heinze +1
Optional type annotations allow for enriching dynamic programming languages with static typing features like better Integrated Development Environment (IDE) support, more precise p…
ROMEO: Exploring Juliet through the Lens of Assembly Language
Clemens-Alexander Brust, Tim Sonnekalb, Bernd Gruner
Automatic vulnerability detection on C/C++ source code has benefitted from the introduction of machine learning to the field, with many recent publications targeting this combinati…