21 citations · 27 across the 12 of their papers we have counts for
12 papers
On Assessing the Relevance of Code Reviews Authored by Generative Models
Robert Heumüller, Frank Ortmeier
The use of large language models like ChatGPT in code review offers promising efficiency gains but also raises concerns about correctness and safety. Existing evaluation methods fo…
Previously on... Automating Code Review
Robert Heumüller, Frank Ortmeier
Modern Code Review (MCR) is a standard practice in software engineering, yet it demands substantial time and resource investments. Recent research has increasingly explored automat…
Improving Out-of-Distribution Detection with Markov Logic Networks
Konstantin Kirchheim, Frank Ortmeier
Out-of-distribution (OOD) detection is essential for ensuring the reliability of deep learning models operating in open-world scenarios. Current OOD detectors mainly rely on statis…
ASAP-Repair: API-Specific Automated Program Repair Based on API Usage Graphs
Sebastian Nielebock, Paul Blockhaus, Jacob Krüger +1
Modern software development relies on the reuse of code via Application Programming Interfaces (APIs). Such reuse relieves developers from learning and developing established algor…
Towards Transformer-based Homogenization of Satellite Imagery for Landsat-8 and Sentinel-2
Venkatesh Thirugnana Sambandham, Konstantin Kirchheim, Sayan Mukhopadhaya +1
Landsat-8 (NASA) and Sentinel-2 (ESA) are two prominent multi-spectral imaging satellite projects that provide publicly available data. The multi-spectral imaging sensors of the sa…
Automated Change Rule Inference for Distance-Based API Misuse Detection
Sebastian Nielebock, Paul Blockhaus, Jacob Krüger +1
Developers build on Application Programming Interfaces (APIs) to reuse existing functionalities of code libraries. Despite the benefits of reusing established libraries (e.g., time…
Addressing Randomness in Evaluation Protocols for Out-of-Distribution Detection
Konstantin Kirchheim, Tim Gonschorek, Frank Ortmeier
Deep Neural Networks for classification behave unpredictably when confronted with inputs not stemming from the training distribution. This motivates out-of-distribution detection (…
An Experimental Analysis of Graph-Distance Algorithms for Comparing API Usages
Sebastian Nielebock, Paul Blockhaus, Jacob Krüger +1
Modern software development heavily relies on the reuse of functionalities through Application Programming Interfaces (APIs). However, client developers can have issues identifying…
AndroidCompass: A Dataset of Android Compatibility Checks in Code Repositories
Sebastian Nielebock, Paul Blockhaus, Jacob Krüger +1
Many developers and organizations implement apps for Android, the most widely used operating system for mobile devices. Common problems developers face are the various hardware dev…
Guided Pattern Mining for API Misuse Detection by Change-Based Code Analysis
Sebastian Nielebock, Robert Heumüller, Kevin Michael Schott +1
Lack of experience, inadequate documentation, and sub-optimal API design frequently cause developers to make mistakes when re-using third-party implementations. Such API misuses ca…
Learning References with Gaussian Processes in Model Predictive Control applied to Robot Assisted Surgery
Janine Matschek, Tim Gonschorek, Magnus Hanses +3
One of the key benefits of model predictive control is the capability of controlling a system proactively in the sense of taking the future system evolution into account. However,…
Probabilistic Model-Based Safety Analysis
Matthias Güdemann, Frank Ortmeier
Model-based safety analysis approaches aim at finding critical failure combinations by analysis of models of the whole system (i.e. software, hardware, failure modes and environmen…