output
20152024
most citedFairSR: Fairness-aware Sequential Recommendation through Multi-Task Learning with Preference Graph Embeddings

49 citations

Showing cs.SEShow all

5 papers · 1 filter

cs.SE20235 cited

Revisiting Neural Program Smoothing for Fuzzing

Maria-Irina Nicolae, Max Eisele, Andreas Zeller

Testing with randomly generated inputs (fuzzing) has gained significant traction due to its capacity to expose program vulnerabilities automatically. Fuzz testing campaigns generat…

cs.SE202115 cited

Using Relative Lines of Code to Guide Automated Test Generation for Python

Josie Holmes, Iftekhar Ahmed, Caius Brindescu +3

Raw lines of code (LOC) is a metric that does not, at first glance, seem extremely useful for automated test generation. It is both highly language-dependent and not extremely mean…

cs.SE20213 cited

Restoring Execution Environments of Jupyter Notebooks

Jiawei Wang, Li Li, Andreas Zeller

More than ninety percent of published Jupyter notebooks do not state dependencies on external packages. This makes them non-executable and thus hinders reproducibility of scientifi…

cs.SE20198 cited

Better Code, Better Sharing:On the Need of Analyzing Jupyter Notebooks

Jiawei Wang, Li Li, Andreas Zeller

By bringing together code, text, and examples, Jupyter notebooks have become one of the most popular means to produce scientific results in a productive and reproducible way. As ma…

cs.SE20181 cited

Carving Parameterized Unit Tests

Alexander Kampmann, Andreas Zeller

We present a method to automatically extract ("carve") parameterized unit tests from system executions. The unit tests execute the same functions as the system tests they are carve…