4 citations · 4 across the 6 of their papers we have counts for
4 papers · 1 filter
CodeTransBenchmark: Evaluating LLM-based Code Translation and Repair Across Programming Languages
Vera Kowalczuk, Oliver Weißl, Severin Kacianka +1
Large Language Models (LLMs) pre-trained on expansive text and code corpora have revealed promising code generation abilities and have attracted increasing attention in code transl…
Latent Regularization in Generative Test Input Generation
Giorgi Merabishvili, Oliver Weißl, Andrea Stocco
This study investigates the impact of regularization of latent spaces through truncation on the quality of generated test inputs for deep learning classifiers. We evaluate this eff…
Feature-Aware Test Generation for Deep Learning Models
Xingcheng Chen, Oliver Weissl, Andrea Stocco
As deep learning models are widely used in software systems, test generation plays a crucial role in assessing the quality of such models before deployment. To date, the most advan…
Targeted Deep Learning System Boundary Testing
Oliver Weißl, Amr Abdellatif, Xingcheng Chen +4
Evaluating the behavioral boundaries of deep learning (DL) systems is crucial for understanding their reliability across diverse, unseen inputs. Existing solutions fall short as th…