4 papers
Explanation-Guided Metamorphic Testing of Specialized Language Models: An Empirical Study
Xingcheng Chen, Mehmet Besenk, Andrea Stocco
\head{Background} Task-specialized language models are increasingly integrated into software engineering workflows to support vertical-domain activities such as issue triaging, doc…
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…
XMutant: XAI-based Fuzzing for Deep Learning Systems
Xingcheng Chen, Matteo Biagiola, Vincenzo Riccio +2
Semantic-based test generators are widely used to produce failure-inducing inputs for Deep Learning (DL) systems. They typically generate challenging test inputs by applying random…
Targeted Deep Learning System Boundary Testing
Oliver WeiÃl, 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…