1 citations · 1 across the 9 of their papers we have counts for
19 papers
When Knowledge Changes: Metamorphic Testing of RAG Systems with Mutations
Jinhan Kim, Samuele Pasini, Paolo Tonella
Retrieval-Augmented Generation (RAG)-based LLM systems rely on external document corpora that can evolve and change over time. However, current evaluation methodologies (e.g., RAGA…
Testing Retrieval-Augmented Generation Systems with Chunk Coverage
Jinhan Kim, Samuele Pasini, Paolo Tonella
Retrieval-Augmented Generation (RAG)-based systems\footnote{For brevity, RAG-based systems are referred to as RAG systems throughout this paper.} are increasingly deployed in high-…
Dynamic Deception: When Pedestrians Team Up to Fool Autonomous Cars
Masoud Jamshidiyan Tehrani, Marco Gabriel, Jinhan Kim +1
Many adversarial attacks on autonomous-driving perception models fail to cause system-level failures once deployed in a full driving stack. The main reason for such ineffectiveness…
Revisiting "Revisiting Neuron Coverage for DNN Testing: A Layer-Wise and Distribution-Aware Criterion": A Critical Review and Implications on DNN Coverage Testing
Jinhan Kim, Nargiz Humbatova, Gunel Jahangirova +2
We present a critical review of Neural Coverage (NLC), a state-of-the-art DNN coverage criterion by Yuan et al. at ICSE 2023. While NLC proposes to satisfy eight design requirement…
Bridging Research and Practice in Simulation-based Testing of Industrial Robot Navigation Systems
Sajad Khatiri, Francisco Eli Vina Barrientos, Maximilian Wulf +2
Ensuring robust robotic navigation in dynamic environments is a key challenge, as traditional testing methods often struggle to cover the full spectrum of operational requirements.…
TopoMap: A Feature-based Semantic Discriminator of the Topographical Regions in the Test Input Space
Gianmarco De Vita, Nargiz Humbatova, Paolo Tonella
Testing Deep Learning (DL)-based systems is an open challenge. Although it is relatively easy to find inputs that cause a DL model to misbehave, the grouping of inputs by features…