2 papers
cs.SE2026
PLMGH: What Matters in PLM-GNN Hybrids for Code Classification and Vulnerability Detection
Mohamed Taoufik Kaouthar El Idrissi, Edward Zulkoski, Mohammad Hamdaqa
Code understanding models increasingly rely on pretrained language models (PLMs) and graph neural networks (GNNs), which capture complementary semantic and structural information.…
cs.SE2025
PRIMG : Efficient LLM-driven Test Generation Using Mutant Prioritization
Mohamed Salah Bouafif, Mohammad Hamdaqa, Edward Zulkoski
Mutation testing is a widely recognized technique for assessing and enhancing the effectiveness of software test suites by introducing deliberate code mutations. However, its appli…