SOURCE-LINKED INTELLIGENCE
Type-IV Code Clone Detection via Layer-Wise Non-Contrastive Representation Learning
Software clones are fragments of code that are similar or functionally equivalent to each other. They pose significant challenges for maintenance, refactoring, and bug detection. Detecting Type-IV clones, which are semantically equivalent but may differ syntactically, is particularly difficult for traditional token- or syntax-based methods. Recent machine learning approaches rely on contrastive learning, which requires careful negative sampling and can introduce bias. In this paper, we propose LWVIC4Code, a non-contrastive representation learning approach specifically designed for Type-IV clon
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T15:42:06.000Z
First collected: 2026-09-20T08:40:59.508Z. This is not the publication date.