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Found 3 papers, 0 papers with code
CONCORD: Towards a DSL for Configurable Graph Code Representation
CONCORD will help researchers a) create and experiment with customizable graph-based code representations for different software engineering tasks involving DL, b) reduce the engineering work to generate graph representations, c) address the issue of scalability in GNN models, and d) enhance the reproducibility of experiments in research through a standardized approach to code representation and analysis.
Naturalness of Attention: Revisiting Attention in Code Language Models
Language models for code such as CodeBERT offer the capability to learn advanced source code representation, but their opacity poses barriers to understanding of captured properties.
DACOS-A Manually Annotated Dataset of Code Smells
Researchers apply machine-learning techniques for code smell detection to counter the subjectivity of many code smells.
