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Found 5 papers, 5 papers with code
Improved Automatic Summarization of Subroutines via Attention to File Context
In this paper, we present an approach that models the file context of subroutines (i. e. other subroutines in the same file) and uses an attention mechanism to find words and concepts to use in summaries.
Software Engineering
Improved Code Summarization via a Graph Neural Network
The first approaches to use structural information flattened the AST into a sequence.
Recommendations for Datasets for Source Code Summarization
The main use for these descriptions is in software documentation e. g. the one-sentence Java method descriptions in JavaDocs.
A Neural Model for Generating Natural Language Summaries of Program Subroutines
In this paper, we present a neural model that combines words from code with code structure from an AST.
Software Engineering
Adapting Neural Text Classification for Improved Software Categorization
Software Categorization is the task of organizing software into groups that broadly describe the behavior of the software, such as "editors" or "science."
