Source Code Summarization
37 papers with code • 9 benchmarks • 7 datasets
Code Summarization is a task that tries to comprehend code and automatically generate descriptions directly from the source code.
Source: Improving Automatic Source Code Summarization via Deep Reinforcement Learning
Benchmarks
These leaderboards are used to track progress in Source Code Summarization
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Libraries
Use these libraries to find Source Code Summarization models and implementationsDatasets
CodeSearchNet
StaQC
Latest papers
Assemble Foundation Models for Automatic Code Summarization
jianguda/afm4acs
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Thereby, we propose a flexible and robust approach for automatic code summarization, based on neural models.
Leveraging Unsupervised Learning to Summarize APIs Discussed in Stack Overflow
Automated source code summarization is a task that generates summarized information about the purpose, usage, and--or implementation of methods and classes to support understanding of these code entities.
Modeling Hierarchical Syntax Structure with Triplet Position for Source Code Summarization
gjcexp/codescribe
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ACL ARR November 2021
In this paper, we propose CODESCRIBE to model the hierarchical syntax structure of code by introducing a novel triplet position for code summarization.
GraphSearchNet: Enhancing GNNs via Capturing Global Dependencies for Semantic Code Search
shangqing-liu/graphsearchnet
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Specifically, we propose to construct graphs for the source code and queries with bidirectional GGNN (BiGGNN) to capture the local structural information of the source code and queries.
On the Evaluation of Neural Code Summarization
To achieve a profound understanding of how far we are from solving this problem and provide suggestions to future research, in this paper, we conduct a systematic and in-depth analysis of 5 state-of-the-art neural code summarization models on 6 widely used BLEU variants, 4 pre-processing operations and their combinations, and 3 widely used datasets.
Code to Comment Translation: A Comparative Study on Model Effectiveness & Errors
SageSELab/CodeSumStudy
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ACL (NLP4Prog) 2021
Automated source code summarization is a popular software engineering research topic wherein machine translation models are employed to "translate" code snippets into relevant natural language descriptions.
CoDesc: A Large Code-Description Parallel Dataset
In this study, we present CoDesc -- a large parallel dataset composed of 4. 2 million Java methods and natural language descriptions.
CodeTrans: Towards Cracking the Language of Silicon's Code Through Self-Supervised Deep Learning and High Performance Computing
Simultaneously, the transformer model, especially its combination with transfer learning, has been proven to be a powerful technique for natural language processing tasks.
HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks
liubest/HAConvGNN
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Findings (EMNLP) 2021
Jupyter notebook allows data scientists to write machine learning code together with its documentation in cells.
Project-Level Encoding for Neural Source Code Summarization of Subroutines
aakashba/projcon
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Source code summarization of a subroutine is the task of writing a short, natural language description of that subroutine.
