Learning Semantic Vector Representations of Source Code via a Siamese Neural Network
The abundance of open-source code, coupled with the success of recent advances in deep learning for natural language processing, has given rise to a promising new application of machine learning to source code. In this work, we explore the use of a Siamese recurrent neural network model on Python so...
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26-04-2019
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| Abstract | The abundance of open-source code, coupled with the success of recent
advances in deep learning for natural language processing, has given rise to a
promising new application of machine learning to source code. In this work, we
explore the use of a Siamese recurrent neural network model on Python source
code to create vectors which capture the semantics of code. We evaluate the
quality of embeddings by identifying which problem from a programming
competition the code solves. Our model significantly outperforms a
bag-of-tokens embedding, providing promising results for improving code
embeddings that can be used in future software engineering tasks. |
|---|---|
| AbstractList | The abundance of open-source code, coupled with the success of recent
advances in deep learning for natural language processing, has given rise to a
promising new application of machine learning to source code. In this work, we
explore the use of a Siamese recurrent neural network model on Python source
code to create vectors which capture the semantics of code. We evaluate the
quality of embeddings by identifying which problem from a programming
competition the code solves. Our model significantly outperforms a
bag-of-tokens embedding, providing promising results for improving code
embeddings that can be used in future software engineering tasks. |
| Author | Pence, Eleanor Walczyk, John Ferreira, Guilherme Wehr, David Zhang, Bo Fede, Halley Hughes, Joseph |
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| BackLink | https://doi.org/10.48550/arXiv.1904.11968$$DView paper in arXiv |
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| Snippet | The abundance of open-source code, coupled with the success of recent
advances in deep learning for natural language processing, has given rise to a
promising... |
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| SubjectTerms | Computer Science - Learning Computer Science - Programming Languages Computer Science - Software Engineering Statistics - Machine Learning |
| Title | Learning Semantic Vector Representations of Source Code via a Siamese Neural Network |
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