Website for "A Survey of Machine Learning for Big Code and Naturalness"
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Updated
Feb 16, 2023 - CSS
Website for "A Survey of Machine Learning for Big Code and Naturalness"
A curated list of papers, theses, datasets, and tools related to the application of Machine Learning for Software Engineering
Implementation of the paper "Language-agnostic representation learning of source code from structure and context".
Repository for the code of the "A Convolutional Attention Network for Extreme Summarization of Source Code" paper
PyTorch's implementation of the code2seq model.
A Tool for Mining Rich Abstract Syntax Trees from Code
Tree-based Autofolding Software Summarization Algorithm
Set of PyTorch modules for developing and evaluating different algorithms for embedding trees.
Fixes Java syntax errors with LSTM neural networks! [proof-of-concept]
[ICLR 2021] "Generating Adversarial Computer Programs using Optimized Obfuscations" by Shashank Srikant, Sijia Liu, Tamara Mitrovska, Shiyu Chang, Quanfu Fan, Gaoyuan Zhang, and Una-May O'Reilly
ComPy-Learn is a framework for exploring program representations for ML4CODE tasks.
Implementation of 'A Convolutional Attention Network for Extreme Summarization of Source Code' in PyTorch using TorchText
The official repository of "GraphSPD: Graph-Based Security Patch Detection with Enriched Code Semantics". The paper will appear in the IEEE Symposium on Security and Privacy (S&P), San Francisco, CA, May 22-26, 2023.
Code and data for "Impact of Evaluation Methodologies on Code Summarization" in ACL 2022.
VSCode Extension of Type4Py
A graph based bug classifier using the dgl library and DeepBugs dataset
Extracts code2seq compatible datasets from PHP source files.
A graph based bug classifier using the dgl library and DeepBugs dataset
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