Repository for the code of the "A Convolutional Attention Network for Extreme Summarization of Source Code" paper
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Updated
Jul 19, 2016 - HTML
Repository for the code of the "A Convolutional Attention Network for Extreme Summarization of Source Code" paper
Tree-based Autofolding Software Summarization Algorithm
Implementation of 'A Convolutional Attention Network for Extreme Summarization of Source Code' in PyTorch using TorchText
Extracts code2seq compatible datasets from PHP source files.
A graph based bug classifier using the dgl library and DeepBugs dataset
A graph based bug classifier using the dgl library and DeepBugs dataset
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
Set of PyTorch modules for developing and evaluating different algorithms for embedding trees.
VSCode Extension of Type4Py
Implementation of the paper "Language-agnostic representation learning of source code from structure and context".
Code and data for "Impact of Evaluation Methodologies on Code Summarization" in ACL 2022.
PyTorch's implementation of the code2seq model.
[SANER 2023] "CLAWSAT: Towards Both Robust and Accurate Code Models" by Jinghan Jia*, Shashank Srikant*, Tamara Mitrovska, Chuang Gan, Shiyu Chang, Sijia Liu, Una-May O'Reilly
A Tool for Mining Rich Abstract Syntax Trees from Code
ComPy-Learn is a framework for exploring program representations for ML4CODE tasks.
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.
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