A graph based bug classifier using the dgl library and DeepBugs dataset
-
Updated
Oct 25, 2021 - Python
A graph based bug classifier using the dgl library and DeepBugs dataset
Neural Data-Flow Analysis: A tool for solving program-related tasks which involve data-flow analysis using deep neural networks
VSCode Extension of Type4Py
Extracts code2seq compatible datasets from PHP source files.
[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
Code and data for "Impact of Evaluation Methodologies on Code Summarization" in ACL 2022.
A graph based bug classifier using the dgl library and DeepBugs dataset
Set of PyTorch modules for developing and evaluating different algorithms for embedding trees.
[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
Fixes Java syntax errors with LSTM neural networks! [proof-of-concept]
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.
Tree-based Autofolding Software Summarization Algorithm
ComPy-Learn is a framework for exploring program representations for ML4CODE tasks.
A Tool for Mining Rich Abstract Syntax Trees from Code
PyTorch's implementation of the code2seq model.
Repository for the code of the "A Convolutional Attention Network for Extreme Summarization of Source Code" paper
Add a description, image, and links to the ml4code topic page so that developers can more easily learn about it.
To associate your repository with the ml4code topic, visit your repo's landing page and select "manage topics."