A curated list of papers, theses, datasets, and tools related to the application of Machine Learning for Software Engineering
Type4Py: Deep Similarity Learning-Based Type Inference for Python
A Tool for Mining Rich Abstract Syntax Trees from Code
PyTorch's implementation of the code2seq model.
TeCo: an ML+Execution model for test completion
[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
CD4Py: Code De-Duplication for Python
Set of PyTorch modules for developing and evaluating different algorithms for embedding trees.
Machine Learning for Source Code Analysis
Pre-training and fine-tuning GNN model on source code
VSCode Extension of Type4Py
This paper explores the idea of using heterogeneous graph neural networks (Het-GNN) to partition old legacy monoliths into candidate microservices. We additionally take membership constraints that come from a subject matter expert who has deep domain knowledge of the application.
Implementing idea from the "Extracting Training Data from Large Language Models" paper on starcoderbase-3b model
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