SEMERU-Lab

ACER

ACER is an AST-based Callgraph Generator Development Framework

ds4se

Data Science for Software Engineering (ds4se) is an academic initiative to perform exploratory and causal inference analysis on software engineering artifacts and metadata. Data Management, Analysis, and Benchmarking for DL and Traceability.

galeras-benchmark

Benchmarking Causl Study to Interpret Large Language Models for Source Code

CodeSyntaxConcept

Describing and Evaluating Semantic Capabilities for SOTA Code Models.

CausalSE

Causal Interpretability for SE

SyntaxEval

docker-container-example

galeras-dataset

Curated datasets extractor and API

SemeruGuidelines

Semeru Data and Machine Guidelines

csci-435_what_if_tool

Project #3: What-if-tool Code. A Visual Tool for Understanding Machine Learning Models for Software Engineering

SecureReqNet

We present a novel approach, called SecureReqNet, for automatically identifying whether issues in bug or issue tracking systems describe security related content that should be given careful attention. Our approach consists of a two-phase deep learning architecture that operates purely on the natural language descriptions of issues. The first phase of our approach learns high dimensional sentence embeddings from hundreds of thousands of descriptions extracted from software vulnerabilities listed in the CVE database and issue descriptions extracted from open source projects using an unsupervised learning process. The second phase then utilizes this semantic ontology of embeddings to train a deep convolutional neural network capable of predicting whether a given issue contains security- related information.

mlproj_template_deprecated

Machine learning project template based on the awesome nbdev_template

WM-Thesis-Template

This repo holds the latest version of the LaTeX template for writing Theses and Dissertations at the College of William & Mary

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

traceXplainer

A Library for Software Artifact Vectorization, Distance Computation, and Statistical Analysis on vectors.

code

This project contains code specific processing utilities, mostly focused for helping software engineering research with machine learning models for code data.

dl4se

A Systematic Literature Review of Deep Learning in Software Engineering

hephaestus

gpu-jupyter

Leverage the flexibility of Jupyterlab through the power of your NVIDIA GPU to run your code from Tensorflow and Pytorch in collaborative notebooks on the GPU.

big_clone_benchmark_setup

Repo for automatically setting up environment for the Big Clone Benchmark