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LineVul
A Transformer-based Line-Level Vulnerability PredictionVulRepair
VulRepair: A T5-Based Automated Software Vulnerability RepairPyExplainer
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)DeepLineDP
line-level-defect-prediction
A3Test
Rnalytica
Rnalytica: An R package of JIRA defect datasets and tool suites for actionable software analyticsVulExplainer
VulExplainer: A Transformer-based Hierarchical Distillation for Explaining Vulnerability Typestutorial
Software Analytics in Action: A Hands-on Tutorial on Mining, Analyzing, Modelling, and Explaining Software DataVQM
Vision Transformer-Inspired Automated Vulnerability RepairChatGPT4Vul
pycoder
AutoTransform-Replication
gpt2sp
Large-Defect-Prediction-Benchmark
JITLine-replication-package
JIT-defect-models
replication-icse2019
Replication Package: Mining Software Defects: Should We Consider Affected Releases?LLM-for-code-review-automatiton
gpt2sp_webapp
storypoints-changes
This is a replication package for the paper titled "Understanding and Predicting the change of StoryPoints"wiki-admin
SQAPlanner-implementation
paper-writing-guidelines
optimatch
Optimal Transport for Function-Level and Line-Level Vulnerability DetectionD-ACT-Replication-Package
DefectData
The R package DefectData is a collection of software metrics dataset for software engineering researchers.Love Open Source and this site? Check out how you can help us