An implementation of the SZZ algorithm, i.e., an approach to identify bug-introducing commits.
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Updated
Oct 4, 2023 - Java
An implementation of the SZZ algorithm, i.e., an approach to identify bug-introducing commits.
This project is about detecting defects on steel surface using Unet. The dataset used for this project is the NEU-DET database.
we proposed a software defect predictive development models using machine learning techniques that can enable the software to continue its projected task.
ICSE'18: Tuning Smote
Epsilon domination
A ML model that predicts the number of bugs that might occur while reaching the QA Stage.
Mahakil Code
An implementation of the SZZ algorithm, i.e., an approach to identify bug-introducing commits.
Defect prediction of java projects using neural networks.
Tuning of parameters of ML algorithms to optimise precision/f-score for fault detection in softwares
Software measure datasets of software network structure for defect prediction
Appendix of paper "Within-Project Defect Prediction of Infrastructure-as-Code Using Product and Process Metrics" accepted at Transactions on Software Engineering.
BUGZY - Automated machine learning model to predict if a git commit is a bug fix. Based on topic modeling and natural language processing, it is built with SVM and Latent Dirichlet Allocation (LDA).
Code of Master's thesis Machine Learning for Interactive Performance Prediction
Replication package for Software Defect Prediction Using Rich Contextualized Language Use Vectors
A fuzzy TOPSIS implementation and its usage for selecting a software defect prediction method
An offline crystal library, which includes about tens of thousand structure calculated by VASP.
Defect prediction guided search-based software testing (SBST-DPG)
极快速微分催化排序,世界最快的排序算法,The Top Sort 20200317
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