Predict the probability of various defects on steel plates.
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Updated
Mar 20, 2024 - Jupyter Notebook
Predict the probability of various defects on steel plates.
DEPTs: Parameter tuning for software fault prediction with different variants of differential evolution *** Parameter tuners for software analytics problems ***
An implementation of the SZZ algorithm, i.e., an approach to identify bug-introducing commits.
Defect prediction in Softwares. The Metrics Data Program dataset provided by NASA has been used.
Weldright -Techfest repository
Code of Master's thesis Machine Learning for Interactive Performance Prediction
a project about software prediction
Appendix of paper "Within-Project Defect Prediction of Infrastructure-as-Code Using Product and Process Metrics" accepted at Transactions on Software Engineering.
A fuzzy TOPSIS implementation and its usage for selecting a software defect prediction method
极快速微分催化排序,世界最快的排序算法,The Top Sort 20200317
Defect prediction guided search-based software testing (SBST-DPG)
An offline crystal library, which includes about tens of thousand structure calculated by VASP.
The RADON defect predictor for IaC based on the Scikit-learn Python framework
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.
An implementation of the SZZ algorithm, i.e., an approach to identify bug-introducing commits.
Replication package for Software Defect Prediction Using Rich Contextualized Language Use Vectors
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).
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