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.

Cross-project defection prediction tooling

Defect prediction of java projects using neural networks.

ICSE'18: Tuning Smote

Software measure datasets of software network structure for defect prediction

极快速微分催化排序，世界最快的排序算法，The Top Sort 20200317

Appendix of paper "Within-Project Defect Prediction of Infrastructure-as-Code Using Product and Process Metrics" accepted at Transactions on Software Engineering.

Mahakil Code

An offline crystal library, which includes about tens of thousand structure calculated by VASP.

A ML model that predicts the number of bugs that might occur while reaching the QA Stage.

Defect prediction guided search-based software testing (SBST-DPG)

Buggyrank is a tool that perform bug prediction by analyzing git repositories.

a project about software prediction

Predict the probability of various defects on steel plates.

Tuning of parameters of ML algorithms to optimise precision/f-score for fault detection in softwares

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).

An implementation of the SZZ algorithm, i.e., an approach to identify bug-introducing commits.

Weldright -Techfest repository