A systematic literature review and meta-analysis on cross project defect prediction
Background: Cross project defect prediction (CPDP) recently gained considerable attention,
yet there are no systematic efforts to analyse existing empirical evidence. Objective: To …
yet there are no systematic efforts to analyse existing empirical evidence. Objective: To …
A systematic literature review on fault prediction performance in software engineering
Background: The accurate prediction of where faults are likely to occur in code can help
direct test effort, reduce costs, and improve the quality of software. Objective: We investigate …
direct test effort, reduce costs, and improve the quality of software. Objective: We investigate …
[ΒΙΒΛΙΟ][B] Feature engineering for machine learning and data analytics
Feature engineering plays a vital role in big data analytics. Machine learning and data
mining algorithms cannot work without data. Little can be achieved if there are few features …
mining algorithms cannot work without data. Little can be achieved if there are few features …
Deep semantic feature learning for software defect prediction
Software defect prediction, which predicts defective code regions, can assist developers in
finding bugs and prioritizing their testing efforts. Traditional defect prediction features often …
finding bugs and prioritizing their testing efforts. Traditional defect prediction features often …
Scancomplete: Large-scale scene completion and semantic segmentation for 3d scans
We introduce ScanComplete, a novel data-driven approach for taking an incomplete 3D
scan of a scene as input and predicting a complete 3D model along with per-voxel semantic …
scan of a scene as input and predicting a complete 3D model along with per-voxel semantic …
VUDENC: vulnerability detection with deep learning on a natural codebase for Python
Context: Identifying potential vulnerable code is important to improve the security of our
software systems. However, the manual detection of software vulnerabilities requires expert …
software systems. However, the manual detection of software vulnerabilities requires expert …
Heterogeneous defect prediction
Software defect prediction is one of the most active research areas in software engineering.
We can build a prediction model with defect data collected from a software project and …
We can build a prediction model with defect data collected from a software project and …
Deepjit: an end-to-end deep learning framework for just-in-time defect prediction
Software quality assurance efforts often focus on identifying defective code. To find likely
defective code early, change-level defect prediction-aka. Just-In-Time (JIT) defect prediction …
defective code early, change-level defect prediction-aka. Just-In-Time (JIT) defect prediction …
Deep learning for just-in-time defect prediction
Defect prediction is a very meaningful topic, particularly at change-level. Change-level
defect prediction, which is also referred as just-in-time defect prediction, could not only …
defect prediction, which is also referred as just-in-time defect prediction, could not only …
A large-scale empirical study of just-in-time quality assurance
Defect prediction models are a well-known technique for identifying defect-prone files or
packages such that practitioners can allocate their quality assurance efforts (eg, testing and …
packages such that practitioners can allocate their quality assurance efforts (eg, testing and …