Software fault prediction using data mining, machine learning and deep learning techniques: A systematic literature review
Software fault/defect prediction assists software developers to identify faulty constructs, such
as modules or classes, early in the software development life cycle. There are data mining …
as modules or classes, early in the software development life cycle. There are data mining …
A systematic review of machine learning techniques for software fault prediction
R Malhotra - Applied Soft Computing, 2015 - Elsevier
Background Software fault prediction is the process of developing models that can be used
by the software practitioners in the early phases of software development life cycle for …
by the software practitioners in the early phases of software development life cycle for …
Machine learning based methods for software fault prediction: A survey
SK Pandey, RB Mishra, AK Tripathi - Expert Systems with Applications, 2021 - Elsevier
Several prediction approaches are contained in the arena of software engineering such as
prediction of effort, security, quality, fault, cost, and re-usability. All these prediction …
prediction of effort, security, quality, fault, cost, and re-usability. All these prediction …
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 …
Software fault prediction metrics: A systematic literature review
CONTEXT: Software metrics may be used in fault prediction models to improve software
quality by predicting fault location. OBJECTIVE: This paper aims to identify software metrics …
quality by predicting fault location. OBJECTIVE: This paper aims to identify software metrics …
Local versus global lessons for defect prediction and effort estimation
Existing research is unclear on how to generate lessons learned for defect prediction and
effort estimation. Should we seek lessons that are global to multiple projects or just local to …
effort estimation. Should we seek lessons that are global to multiple projects or just local to …
[PDF][PDF] Software bug prediction using machine learning approach
Software Bug Prediction (SBP) is an important issue in software development and
maintenance processes, which concerns with the overall of software successes. This is …
maintenance processes, which concerns with the overall of software successes. This is …
A feature dependent Naive Bayes approach and its application to the software defect prediction problem
Naive Bayes is one of the most widely used algorithms in classification problems because of
its simplicity, effectiveness, and robustness. It is suitable for many learning scenarios, such …
its simplicity, effectiveness, and robustness. It is suitable for many learning scenarios, such …
Value-cognitive boosting with a support vector machine for cross-project defect prediction
It is well-known that software defect prediction is one of the most important tasks for software
quality improvement. The use of defect predictors allows test engineers to focus on defective …
quality improvement. The use of defect predictors allows test engineers to focus on defective …
A transfer cost-sensitive boosting approach for cross-project defect prediction
Software defect prediction has been regarded as one of the crucial tasks to improve software
quality by effectively allocating valuable resources to fault-prone modules. It is necessary to …
quality by effectively allocating valuable resources to fault-prone modules. It is necessary to …