Comparing case-based reasoning classifiers for predicting high risk software components
Journal of Systems and Software
An Application of Fuzzy Clustering to Software Quality Prediction
ASSET '00 Proceedings of the 3rd IEEE Symposium on Application-Specific Systems and Software Engineering Technology (ASSET'00)
Software Quality Classification Modeling Using The SPRINT Decision Tree Algorithm
ICTAI '02 Proceedings of the 14th IEEE International Conference on Tools with Artificial Intelligence
Application of Neural Networks for Software Quality Prediction Using Object-Oriented Metrics
ICSM '03 Proceedings of the International Conference on Software Maintenance
Learning Weighted Naive Bayes with Accurate Ranking
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Eclipse: Building Commercial-Quality Plug-ins (2nd Edition) (Eclipse)
Eclipse: Building Commercial-Quality Plug-ins (2nd Edition) (Eclipse)
On the Automation of Software Fault Prediction
TAIC-PART '06 Proceedings of the Testing: Academic & Industrial Conference on Practice And Research Techniques
Predicting software defects in varying development lifecycles using Bayesian nets
Information and Software Technology
Object-oriented software fault prediction using neural networks
Information and Software Technology
Journal of Systems and Software
Data Mining Static Code Attributes to Learn Defect Predictors
IEEE Transactions on Software Engineering
Applying machine learning to software fault-proneness prediction
Journal of Systems and Software
Mining software repositories for comprehensible software fault prediction models
Journal of Systems and Software
Predicting defect-prone software modules using support vector machines
Journal of Systems and Software
Implications of ceiling effects in defect predictors
Proceedings of the 4th international workshop on Predictor models in software engineering
A Fault Prediction Model with Limited Fault Data to Improve Test Process
PROFES '08 Proceedings of the 9th international conference on Product-Focused Software Process Improvement
What can fault prediction do for you?
TAP'08 Proceedings of the 2nd international conference on Tests and proofs
Eclipse Rich Client Platform
Identification of defect-prone classes in telecommunication software systems using design metrics
Information Sciences: an International Journal
Software fault prediction with object-oriented metrics based artificial immune recognition system
PROFES'07 Proceedings of the 8th international conference on Product-Focused Software Process Improvement
Exemplar driven development of software product lines
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Despite the amount of effort software engineers have been putting into developing fault prediction models, software fault prediction still poses great challenges. This research using machine learning and statistical techniques has been ongoing for 15years, and yet we still have not had a breakthrough. Unfortunately, none of these prediction models have achieved widespread applicability in the software industry due to a lack of software tools to automate this prediction process. Historical project data, including software faults and a robust software fault prediction tool, can enable quality managers to focus on fault-prone modules. Thus, they can improve the testing process. We developed an Eclipse-based software fault prediction tool for Java programs to simplify the fault prediction process. We also integrated a machine learning algorithm called Naive Bayes into the plug-in because of its proven high-performance for this problem. This article presents a practical view to software fault prediction problem, and it shows how we managed to combine software metrics with software fault data to apply Naive Bayes technique inside an open source platform.