Design complexity measurement and testing
Communications of the ACM
A practical approach to feature selection
ML92 Proceedings of the ninth international workshop on Machine learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Estimating attributes: analysis and extensions of RELIEF
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
An investigation into coupling measures for C++
ICSE '97 Proceedings of the 19th international conference on Software engineering
Explora: a multipattern and multistrategy discovery assistant
Advances in knowledge discovery and data mining
Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
A Critique of Software Defect Prediction Models
IEEE Transactions on Software Engineering
Experimentation in software engineering: an introduction
Experimentation in software engineering: an introduction
Journal of Systems and Software - Special issue on Evaluation and assessment in software engineering
Comparing Software Prediction Techniques Using Simulation
IEEE Transactions on Software Engineering - Special section on the seventh international software metrics symposium
Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
Machine Learning
An empirical evaluation of fault-proneness models
Proceedings of the 24th International Conference on Software Engineering
Detecting Group Differences: Mining Contrast Sets
Data Mining and Knowledge Discovery
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
Machine Learning
An Algorithm for Multi-relational Discovery of Subgroups
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Thresholds for Object-Oriented Measures
ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
Analogy-Based Practical Classification Rules for Software Quality Estimation
Empirical Software Engineering
Benchmarking Attribute Selection Techniques for Discrete Class Data Mining
IEEE Transactions on Knowledge and Data Engineering
Comparative Assessment of Software Quality Classification Techniques: An Empirical Case Study
Empirical Software Engineering
Subgroup Discovery with CN2-SD
The Journal of Machine Learning Research
Reliability and Validity in Comparative Studies of Software Prediction Models
IEEE Transactions on Software Engineering
Building Defect Prediction Models in Practice
IEEE Software
Empirical Validation of Object-Oriented Metrics on Open Source Software for Fault Prediction
IEEE Transactions on Software Engineering
Software Defect Association Mining and Defect Correction Effort Prediction
IEEE Transactions on Software Engineering
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Predicting fault-prone components in a java legacy system
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Data Mining Static Code Attributes to Learn Defect Predictors
IEEE Transactions on Software Engineering
Predicting Defects for Eclipse
PROMISE '07 Proceedings of the Third International Workshop on Predictor Models in Software Engineering
IEEE Transactions on Software Engineering
Comments on "Data Mining Static Code Attributes to Learn Defect Predictors"
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
Software Defect Prediction Using Regression via Classification
AICCSA '06 Proceedings of the IEEE International Conference on Computer Systems and Applications
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
Comparing software metrics tools
ISSTA '08 Proceedings of the 2008 international symposium on Software testing and analysis
IEEE Transactions on Software Engineering
Review: A systematic review of software fault prediction studies
Expert Systems with Applications: An International Journal
Revisiting the evaluation of defect prediction models
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
A hybrid heuristic approach to optimize rule-based software quality estimation models
Information and Software Technology
The Journal of Machine Learning Research
Data Mining for Software Engineering
Computer
Expert-guided subgroup discovery: methodology and application
Journal of Artificial Intelligence Research
Journal of Systems and Software
Empirical validation of object-oriented metrics for predicting fault proneness models
Software Quality Control
Finding software metrics threshold values using ROC curves
Journal of Software Maintenance and Evolution: Research and Practice
Defect prediction from static code features: current results, limitations, new approaches
Automated Software Engineering
Information and Software Technology
Effort-Aware Defect Prediction Models
CSMR '10 Proceedings of the 2010 14th European Conference on Software Maintenance and Reengineering
Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Practical Machine Learning Tools and Techniques
Data mining in software engineering
Intelligent Data Analysis
An overview on subgroup discovery: foundations and applications
Knowledge and Information Systems
User preferences based software defect detection algorithms selection using MCDM
Information Sciences: an International Journal
Searching for rules to detect defective modules: A subgroup discovery approach
Information Sciences: an International Journal
Evaluating defect prediction approaches: a benchmark and an extensive comparison
Empirical Software Engineering
IEEE Transactions on Neural Networks
A Systematic Literature Review on Fault Prediction Performance in Software Engineering
IEEE Transactions on Software Engineering
Local versus Global Lessons for Defect Prediction and Effort Estimation
IEEE Transactions on Software Engineering
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Context: Although many papers have been published on software defect prediction techniques, machine learning approaches have yet to be fully explored. Objective: In this paper we suggest using a descriptive approach for defect prediction rather than the precise classification techniques that are usually adopted. This allows us to characterise defective modules with simple rules that can easily be applied by practitioners and deliver a practical (or engineering) approach rather than a highly accurate result. Method: We describe two well-known subgroup discovery algorithms, the SD algorithm and the CN2-SD algorithm to obtain rules that identify defect prone modules. The empirical work is performed with publicly available datasets from the Promise repository and object-oriented metrics from an Eclipse repository related to defect prediction. Subgroup discovery algorithms mitigate against characteristics of datasets that hinder the applicability of classification algorithms and so remove the need for preprocessing techniques. Results: The results show that the generated rules can be used to guide testing effort in order to improve the quality of software development projects. Such rules can indicate metrics, their threshold values and relationships between metrics of defective modules. Conclusions: The induced rules are simple to use and easy to understand as they provide a description rather than a complete classification of the whole dataset. Thus this paper represents an engineering approach to defect prediction, i.e., an approach which is useful in practice, easily understandable and can be applied by practitioners.