Learning from Examples: Generation and Evaluation of Decision Trees for Software Resource Analysis
IEEE Transactions on Software Engineering - Special Issue on Artificial Intelligence in Software Applications
A sequential algorithm for training text classifiers
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Selected papers of the sixth annual Oregon workshop on Software metrics
A Validation of Object-Oriented Design Metrics as Quality Indicators
IEEE Transactions on Software Engineering
Predicting Fault-Prone Software Modules in Telephone Switches
IEEE Transactions on Software Engineering
Machine Learning for the Detection of Oil Spills in Satellite Radar Images
Machine Learning - Special issue on applications of machine learning and the knowledge discovery process
Comparing case-based reasoning classifiers for predicting high risk software components
Journal of Systems and Software
Machine Learning
Early Risk-Management by Identification of Fault-prone Modules
Empirical Software Engineering
Combining and Adapting Software Quality Predictive Models by Genetic Algorithms
Proceedings of the 17th IEEE international conference on Automated software engineering
Tree-Based Software Quality Estimation Models For Fault Prediction
METRICS '02 Proceedings of the 8th International Symposium on Software Metrics
Predicting Fault-Prone Modules with Case-Based Reasoning
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
METRICS '03 Proceedings of the 9th International Symposium on Software Metrics
Robust Prediction of Fault-Proneness by Random Forests
ISSRE '04 Proceedings of the 15th International Symposium on Software Reliability Engineering
Comparison of Non-Parametric Methods for Assessing Classifier Performance in Terms of ROC Parameters
AIPR '04 Proceedings of the 33rd Applied Imagery Pattern Recognition Workshop
Predicting the Location and Number of Faults in Large Software Systems
IEEE Transactions on Software Engineering
Nearest neighbor sampling for better defect prediction
PROMISE '05 Proceedings of the 2005 workshop on Predictor models in software engineering
Empirical Assessment of Machine Learning based Software Defect Prediction Techniques
WORDS '05 Proceedings of the 10th IEEE International Workshop on Object-Oriented Real-Time Dependable Systems
Building Defect Prediction Models in Practice
IEEE Software
ROC confidence bands: an empirical evaluation
ICML '05 Proceedings of the 22nd international conference on Machine learning
The relationship between Precision-Recall and ROC curves
ICML '06 Proceedings of the 23rd international conference on Machine learning
Predicting fault-prone components in a java legacy system
Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Data Mining Static Code Attributes to Learn Defect Predictors
IEEE Transactions on Software Engineering
Comments on "Data Mining Static Code Attributes to Learn Defect Predictors"
IEEE Transactions on Software Engineering
An empirical investigation of tree ensembles in biometrics and bioinformatics research
An empirical investigation of tree ensembles in biometrics and bioinformatics research
Revisiting the evaluation of defect prediction models
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
Misclassification cost-sensitive fault prediction models
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
On the ability of complexity metrics to predict fault-prone classes in object-oriented systems
Journal of Systems and Software
Comparing the effectiveness of several modeling methods for fault prediction
Empirical Software Engineering
Variance analysis in software fault prediction models
ISSRE'09 Proceedings of the 20th IEEE international conference on software reliability engineering
Defect prediction from static code features: current results, limitations, new approaches
Automated Software Engineering
Replication of defect prediction studies: problems, pitfalls and recommendations
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
Towards a software failure cost impact model for the customer: an analysis of an open source product
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
An iterative semi-supervised approach to software fault prediction
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
An investigation on the feasibility of cross-project defect prediction
Automated Software Engineering
On the dataset shift problem in software engineering prediction models
Empirical Software Engineering
Using a shallow linguistic kernel for drug-drug interaction extraction
Journal of Biomedical Informatics
Evaluating defect prediction approaches: a benchmark and an extensive comparison
Empirical Software Engineering
Proceedings of the 8th International Conference on Predictive Models in Software Engineering
Failure prediction based on log files using Random Indexing and Support Vector Machines
Journal of Systems and Software
Better cross company defect prediction
Proceedings of the 10th Working Conference on Mining Software Repositories
Neurocomputing
Software defect prediction using relational association rule mining
Information Sciences: an International Journal
DConfusion: a technique to allow cross study performance evaluation of fault prediction studies
Automated Software Engineering
Computational Intelligence and Neuroscience
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Many statistical techniques have been proposed to predict fault-proneness of program modules in software engineering. Choosing the "best" candidate among many available models involves performance assessment and detailed comparison, but these comparisons are not simple due to the applicability of varying performance measures. Classifying a software module as fault-prone implies the application of some verification activities, thus adding to the development cost. Misclassifying a module as fault free carries the risk of system failure, also associated with cost implications. Methodologies for precise evaluation of fault prediction models should be at the core of empirical software engineering research, but have attracted sporadic attention. In this paper, we overview model evaluation techniques. In addition to many techniques that have been used in software engineering studies before, we introduce and discuss the merits of cost curves. Using the data from a public repository, our study demonstrates the strengths and weaknesses of performance evaluation techniques and points to a conclusion that the selection of the "best" model cannot be made without considering project cost characteristics, which are specific in each development environment.