C4.5: programs for machine learning
C4.5: programs for machine learning
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
Evaluating predictive quality models derived from software measures: lessons learned
Journal of Systems and Software
A Critique of Software Defect Prediction Models
IEEE Transactions on Software Engineering
Predicting Fault Incidence Using Software Change History
IEEE Transactions on Software Engineering
Quantitative Analysis of Faults and Failures in a Complex Software System
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
Cost-Sensitive Boosting In Software Quality Modeling
HASE '02 Proceedings of the 7th IEEE International Symposium on High Assurance Systems Engineering
What We Have Learned About Fighting Defects
METRICS '02 Proceedings of the 8th International Symposium on Software Metrics
CVS Release History Data for Detecting Logical Couplings
IWPSE '03 Proceedings of the 6th International Workshop on Principles of Software Evolution
Benchmarking Attribute Selection Techniques for Discrete Class Data Mining
IEEE Transactions on Knowledge and Data Engineering
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Use of relative code churn measures to predict system defect density
Proceedings of the 27th international conference on Software engineering
Predicting the Location and Number of Faults in Large Software Systems
IEEE Transactions on Software Engineering
The Top Ten List: Dynamic Fault Prediction
ICSM '05 Proceedings of the 21st IEEE International Conference on Software Maintenance
Mining metrics to predict component failures
Proceedings of the 28th international conference on Software engineering
Predicting defect densities in source code files with decision tree learners
Proceedings of the 2006 international workshop on Mining software repositories
Looking for bugs in all the right places
Proceedings of the 2006 international symposium on Software testing and analysis
Predicting component failures at design time
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)
Data Mining Static Code Attributes to Learn Defect Predictors
IEEE Transactions on Software Engineering
Empirical Analysis of Object-Oriented Design Metrics for Predicting High and Low Severity Faults
IEEE Transactions on Software Engineering
Using Developer Information as a Factor for Fault Prediction
PROMISE '07 Proceedings of the Third International Workshop on Predictor Models in Software Engineering
Predicting Defects for Eclipse
PROMISE '07 Proceedings of the Third International Workshop on Predictor Models in Software Engineering
EQ-mine: predicting short-term defects for software evolution
FASE'07 Proceedings of the 10th international conference on Fundamental approaches to software engineering
Analysis of the reliability of a subset of change metrics for defect prediction
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
Can developer-module networks predict failures?
Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering
Predicting faults using the complexity of code changes
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Merits of using repository metrics in defect prediction for open source projects
FLOSS '09 Proceedings of the 2009 ICSE Workshop on Emerging Trends in Free/Libre/Open Source Software Research and Development
Fair and balanced?: bias in bug-fix datasets
Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
On the relative value of cross-company and within-company data for defect prediction
Empirical Software Engineering
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
Reducing false alarms in software defect prediction by decision threshold optimization
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
Recurring bug fixes in object-oriented programs
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
Detection of recurring software vulnerabilities
Proceedings of the IEEE/ACM international conference on Automated software engineering
Using traits of web macro scripts to predict reuse
Journal of Visual Languages and Computing
An analysis of developer metrics for fault prediction
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
Software metrics reduction for fault-proneness prediction of software modules
NPC'10 Proceedings of the 2010 IFIP international conference on Network and parallel computing
Requirements attributes to predict requirements related defects
Proceedings of the 2010 Conference of the Center for Advanced Studies on Collaborative Research
Design evolution metrics for defect prediction in object oriented systems
Empirical Software Engineering
By no means: a study on aggregating software metrics
Proceedings of the 2nd International Workshop on Emerging Trends in Software Metrics
Comparing fine-grained source code changes and code churn for bug prediction
Proceedings of the 8th Working Conference on Mining Software Repositories
Security versus performance bugs: a case study on Firefox
Proceedings of the 8th Working Conference on Mining Software Repositories
Software defect prediction based on source code metrics time series
Transactions on rough sets XIII
Dealing with noise in defect prediction
Proceedings of the 33rd International Conference on Software Engineering
Topic-based defect prediction (NIER track)
Proceedings of the 33rd International Conference on Software Engineering
Exploring, exposing, and exploiting emails to include human factors in software engineering
Proceedings of the 33rd International Conference on Software Engineering
Defect prediction using social network analysis on issue repositories
Proceedings of the 2011 International Conference on Software and Systems Process
Detection of malicious applications on Android OS
IWCF'10 Proceedings of the 4th international conference on Computational forensics
Are change metrics good predictors for an evolving software product line?
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
Using the gini coefficient for bug prediction in eclipse
Proceedings of the 12th International Workshop on Principles of Software Evolution and the 7th annual ERCIM Workshop on Software Evolution
High-impact defects: a study of breakage and surprise defects
Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
Micro interaction metrics for defect prediction
Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
A framework for defect prediction in specific software project contexts
CEE-SET'08 Proceedings of the Third IFIP TC 2 Central and East European conference on Software engineering techniques
An investigation on the feasibility of cross-project defect prediction
Automated Software Engineering
Are popular classes more defect prone?
FASE'10 Proceedings of the 13th international conference on Fundamental Approaches to Software Engineering
Finding the merits and drawbacks of software resources from comments
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
A topic-based approach for narrowing the search space of buggy files from a bug report
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
Evaluating defect prediction approaches: a benchmark and an extensive comparison
Empirical Software Engineering
Controversy Corner: On the relationship between comment update practices and Software Bugs
Journal of Systems and Software
Bug prediction based on fine-grained module histories
Proceedings of the 34th International Conference on Software Engineering
Defect, defect, defect: defect prediction 2.0
Proceedings of the 8th International Conference on Predictive Models in Software Engineering
Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement
Recalling the "imprecision" of cross-project defect prediction
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
An industrial study on the risk of software changes
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
Proceedings of the 2013 International Conference on Software Engineering
How, and why, process metrics are better
Proceedings of the 2013 International Conference on Software Engineering
Sample size vs. bias in defect prediction
Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering
Training data selection for cross-project defect prediction
Proceedings of the 9th International Conference on Predictive Models in Software Engineering
Is lines of code a good measure of effort in effort-aware models?
Information and Software Technology
A survey of computational intelligence approaches for software reliability prediction
ACM SIGSOFT Software Engineering Notes
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In this paper we present a comparative analysis of the predictive power of two different sets of metrics for defect prediction. We choose one set of product related and one set of process related software metrics and use them for classifying Java files of the Eclipse project as defective respective defect-free. Classification models are built using three common machine learners: logistic regression, Naïve Bayes, and decision trees. To allow different costs for prediction errors we perform cost-sensitive classification, which proves to be very successful: 75% percentage of correctly classified files, a recall of 80%, and a false positive rate