Reducing false alarms in software defect prediction by decision threshold optimization

2009 3rd International Symposium on Empirical Software Engineering and Measurement, ESEM 2009

Volumn , Issue , 2009, Pages 477-480

  Tosun, Ayşe ^a   Bener, Ayşe ^a  

^a BOGAZICI UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

BAYES CLASSIFIER; CLASS DISTRIBUTIONS; DECISION THRESHOLD; DEFECT-FREE; FALSE ALARMS; MISCLASSIFICATION COSTS; OPTIMUM THRESHOLD; PROBABILITY OF DETECTION; ROC ANALYSIS; SOFTWARE DATA; SOFTWARE DEFECT PREDICTION; SOFTWARE DEFECTS;

COMMUNICATION CHANNELS (INFORMATION THEORY); DEFECTS; ERRORS; OPTIMIZATION;

COMPUTER SOFTWARE;

EID: 72449149627     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ESEM.2009.5316006     Document Type: Conference Paper

References (13)

1. T. Fawcett, "An Introduction to ROC Analysis", Pattern Recognition Letters, vol. 27, issue 8, 2006, pp. 861-874.
2. T. Menzies, J. Greenwald, A. Frank, "Data mining static code attributes to learn defect predictors", IEEE Transactions on Software Engineering vol. 33, issue 1, pp. 2-13, 2007.
3. A. Tosun, B. Turhan, A. Bener, "Ensemble of software defect predictors: a case study", Proc. ESEM, October 2008, pp. 318-320.
4. R. Moser, W. Pedrycz, G. Succi, "A comparative analysis of the efficiency of change metrics and static code attributes for defect prediction", Proc. ICSE, 2008, pp. 181-190.
5. T. Boetticher, T. Menzies, T. Ostrand, "Promise repository of empirical software engineering data" http://promisedata.org/ repository (2007) West Virginia University, Department of Computer Science.
6. B. Turhan, A. Bener, T. Menzies, "Nearest neighbor sampling for cross company defect predictors", (abstract only), Proc. DEFECTS, 2008, p. 26.
7. Y. Kamei, A. Monden, S. Matsumoto, T. Kakimoto, K. Matsumoto, "The effects of over and under sampling on fault-prone module detection", Proc. ESEM, 2007, pp. 196-204.
8. A.M. Maloof, " Learning when data sets are imbalanced and when costs are unequal and unknown" Workshop on Learning from Imbalanced Data Sets, 2003.
9. S. Lessmann, B. Baesens, C. Mues, S. Pietsch, "Benchmarking classification models for software defect prediction: A proposed framework and novel findings", IEEE Trans. on Software Engineering, vol. 34, 2008, pp. 485-496.
10. F. Provost, "Machine learning from imbalanced data sets 101", Proc. Working Notes AAAI00 Workshop Learning from Imbalanced Data Sets, 2000, pp. 1-3.
11. Alpaydin, E., "Intoduction to Machine Learning", MIT Press, October 2004.
12. B. Turhan, T., Menzies, A. Bener, J. Distefano, "On the Relative Value of Cross-company and Within-Company Data for Defect Prediction", Empirical Software Engineering Journal, 2009, in print. DOI 10.1007/s10664-008- 9103-7.
13. C. K. Chow, "On optimum recognition error and reject tradeoff", IEEE Transactions on Information Theory, volume 16, 1970, pp. 41-46.