I must not fear. Fear is the mind-killer. Fear is the little-death that brings total obliteration. I will face my fear. I will permit it to pass over me and through me. And when it has gone past I will turn the inner eye to see its path. Where the fear has gone there will be nothing. Only I will remain. [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13]

[14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [?]

References

1. A. G. Koru and H. Liu, “An investigation of the effect of module size on defect prediction using static measures,” in PROMISE ’05: Proceedings of the 2005 workshop on Predictor models in software engineering, (New York, NY, USA), pp. 1–5, ACM, 2005.

2. O. Jalali, T. Menzies, D. Baker, and J. Hihn, “Column pruning beats stratification in effort estimation,” in PROMISE ’07: Proceedings of the Third International Workshop on Predictor Models in Software Engineering, (Washington, DC, USA), p. 7, IEEE Computer Society, 2007.

3. S. S. Gokhale and R. Mullen, “Software defect repair times: a multiplicative model,” in PROMISE ’08: Proceedings of the 4th international workshop on Predictor models in software engineering, (New York, NY, USA), pp. 93–100, ACM, 2008.

4. M. Azzeh, D. Neagu, and P. Cowling, “Improving analogy software effort estimation using fuzzy feature subset selection algorithm,” in PROMISE ’08: Proceedings of the 4th international workshop on Predictor models in software engineering, (New York, NY, USA), pp. 71–78, ACM, 2008.

5. M. Korte and D. Port, “Confidence in software cost estimation results based on mmre and pred,” in PROMISE ’08: Proceedings of the 4th international workshop on Predictor models in software engineering, (New York, NY, USA), pp. 63–70, ACM, 2008.

6. T. Menzies, B. Turhan, A. Bener, G. Gay, B. Cukic, and Y. Jiang, “Implications of ceiling effects in defect predictors,” in PROMISE ’08: Proceedings of the 4th international workshop on Predictor models in software engineering, (New York, NY, USA), pp. 47–54, ACM, 2008.

7. Y. Jiang, B. Cuki, T. Menzies, and N. Bartlow, “Comparing design and code metrics for software quality prediction,” in PROMISE ’08: Proceedings of the 4th international workshop on Predictor models in software engineering, (New York, NY, USA), pp. 11–18, ACM, 2008.

8. R. Moser, W. Pedrycz, and G. Succi, “A comparative analysis of the efficiency of change metrics and static code attributes for defect prediction,” in ICSE ’08: Proceedings of the 30th international conference on Software engineering, (New York, NY, USA), pp. 181– 190, ACM, 2008.

9. D. Port and M. Korte, “Comparative studies of the model evaluation criterions mmre and pred in software cost estimation research,” in ESEM ’08: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement, (New York, NY, USA), pp. 51–60, ACM, 2008.

10. M. Wedel, U. Jensen, and P. Göhner, “Mining software code repositories and bug databases using survival analysis models,” in ESEM ’08: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement, (New York, NY, USA), pp. 282–284, ACM, 2008.

11. A. Tosun, B. Turhan, and A. Bener, “Ensemble of software defect predictors: a case study,” in ESEM ’08: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement, (New York, NY, USA), pp. 318–320, ACM, 2008.

12. Y. Kultur, B. Turhan, and A. B. Bener, “Enna: software effort estimation using ensemble of neural networks with associative memory,” in SIGSOFT ’08/FSE-16: Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering, (New York, NY, USA), pp. 330–338, ACM, 2008.

13. B. Kitchenham and E. Mendes, “Why comparative effort prediction studies may be invalid,” in PROMISE ’09: Proceedings of the 5th International Conference on Predictor Models in Software Engineering, (New York, NY, USA), pp. 1–5, ACM, 2009.

14. A. Tosun, B. Turhan, and A. Bener, “Validation of network measures as indicators of defective modules in software systems,” in PROMISE ’09: Proceedings of the 5th International Conference on Predictor Models in Software Engineering, (New York, NY, USA), pp. 1–9, ACM, 2009.

15. M. Azzeh, D. Neagu, and P. Cowling, “Software effort estimation based on weighted fuzzy grey relational analysis,” in PROMISE ’09: Proceedings of the 5th International Conference on Predictor Models in Software Engineering, (New York, NY, USA), pp. 1–10, ACM, 2009.

16. T. Mende and R. Koschke, “Revisiting the evaluation of defect prediction models,” in PROMISE ’09: Proceedings of the 5th International Conference on Predictor Models in Software Engineering, (New York, NY, USA), pp. 1–10, ACM, 2009.

17. C. Bird, A. Bachmann, E. Aune, J. Duffy, A. Bernstein, V. Filkov, and P. Devanbu, “Fair and balanced?: bias in bug-fix datasets,” in ESEC/FSE ’09: Proceedings of the the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering, (New York, NY, USA), pp. 121– 130, ACM, 2009.

18. B. Caglayan, A. Bener, and S. Koch, “Merits of using repository metrics in defect prediction for open source projects,” in FLOSS ’09: Proceedings of the 2009 ICSE Workshop on Emerging Trends in Free/Libre/Open Source Software Research and Development, (Washington, DC, USA), pp. 31–36, IEEE Computer Society, 2009.

19. A. Tosun and A. Bener, “Reducing false alarms in software defect prediction by decision threshold optimization,” in ESEM ’09: Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement, (Washington, DC, USA), pp. 477–480, IEEE Computer Society, 2009.

20. S. Winkler, “Trace retrieval for evolving artifacts,” in TEFSE ’09: Proceedings of the 2009 ICSE Workshop on Traceability in Emerging Forms of Software Engineering, (Washington, DC, USA), pp. 49–56, IEEE Computer Society, 2009.

21. Y. Jiang, B. Cukic, and T. Menzies, “Can data transformation help in the detection of fault-prone modules?,” in DEFECTS ’08: Proceedings of the 2008 workshop on Defects in large software systems, (New York, NY, USA), pp. 16–20, ACM, 2008.

22. A. Sami and S. M. Fakhrahmad, “Design-level metrics estimation based on code metrics,” in SAC ’10: Proceedings of the 2010 ACM Symposium on Applied Computing, (New York, NY, USA), pp. 2531–2535, ACM, 2010.

23. Y. Jiang and B. Cukic, “Misclassification cost-sensitive fault prediction models,” in PROMISE ’09: Proceedings of the 5th International Conference on Predictor Models in Software Engineering, (New York, NY, USA), pp. 1–10, ACM, 2009.

24. Y. Ma and B. Cukic, “Adequate and precise evaluation of quality models in software engineering studies,” in PROMISE ’07: Proceedings of the Third International Workshop on Predictor Models in Software Engineering, (Washington, DC, USA), p. 1, IEEE Computer Society, 2007.

25. A. Dekhtyar, J. H. Hayes, and J. Larsen, “Make the most of your time: How should the analyst work with automated traceability tools?,” in PROMISE ’07: Proceedings of the Third International Workshop on Predictor Models in Software Engineering, (Washington, DC, USA), p. 4, IEEE Computer Society, 2007.

26. Y. Liu, J.-F. Yao, G. Williams, and G. Adkins, “Studying software metrics based on realworld software systems,” J. Comput. Small Coll., vol. 22, no. 5, pp. 55–61, 2007.

27. S. K. Sundaram, J. H. Hayes, and A. Dekhtyar, “Baselines in requirements tracing,” in PROMISE ’05: Proceedings of the 2005 workshop on Predictor models in software engineering, (New York, NY, USA), pp. 1–6, ACM, 2005.

28. S. Wagner, “A bayesian network approach to assess and predict software quality using activity-based quality models,” in PROMISE ’09: Proceedings of the 5th International Conference on Predictor Models in Software Engineering, (New York, NY, USA), pp. 1– 9, ACM, 2009.

29. G. D. Boetticher, “Nearest neighbor sampling for better defect prediction,” in PROMISE ’05: Proceedings of the 2005 workshop on Predictor models in software engineering, (New York, NY, USA), pp. 1–6, ACM, 2005.