Evolution and search based metrics to improve defects prediction

Proceedings - 1st International Symposium on Search Based Software Engineering, SSBSE 2009

Volumn , Issue , 2009, Pages 23-32

  Kpodjedo, Segla ^a   Ricca, Filippo ^b   Antoniol, Giuliano ^a   Galinier, Philippe ^a  

^a ÉCOLE POLYTECHNIQUE DE MONTRÉAL   (Canada)

^b UNIVERSITY OF GENOA   (Italy)

Author keywords

Class Rank; Defects Prediction; Error Correcting Graph Matching (ECGM) algorithm; Evolution Cost; Software evolution

Indexed keywords

CLASS DIAGRAMS; CLASS RANK; CRITICAL RESOURCES; EVOLUTION COST; OBJECT ORIENTED METRICS; SOFTWARE EVOLUTION; SOFTWARE METRICS; SOFTWARE QUALITY; TESTING EFFORT;

COMPUTER SOFTWARE SELECTION AND EVALUATION; METRIC SYSTEM; PATTERN MATCHING; SOFTWARE ENGINEERING;

DEFECTS;

EID: 70349283484     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SSBSE.2009.24     Document Type: Conference Paper

References (24)

1. V. Basili, G. Caldiera, and D. H. Rombach. The Goal Question Metric Paradigm Encyclopedia of Software Engineering. JohnWiley and Sons, 1994.
2. L. C. Briand, J. W. Daly, and J. Wüst. A unified framework for cohesion measurement in objectoriented systems. Empirical Softw. Eng., 3(1):65-117, 1998.
3. L. C. Briand, Y. Labiche, and Y. Wang. An investigation of graph-based class integration test order strategies. IEEE Trans. on Software Engineering, 29(7):594-607, 2003.
4. L. C. Briand, W. L. Melo, and J. Wüst. Assessing the applicability of fault-proneness models across object-oriented software projects. IEEE Trans. on Software Engineering, 28(7):706-720, 2002.
5. M. Cartwright and M. Shepperd. An empirical investigation of an object-oriented software system. IEEE Trans. on Software Engineering, 26(8):786-796, August 2000.
6. S. R. Chidamber and C. F. Kemerer. A metrics suite for object oriented design. IEEE Trans. on Software Engineering, 20(6):476-493, June 1994.
7. M. Eaddy, T. Zimmermann, K. D. Sherwood, V. Garg, G. C. Murphy, N. Nagappan, and A. V. Aho. Do crosscutting concerns cause defects? IEEE Transaction on Software Engineering, 34(4):497-515, 2008.
8. K. E. Emam, S. Benlarbi, N. Goel, and S. Rai. The confounding effect of class size on the validity of object-oriented metrics. IEEE Trans. on Software Engineering, 27(7):630-650, July 2001.
9. N. Fenton and S. Pfleeger. Software Metrics: A Rigorous and Practical Approach (2nd Edition). Thomson Computer Press, Boston, 1997.
10. T. Gyimóthy, R. Ferenc, and I. Siket. Empirical validation of object-oriented metrics on open source software for fault prediction. IEEE Transaction on Software Engineering, 31(10):897-910, 2005.
11. T. Khoshgoftaar., B. Allen, K. Kalaichelvan, and N. Goel. Early quality prediction: a case study in telecommunications. IEEE Software, 13(1):65-71, 1996.
12. P. Knab, M. Pinzger, and A. Bernstein. Predicting defect densities in source code files with decision tree learners. In MSR '06: Proceedings of the international workshop on Mining software repositories, pages 119-125, New York, NY, USA, 2006.
13. S. Kpodjedo, P. Galinier, and G. Antoniol. A google-inspired error correcting graph matching algorithm. Technical Report EPM-RT-2008-2106, Ecole Polytechnique de Montreal, 06 2008.
14. S. Kpodjedo, F. Ricca, P. Galinier, and G. Antoniol. Error correcting graph matching application to software evolution. In Proc. of the Working Conference on Reverse Engineering, pages 289- 293, 2008.
15. S. Kpodjedo, F. Ricca, P. Galinier, and G. Antoniol. Not all classes are created equal: toward a recommendation system for focusing testing. In RSSE '08: Proc. of the International Workshop on Recommendation Systems for Software Engineering, pages 6-10, New York, NY, USA, 2008.
16. S. Kpodjedo, F. Ricca, P. Galinier, and G. Antoniol. Recovering the evolution stable part using an ecgm algorithm: is there a tunnel in mozilla. In To appear in Proc. of IEEE European Conference on Software Maintenance and Reengineering, 2009.
17. N. Nagappan and T. Ball. Use of relative code churn measures to predict system defect density. In Proc. of the International Conference on Software Engineering (ICSE), pages 284-292, 2005.
18. T. J. Ostrand, E. J. Weyuker, and R. M. Bell. Predicting the location and number of faults in large software systems. IEEE Trans. on Software Engineering, 31:340-355, 2005.
19. L. Page, S. Brin, R. Motwani, and T. Winograd. The pagerank citation ranking: Bringing order to the web. Technical report, Stanford Digital Library Technologies Project, 1998.
20. J. Rawlings, S. G. Pandula, and D. A. Dickey. Applied Regression Analysis a Research Tool. Springer Texts in Statistics. New York: Springer- Verlag, second edition, 1998.
21. W. Tsai and K.-S. Fu. Error-correcting isomorphism of attributed relational graphs for pattern analysis. IEEE Trans. on Systems, Man, and Cybernetics, 9:757768, 1979.
22. I. Witten and E. Frank. Data Mining Practical Machine Learning Tools and Techniques - Second Edition. Elsevier, 2005.
23. Z. Xing and E. Stroulia. Umldiff: an algorithm for object-oriented design differencing. In ASE '05: Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering, pages 54-65, New York, NY, USA, 2005.
24. T. Zimmermann, R. Premraj, and A. Zeller. Predicting defects for eclipse. In Proceedings of the Third International Workshop on Predictor Models in Software Engineering, May 2007.