Personalized defect prediction

2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings

Volumn , Issue , 2013, Pages 279-289

  Jiang, Tian ^a   Tan, Lin ^a   Kim, Sunghun ^b  

^a UNIVERSITY OF WATERLOO   (Canada)

^b HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

Change classification; machine learning; personalized defect prediction; software reliability

Indexed keywords

CLASSIFICATION TECHNIQUE; DEFECT PATTERNS; DEFECT PREDICTION; PREDICTION MODEL; PREDICTION PERFORMANCE; PROOF OF CONCEPT; SOFTWARE DEFECTS; SOFTWARE PROJECT;

C (PROGRAMMING LANGUAGE); COMPUTER SOFTWARE; FORECASTING; LEARNING SYSTEMS; MATHEMATICAL MODELS; SOFTWARE RELIABILITY;

DEFECTS;

EID: 84893606732     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ASE.2013.6693087     Document Type: Conference Paper

References (59)

1. S. Kim, J. E. James Whitehead, and Y. Zhang, "Classifying software changes: Clean or buggy?" TSE, vol. 34, pp. 181-196, 2008. (Pubitemid 351583527)
2. A. Hassan, "Predicting faults using the complexity of code changes," in ICSE, 2009, pp. 78-88.
3. A. Meneely, L. Williams, W. Snipes, and J. Osborne, "Predicting failures with developer networks and social network analysis," in FSE, 2008, pp. 13-23.
4. T. Menzies, Z. Milton, B. Turhan, B. Cukic, Y. Jiang, and A. B. Bener, "Defect prediction from static code features: Current results, limitations, new approaches," ASE, 2010.
5. T. Zimmermann and N. Nagappan, "Predicting defects using network analysis on dependency graphs," in ICSE, 2008.
6. T. Zimmermann, R. Premraj, and A. Zeller, "Predicting Defects for Eclipse," in PROMISE, 2007.
7. N. Bettenburg, M. Nagappan, and A. E. Hassan, "Think locally, act globally: Improving defect and effort prediction models," in MSR, 2012, pp. 60-69.
8. T. Graves, A. Karr, J. Marron, and H. Siy, "Predicting fault incidence using software change history," TSE, vol. 26, no. 7, pp. 653-661, 2000.
9. I. Herraiz, J. González-Barahona, G. Robles, and D. Germán, "On the prediction of the evolution of libre software projects," in ICSM, 2007, pp. 405-414.
10. A. Mockus, D. Weiss, and P. Zhang, "Understanding and predicting effort in software projects," in ICSE, 2003.
11. T. J. Ostrand, E. J. Weyuker, R. M. Bell, P. Avenue, and F. Park, "Programmer-based fault prediction," in PROMISE, 2010, pp. 1-10.
12. Google Official Blog, "Personalized search for everyone," http://googleblog.blogspot.ca/2009/12/personalized-search-for-everyone .html, 2009.
13. Y. Freund and L. Mason, "The alternating decision tree learning algorithm," in ICML, 1999, pp. 124-133.
14. J. H. Friedman, "Multivariate adaptive regression splines," The Annals of Statistics, vol. 19, no. 1, pp. 1-67, 1991.
15. F. Rahman, D. Posnett, and P. Devanbu, "Recalling the "imprecision" of cross-project defect prediction," in FSE, 2012.
16. F. Rahman and P. Devanbu, "How, and Why, process metrics are better," in ICSE, 2013.
17. E. Arisholm, L. C. Briand, and M. Fuglerud, "Data mining techniques for building fault-proneness models in telecom java software," 2007, pp. 215-224.
18. J. Eyolfson, L. Tan, and P. Lam, "Correlations between bugginess and time-based commit characteristics," EMSE, pp. 1-31, 2013.
19. J. Śliwerski, T. Zimmermann, and A. Zeller, "When do Changes Induce Fixes?" in MSR, 2005, pp. 24-28.
20. K. Herzig, S. Just, and A. Zeller, "It's not a bug, it's a feature: How misclassification impacts bug prediction," in ICSE, 2013.
21. L. Jiang, G. Misherghi, Z. Su, and S. Glondu, "DECKARD: Scalable and accurate tree-based detection of code clones," in ICSE, 2007, pp. 96-105. (Pubitemid 47430645)
22. B. Raskutti, H. Ferra, and A. Kowalczyk, "Second-order features for maximizing text classification performance," ECML, pp. 419-430, 2001. (Pubitemid 33331088)
23. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. H. Witten, "The WEKA data mining software: An update," SIGKDD Explor. Newsl., vol. 11, no. 1, pp. 10-18, 2009.
24. "Snowball," http://snowball.tartarus.org/.
25. Z. Li, L. Tan, X. Wang, S. Lu, Y. Zhou, and C. Zhai, "Have things changed now? An empirical study of bug characteristics in modern open source software," in ASID, October 2006.
26. G. Bougie, C. Treude, D. Germán, and M. Storey, "A comparative exploration of FreeBSD bug lifetimes," in MSR, 2010, pp. 106-109.
27. T. Zimmermann, N. Nagappan, H. Gall, E. Giger, and B. Murphy, "Cross-project defect prediction: A large scale experiment on data vs. domain vs. process," in FSE, 2009, pp. 91-100.
28. G. H. John and P. Langley, "Estimating continuous distributions in bayesian classifiers," in UAI. San Mateo: Morgan Kaufmann, 1995, pp. 338-345.
29. N. Landwehr, M. Hall, and E. Frank, "Logistic model trees," vol. 95, no. 1-2, pp. 161-205, 2005. (Pubitemid 40890416)
30. T. Curk, J. Demar, Q. Xu, G. Leban, U. Petrovi, I. Bratko, G. Shaulsky, and B. Zupan, "Microarray data mining with visual programming," Bioinformatics, vol. 21, pp. 396-398, Feb. 2005. (Pubitemid 40246614)
31. D. Engler, D. Y. Chen, S. Hallem, A. Chou, and B. Chelf, "Bugs as deviant behavior: A general approach to inferring errors in systems code," in SOSP, 2001, pp. 57-72. (Pubitemid 33612605)
32. A. Chou, J. Yang, B. Chelf, S. Hallem, and D. Engler, "An empirical study of operating systems errors," in SOSP, 2001, pp. 73-88. (Pubitemid 33612606)
33. S. Kim and E. J. Whitehead, Jr., "How long did it take to fix bugs?" in MSR, 2006, pp. 173-174.
34. A. Hassan and R. Holt, "The top ten list: Dynamic fault prediction," in ICSM, 2005, pp. 263-272. (Pubitemid 43790940)
35. A. W. Moore, "Cross-validation," http://www.autonlab.org/ tutorials/overfit.html, 2008.
36. S. Kim, H. Zhang, R. Wu, and L. Gong, "Dealing with noise in defect prediction," in ICSE, New York, NY, USA, 2011, pp. 481-490.
37. T. J. Ostrand, E. J. Weyuker, and R. M. Bell, "Predicting the location and number of faults in large software systems," TSE, vol. 31, no. 4, pp. 340-355, Apr. 2005. (Pubitemid 41046924)
38. C. Lewis, Z. Lin, C. Sadowski, X. Zhu, R. Ou, and E. J. Whitehead Jr, "Does bug prediction support human developers? findings from a google case study," in ICSE, 2013, pp. 372-381.
39. C. Bird, A. Bachmann, E. Aune, J. Duffy, A. Bernstein, V. Filkov, and P. Devanbu, "Fair and balanced?: Bias in bug-fix datasets," in FSE, 2009, pp. 121-130.
40. R. Wu, H. Zhang, S. Kim, and S. Cheung, "Relink: Recovering links between bugs and changes," in FSE, 2011, pp. 15-25.
41. S. Kim, T. Zimmermann, K. Pan, and J. J. Whitehead, "Automatic identification of bug-introducing changes," in ASE, 2006, pp. 81-90. (Pubitemid 47159336)
42. PostgreSQL Community, "Committing with Git - PostgreSQL Wiki," http://wiki.postgresql.org/wiki/Committing-with Git, 2012.
43. J. Anvik, L. Hiew, and G. C. Murphy, "Who should fix this bug?" in ICSE, 2006, pp. 361-370. (Pubitemid 46600933)
44. D. Matter, A. Kuhn, and O. Nierstrasz, "Assigning bug reports using a vocabulary-based expertise model of developers," in MSR, 2009, pp. 131-140.
45. J. Park, M. Lee, J. Kim, S. Hwang, and S. Kim, "CosTriage: A costaware triage algorithm for bug reporting systems," in AAAI, 2011.
46. G. Jeong, S. Kim, and T. Zimmermann, "Improving bug triage with bug tossing graphs," in FSE, 2009, pp. 111-120.
47. M. Lumpe, R. Vasa, T. Menzies, R. Rush, and B. Turhan, "Learning better inspection optimization policies," IJSEKE, vol. 22, no. 5, pp. 621- 644, 2012.
48. S. Shivaji, E. J. W. Jr., R. Akella, and S. Kim, "Reducing features to improve code change-based bug prediction," TSE, vol. 39, no. 4, pp. 552-569, 2013.
49. C. Tucker, "Social Networks, Personalized Advertising, and Privacy Controls," in WEIS, 2011.
50. S. Matsumoto, Y. Kamei, A. Monden, K.-i. Matsumoto, and M. Nakamura, "An analysis of developer metrics for fault prediction," in PROMISE, 2010, pp. 18:1-18:9.
51. F. Rahman and P. Devanbu, "Ownership, experience and defects: A finegrained study of authorship," in ICSE, 2011, pp. 491-500.
52. D. Posnett, R. DSouza, P. Devanbu, and V. Filkov, "Dual ecological measures of focus in software development," in ICSE, 2013.
53. A. Hindle, E. Barr, Z. Su, M. Gabel, and P. Devanbu, "On the naturalness of software," in ICSE, 2012, pp. 837-847.
54. K. Muslu, Y. Brun, R. Holmes, M. D. Ernst, and D. Notkin, "Improving ide recommendations by considering global implications of existing recommendations," in ICSE, 2012, pp. 1349-1352.
55. Y. Ye and G. Fischer, "Supporting reuse by delivering task-relevant and personalized information," in ICSE, 2002, pp. 513-523. (Pubitemid 35009137)
56. D. Kim, X. Wang, S. Kim, A. Zeller, S. Cheung, and S. Park, "Which crashes should i fix first?: Predicting top crashes at an early stage to prioritize debugging efforts," TSE, vol. 37, no. 3, pp. 430-447, 2011.
57. S. S. Kolesnikov, S. Apel, N. Siegmund, S. Sobernig, C. Kästner, and S. Senkaya, "Predicting quality attributes of software product lines using software and network measures and sampling," in VaMoS, 2013, p. 6.
58. Y. Tian, J. Lawall, and D. Lo, "Identifying Linux bug fixing patches," in ICSE, 2012, pp. 386-396.
59. Y. Shin and L. Williams, "Can traditional fault prediction models be used for vulnerability prediction?" EMSE, vol. 18, no. 1, pp. 25-59, 2013.