Using Machine Learning and Information Retrieval Techniques to Improve Software Maintainability - Trustworthy Eternal Systems via Evolving, Software Data and Knowledge - page 132

4. Bellon, S., Koschke, R., Antoniol, G., Krinke, J., Merlo, E.M.: Comparison and
evaluation of clone detection tools. IEEE Trans. Software Eng., 577-591 (Septem-
ber 2007)
5. Bittencourt, R.A., Guerrero, D.D.S.: Comparison of graph clustering algorithms
for recovering software architecture module views. In: Proceedings of the Euro-
pean Conference on Software Maintenance and Reengineering, pp. 251-254. IEEE
Computer Society, Washington, DC (2009),
http://portal.acm.org/citation.cfm?id=1545011.1545446
6. Bulychev, P., Minea, M.: Duplicate code detection using anti-unification. In:
Spring/Summer Young Researcher's Colloquium (2008)
7. Corazza, A., Di Martino, S., Maggio, V., Scanniello, G.: Investigating the use of
lexical information for software system clustering. In: Proceedings of the 15th Eu-
ropean Conference on Software Maintenance and Reengineering, CSMR 2011, pp.
35-44. IEEE Computer Society, Washington, DC (2011),
http://dx.doi.org/10.1109/CSMR.2011.8
8. Corazza, A., Di Martino, S., Scanniello, G.: A probabilistic based approach towards
software system clustering. In: Proceedings of the European Conference on Software
Maintenance and Reengineering, pp. 88-96 (2010)
9. Corazza, A., Di Martino, S., Maggio, V., Scanniello, G.: A tree kernel based ap-
proach for clone detection. In: Proceedings of the 2010 IEEE International Con-
ference on Software Maintenance, ICSM 2010, pp. 1-5. IEEE Computer Society,
Washington, DC (2010),
http://dx.doi.org/10.1109/ICSM.2010.5609715
10. Corazza, A., Di Martino, S., Maggio, V., Scanniello, G.: Combining machine learn-
ing and information retrieval techniques for software clustering. In: Moschitti, A.,
Scandariato, R. (eds.) EternalS 2011. CCIS, vol. 255, pp. 42-60. Springer, Heidel-
berg (2012)
11. Deerwester, S.C., Dumais, S.T., Landauer, T.K., Furnas, G.W., Harshman, R.A.:
Indexing by latent semantic analysis. Journal of the American Society of Informa-
tion Science 41(6), 391-407 (1990),
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.49.7546
12. Doval, D., Mancoridis, S., Mitchell, B.S.: Automatic clustering of software systems
using a genetic algorithm. In: Proceedings of the Software Technology and Engi-
neering Practice, pp. 73-82. IEEE Computer Society, Washington, DC (1999),
http://portal.acm.org/citation.cfm?id=829540.832036
13. Ducasse, S., Pollet, D.: Software architecture reconstruction: A process-oriented
taxonomy. IEEE Transactions on Software Engineering 35(4), 573-591 (2009)
14. Ducasse, S., Rieger, M., Demeyer, S.: A language independent approach for detect-
ing duplicated code. In: Proceedings of the International Conference on Software
Maintenance, pp. 109-118 (1999)
15. Finley, T., Joachims, T.: Supervised clustering with support vector machines. In:
Proceedings of the 22nd International Conference on Machine Learning, ICML
2005, pp. 217-224. ACM, New York (2005),
http://doi.acm.org/10.1145/1102351.1102379
16. Frasconi, P., Passerini, A.: Learning with kernels and logical representations. In: De
Raedt, L., Frasconi, P., Kersting, K., Muggleton, S. (eds.) Probabilistic Inductive
Logic Programming. LNCS (LNAI), vol. 4911, pp. 56-91. Springer, Heidelberg
(2008)