Moving to smaller libraries via clustering and genetic algorithms

Proceedings of the European Conference on Software Maintenance and Reengineering, CSMR

Volumn , Issue , 2003, Pages 307-316

  Antoniol, G ^a   Di Penta, M ^a   Neteler, M ^b  

^a UNIVERSITY OF SANNIO   (Italy)

^b ITC IRST   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING METHODS; EMBEDDED DEVICE; INITIAL SOLUTION; MEMORY REQUIREMENTS; MULTI-OBJECTIVE FITNESS FUNCTION; NOVEL GENETIC ALGORITHM; OPEN SOURCE SOFTWARE SYSTEMS; SOFTWARE SYSTEMS;

COMPUTER SOFTWARE; COMPUTER SOFTWARE MAINTENANCE; GENETIC ALGORITHMS; KNOWLEDGE BASED SYSTEMS; REENGINEERING;

LIBRARIES;

EID: 84884717973     PISSN: 15345351     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CSMR.2003.1192439     Document Type: Conference Paper

References (32)

1. The R project for statistical computing. http://www. r-project. org.
2. M. R. Anderberg. Cluster Analysis for Applications. Academic Press Inc., 1973.
3. N. Anquetil and T. Lethbridge. Extracting concepts from file names; a newfi le clustering criterion. In Proceedings of the International Conference on Software Engineering, pages 84-93, April 1998.
4. G. Antoniol, G. Casazza, M. Di Penta, and E. Merlo. A method to re-organize legacy systems via concept analysis. In Proceedings of the IEEE International Workshop on Program Comprehension, pages 281-290, Toronto, ON, Canada, May 2001. IEEE Press.
5. T. N. Bui and B. R. Moon. Genetic algorithm and graph partitioning. IEEE Transactions on Computers, 45(7):841-855, Jul 1996.
6. K. Deb. Multi-objective genetic algorithms: Problem difficulties and construction of test problems. Evolutionary Computation, 7(3):205-230, 1999.
7. M. Di Penta, M. Neteler, G. Antoniol, and E. Merlo. Knowledge-based library re-factoring for an open source project. In Proceedings of IEEE Working Conference on Reverse Engineering, Richmond-VA, Oct 2002 (to appear).
8. D. Doval, S. Mancoridis, and B. Mitchell. Automatic clustering of software systems using a genetic algorithm. In Software Technology and Engineering Practice (STEP), pages 73-91, Pittsburgh, PA, 1999.
9. M. Garey and D. Johnson. Computers and Intractability: a Guide to the Theory of NP-Completeness. W. H. Freeman, 1979.
10. D. E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub Co, Jan 1989.
11. A. Gordon. Classification-(2nd edition). Chapman and Hall, London, 1988.
12. M. Harman, R. Hierons, and M. Proctor. A newr epresentation and crossover operator for search-based optimization of software modularization. In AAAIGe netic and Evolutionary Computation COnference (GECCO), pages 82-87, New York, USA, July 2002.
13. J. Horn, N. Nafpliotis, and D. E. Goldberg. A Niched Pareto Genetic Algorithm for Multiobjective Optimization. In Proceedings of the First IEEE Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, volume 1, pages 82-87, Piscataway, New Jersey, 1994. IEEE Service Center.
14. R. Ihaka and R. Gentleman. R: A language for data analysis and graphics. Journal of Computational and Graphical Statistics, 5(3):299-314, 1996.
15. A. Jain and R. Dubes. Algorithms for Clustering Data. Prentice-Hall, 1988.
16. L. Kaufman and P. Rousseeew. Finding groups in data: an introduction to cluster analysis. Wiley-Inter Science, Wiley-NY, 1990.
17. L. Kaufman and P. J. Rousseeuw. Finding Groups in Data: An Introduction to Cluster Analysis. John Wiley, 1990.
18. M. Krone and G. Snelting. On the inference of configuration structures from source code. In Proc. of the 16th International Conference on Software Engineering, pages 49-57, Sorrento Italy, May 1994.
19. T. Kuipers and A. van Deursen. Identifying objects using cluster and concept analysis. In Proceedings of the International Conference on Software Engineering, pages 246-255, June 1999.
20. H. Maini, K. Mehrotra, C. Mohan, and S. Ranka. Knowledge-based nonuniform crossover. In IEEE World Congress on Computational Intelligence, pages 22-27, 1994.
21. S. Mancoridis, B. S. Mitchell, C. Rorres, Y. Chen, and E. R. Gansner. Using automatic clustering to produce high-level system organizations of source code. In IEEE Proceedings of the 1998 Int. Workshop on Program Comprehension (IWPC'98), 1998.
22. E. Merlo, I. McAdam, and R. De Mori. Source code informal information analysis using connectionist model. In Proceedings of the International Joint Conference on Artificial Intelligence, pages 1339-44, Load Altos Calif, 1993.
23. M. Neteler, editor. GRASS 5. 0 Programmer's Manual. Geographic Resources Analysis Support System. ITC-irst, Italy, http://grass. itc. it/grassdevel. html, 2001.
24. M. Neteler and H. Mitasova. Open Source GIS: A GRASS GIS Approach. Kluwer Academic Publishers, Boston/U. S. A; Dordrecht/Holland; London/U. K., 2002.
25. B. Oommen and E. de St. Croix. Graph partitioning using learning automata. IEEE Transactions on Computers, 45(2):195-208, Feb 1996.
26. S. Shazely, H. Baraka, and A. Abdel-Wahab. Solving graph partitioning problem using genetic algorithms. In Midwest Symposium on Circuits and Systems, pages 302-305, 1998.
27. G. Snelting. Software reengineering based on concept lattices. In Proceedings of IEEE International Conference on Software Maintenance, pages 3-10, March 2000.
28. E. Talbi and P. Bessire. A parallel genetic algorithm for the graph partitioning problem. In ACM International Conference on Supercomputing, Cologne, Germany, 1991.
29. V. Tzerpos and R. C. Holt. MoJo: A distance metric for software clusterings. pages 187-195.
30. V. Tzerpos and R. C. Holt. Software botryology: Automatic clustering of software systems. In DEXA Workshop, pages 811-818, 1998.
31. M. Wall. GAlib-a C++ library of genetic algorithm components. http://lancet. mit. edu/ga/.
32. E. Zitzler, K. Deb, and L. Thiele. Comparison of Multiobjective Evolutionary Algorithms on Test Functions of Different Difficulty. In A. S. Wu, editor, Proceedings of the 1999 Genetic and Evolutionary Computation Conference. Workshop Program, pages 121-122, Orlando, Florida, 1999.