E-CDGM: An Evolutionary Call-Dependency Graph Modularization Approach for Software Systems

1. Mitchell, B. S., S. Mancoridis. On the Automatic Modularization of Software Systems Using the Bunch Tool. - Software Engineering, IEEE Transactions On, Vol. 32, 2006, No 3, pp. 193-208.10.1109/TSE.2006.31Search in Google Scholar

2. Qifeng, Z., Q. Dehong, T. Qubo, S. Lei. Object-Oriented Software Architecture Recovery Usinga New Hybrid Clustering Algorithm. - In: 7th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD’2010), 2010, pp. 2546-2550.Search in Google Scholar

3. Lung, C., M. Zaman, A. Nandi. Applications of Clustering Techniques to Software Partitioning, Recovery and Restructuring. - Journal of Systems and Software, Vol. 73, 2004, pp. 227-244.10.1016/S0164-1212(03)00234-6Search in Google Scholar

4. Lung, C., X. Xu, M. Zaman, A. Srinivasan. Program Restructuring Using Clustering Techniques. - The Journal of Systems and Software, Vol. 79, 2006, pp. 1261-1279.10.1016/j.jss.2006.02.037Search in Google Scholar

5. Bittencourt, R. A., G. D. D. Serey. Comparison of Graph Clustering Algorithms for Recovering Software Architecture Module Views. - In: Proc. of Software Maintenance and Reengineering (CSMR’2009), IEEE Computer Society Press, pp. 251-254.10.1109/CSMR.2009.28Search in Google Scholar

6. Pressman, R. S. Software Engineering: A Practitioner’s Approach. Eighth Ed. 2014, Mc Graw-Hill, Inc. Search in Google Scholar

7. Poshyvanyk, D., A. Marcus, R. Ferenc, T. Gyimóthy. Using Information Retrieval based Coupling Measures for Impact Analysis. - Empirical Software Engineering, Vol. 14, 2009, No 1, pp. 5-32.10.1007/s10664-008-9088-2Search in Google Scholar

8. Ferenc, R., A. Beszedes, T. Gyimóthy. Extracting Facts with Columbus from C++ Code. - In: Proc. of the Eighth CSMR, 2004, pp. 4-8.Search in Google Scholar

9. Chen, Y., E. Gansner, E. Koutsofios. A C++ Data Model Supporting Reachability Analysis and Dead Code Detection. - In: Proc. of 6th European Software Engineering Conf. and 5th ACM SIGSOFT Symposioum on the Foundations of Software Engineering, 1997.10.1145/267896.267924Search in Google Scholar

10. Korn, J., Y. Chen, E. Koutsofios. Chava: Reverse Engineering and Tracking of Java Applets. - In: Proc. of Working Conf. on Reverse Engineering, 1999.Search in Google Scholar

11. Raza, A., G. Vogel, E. Plödereder. Bauhaus - A Tool Suite for Program Analysis and Reverse Engineering. - In: Reliable Software Technologies. Ada, Europe 2006, pp. 71-83.10.1007/11767077_6Search in Google Scholar

12. Dobiš, M., L. U. Majtás. Mining Design Patterns from Existing Projects Using Static and Run-Time Analysis. - In: Software Engineering Techniques. Berlin, Heidelberg, Springer, 2008, pp. 62-75.10.1007/978-3-642-22386-0_5Search in Google Scholar

13. Clarke, P. J., T. H. Gibbs, B. A. Malloy, J. F. Power. Reveal: A Tool to Reverse Engineer Class Diagrams. - In: Proc. of 14th International Conference on Tools Pacific: Objects for Internet, Mobile and Embedded Applications CRPIT’2002, Sarah Matzko, pp. 13-21.Search in Google Scholar

14. Mkaouer, W., M. Kessentini, A. Shaout, P. Koligheu, S. Bechikh, K. Deb, A. Ouni. Many-Objective Software Remodularization Using NSGA-III. - ACM Transactions on Software Engineering and Methodology (TOSEM), Vol. 24, 2015, No 3, p. 17.10.1145/2729974Search in Google Scholar

15. Bavota, G., F. Carnevale, A. De Lucia, M. Di Pena, R. Oliveto. Putting the Developer in-the-Loop: An Interactive GAfor Software Re-Modularization. - In: Search Based Software Engineering, Berlin, Heidelberg, Springer, 2012, pp. 75-89.Search in Google Scholar

16. Bavota, G., A. De Lucia, A. Marcus, R. Oliveto. Using Structural and Semantic Measures to Improve Software Modularization. - Empirical Software Engineering, Vol. 18, 2013, No 5, pp. 901-932.10.1007/s10664-012-9226-8Search in Google Scholar

17. Parsa, S., O. Bushehrian. A New Encoding Scheme anda Framework to Investigate Genetic Clustering Algorithms. - Journal of Research and Practice in Information Technology, Vol. 37, 2005, No 1, pp. 127-143.Search in Google Scholar

18. Mitchell, B. S., S. Mancoridis. CRAFT: A Framework for Evaluating Software Clustering Results in the Absence of Benchmark Decomposition. - In: Proc. of IWPC, IEEE, 2001.Search in Google Scholar

19. Räihä, O. A Survey on Search-Based Software Design. - Computer Science Review, Vol. 4, 2010, Issue 4, pp. 203-249.10.1016/j.cosrev.2010.06.001Search in Google Scholar

20. Harman, M., S. A. Ansouri, J. Zhang. Search Based Software Engineering: A Comprehensive Review. Technical Report TR-09-03, 2009, King’s College, London, United Kingdom.Search in Google Scholar

21. Auffarth, B. Clustering bya Genetic Algorithm with Biased Mutation Operator. - WCCI CEC, IEEE, 2010, pp. 18-23.10.1109/CEC.2010.5586090Search in Google Scholar

22. Mamaghani, A., M. R. Meybodi. Clustering of Software Systems Using New Hybrid Algorithms. - In: Proc. of IEEE 11th International Conference on Computer and Information Technology, 2009, pp. 20-26.10.1109/CIT.2009.111Search in Google Scholar

23. Sundaresan, V., L. Hendren, C. Raza Fimahefa, R. Vallée-Rai, P. Lam, E. Gagnon, C. Godin. Practical Virtual Method Call Resolution for Java. - ACM, Vol. 35, 2000, No 10, pp. 264-280.10.1145/354222.353189Search in Google Scholar

24. Bush, R. R., F. Mosteller. Stochastic Models for Learning. New York, Wiley, 1958. Search in Google Scholar