ENNA: Software effort estimation using ensemble of neural networks with associative memory

Proceedings of the ACM SIGSOFT Symposium on the Foundations of Software Engineering

Volumn , Issue , 2008, Pages 330-338

  Kultur, Yigit ^a   Turhan, Burak ^a   Bener, Ayse Basar ^a  

^a BOGAZICI UNIVERSITY   (Turkey)

Author keywords

Adaptive Resonance Theory; Associative Memory; Bootstrap; Cost Estimation; Effort Estimation; Ensemble; K nearest neighbors; Multilayer Perceptron; Neural Network

Indexed keywords

ADAPTIVE RESONANCE THEORY; ASSOCIATIVE MEMORIES; COST ESTIMATIONS; EFFORT ESTIMATION; K-NEAREST NEIGHBORS; MULTI-LAYER PERCEPTRON NEURAL NETWORKS;

ASSOCIATIVE PROCESSING; COMPUTER SOFTWARE; ELECTRIC LOADS; ESTIMATION; LEARNING ALGORITHMS; LEARNING SYSTEMS; MOTION COMPENSATION; MULTILAYERS; OBJECT ORIENTED PROGRAMMING; RESONANCE;

NEURAL NETWORKS;

EID: 73949114934     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1453101.1453148     Document Type: Conference Paper

References (35)

1. Srinivasan, K. and Fisher, D., 1995. Machine Learning Approaches to Estimating Software Development Effort, IEEE Transactions on Software Engineering, Vol.21, No.2 (February 1995), Pages: 126-137
2. Younghee, K. and Keumsuk L., 2005. A Comparison of Techniques for Software Development Effort Estimating, System Integration
3. Venkatachalam, A. R., 1993. Software Cost Estimation Using Artificial Neural Networks, Proceedings of 1993 International Joint Conference on Neural Networks, Vol.1, (October 1993), Pages: 987- 990
4. Finnie, G. R. and Wittig, G. E., 1996. AI Tools for Software Development Effort Estimation, Proceedings of International Conference on Software Engineering: Education and Practice (SE:EP '96), Pages: 346
5. Ahn, Y., Suh, J., Kim, S. and Kim, H., 2003. The Software Maintenance Project Effort Estimation Model Based on Function Points, Journal of Software Maintenance and Evolution: Research and Practice, Vol.15, Issue 2 (April 2003), Pages: 71-85
6. Adrangi, B. and Harrison, W., 1987. Effort Estimation in a System Development Project, Journal of Systems Management, Vol.36, Issue 8, Pages: 21-23
7. Banker, R. D., Chang, H. and Kemerer, C. F., 1994. Evidence on Economies of Scale in Software Development, Information and Software Technology, Vol.36, Issue 5, Pages: 275-282.
8. Benediktsson, O., Dalcher, D. and Reed, K., 2003. COCOMO-Based Effort Estimation for Iterative and Incremental Software Development, Software Quality Journal, Vol.11, Issue 4, Pages: 265-281 (Pubitemid 39019677)
9. Harrison, W. and Adrangi, B., 1987. The Role of Programming Language in Estimating Software Development Costs, Journal of Management Information Systems, Vol.3, Issue 3, Pages: 101-110
10. Bielak, J., Improving Size Estimates Using Historical Data, 2000. IEEE Software, Vol.17, Issue 6 (November-December 2000), Pages: 27-35 (Pubitemid 32085693)
11. Kaplan, H. T., 1991. The Ada COCOMO Cost Estimating Model and VASTT Development Estimates vs. Actuals, Vitro Technical Journal, Vol.9, Issue 1, Pages: 48-60
12. Jorgensen, M., and Shepperd, M., 2007. A Systematic Review of Software Development Cost Estimation Studies, IEEE Transactions on Software Engineering, Vol.33, No.1 (January 2007), Pages: 33-53 (Pubitemid 46002167)
13. Kemerer, C. F., 1987. An Empirical Validation of Software Cost Estimation Models, Communications of the ACM, Vol.30, Issue 5 (May 1987), Pages: 416- 429 (Pubitemid 17589082)
14. Shepperd, M. and Schofield, C., 1997. Estimating Software Project Effort Using Analogies, IEEE Transactions on Software Engineering, Vol.23, No.12 (November 1997), Pages: 736-743 (Pubitemid 127762233)
15. Burgess, C. J. and Lefley, M., 2001. Can genetic programming improve software effort estimation? A comparative evaluation", Information and Software Technology 43, Pages: 863-873 (Pubitemid 33050966)
16. Shan, Y., McKay, R. I., Lokan, C. J. and Essam, D. L., 2002. Software Project Effort Estimation Using Genetic Programming, International Conference on Communications, Circuits and Systems and West Sino Expositions, Vol.2, Pages: 1108-1112
17. Breiman, L., Friedman J., Olshen, R. A. and Stone C. J., 1984. Classification and regression trees, Wadsworth
18. Hornik, K., Stinchcombe, M. and White, H., 1989. Multilayer Feedforward Networks are Universal Approximators, Neural Networks, Vol.2, Issue 5, Pages: 359-366 (Pubitemid 20609008)
19. German, S., Bienenstock, E. and Doursat R., 1992. Neural Networks and the Bias/Variance Dilemma, Neural Computation, Vol.4, Issue 1 (January 1992), Pages: 1-58
20. Oral, A. D. and Bener, A., 2007. Defect Prediction for Embedded Software, ISCIS 2007, Ankara, Turkey, November 7-9 2007
21. Abeles, M., 1991. Corticotronics: Neural circuits of the cerebral cortex, Cambridge University Press, New York
22. Alpaydn, E., 2004. Introduction to Machine Learning, MIT Press, 2004
23. Levenberg, K., 1944. A Method for the Solution of Certain Non-Linear Problems in Least Squares, The Quarterly of Applied Mathematics 2, Pages: 164-168
24. Marquardt, D., 1963. An Algorithm for Least-Squares Estimation of Nonlinear Parameters, SIAM Journal on Applied Mathematics 11, Pages: 431-441.
25. Hagan, M. T. and Menhaj, M. B., 1994. Training Feedforward Networks with the Marquardt Algorithm, IEEE Transactions on Neural Networks, Vol.5, Issue 6 (November 1994), Pages: 989-993
26. Carpenter, G. A. and Grossberg, S., 1988. The ART of Adaptive Pattern Recognition by a Self-Organizing Neural Network, IEEE Computer, Vol.21, Issue 3 (March 1988), Pages: 77-88 (Pubitemid 18612300)
27. Kohonen, T., 1984. Self-Organization and Associative Memory, Springer Series In Information Sciences, Vol.8.
28. Boetticher, G., Menzies, T. and Ostrand T., 2007. PROMISE Repository of empirical software engineering data http://promisedata.org/ repository, West Virginia University, Department of Computer Science
29. Software Research Laboratory, Bogazici University, SDR Dataset for Cost Estimation, http://softlab.boun.edu.tr/?q=resources
30. Desharnais, J. M., 1989. Analyse statistique de la productivitie des projets informatique a partie de la technique des point des function, University of Montreal, Masters Thesis
31. Conte, S. D., Dunsmore, H. E. and Shen, V. Y., 1986. Software Engineering Metrics and Models, Benjamin- Cummings Publishing, Menlo Park CA
32. Kohavi, R., 1995. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection, Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, Pages: 1137-1143.
33. Baskeles, B., Turhan, B. and Bener A., 2007. Software Effort Estimation Using Machine Learning Methods, ISCIS 2007, Ankara, Turkey, November 7-9 2007
34. Basili, V. R., McGarry, F. E., Pajerski, R. and Zelkowitz, M. V., 2002. Lessons Learned from 25 years of process improvement: The Rise and Fall of the NASA Software Engineering Laboratory, Proceedings of the 24th International Conference on Software Engineering, Pages: 69-79
35. Hersleb, J. D. and Moitra, D., 2001. Global software development, IEEE Software, Vol.18, Issue 2, (March-April 2001), Pages: 16-20