Development of software effort and schedule estimation models using soft computing techniques

2008 IEEE Congress on Evolutionary Computation, CEC 2008

Volumn , Issue , 2008, Pages 1283-1289

  Sheta, Alaa ^a   Rine, David ^b   Ayesh, Aladdin ^c  

^a AL BALQA APPLIED UNIVERSITY   (Jordan)

^b GEORGE MASON UNIVERSITY   (United States)

^c DE MONTFORT UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EVOLUTIONARY ALGORITHMS; FUZZY LOGIC; FUZZY SETS; FUZZY SYSTEMS; NASA; SOFT COMPUTING;

ACCURATE ESTIMATIONS; CONSTRUCTIVE COST MODELS; DATA SETS; DEVELOPED MODELS; DO-MAINS; ESTIMATED COSTS; ESTIMATION MODELS; LINE OF CODES; LINEAR MODELS; PROJECT DELIVERIES; SOFT COMPUTING TECHNIQUES; SOFTWARE EFFORTS; SOFTWARE PROJECTS;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 55849119549     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2008.4630961     Document Type: Conference Paper

References (44)

1. J. W. Bailey and V. R. Basili, "A meta model for software development resource expenditure," in Proceedings of the International Conference on Software Engineering, pp. 107-115, 1981.
2. L. C. Briand, K. E, Emam, and I. Wieczorek, "Explaining the cost of european space and military projects," in ICSE'99: Proceedings of the 21st international conference on Software engineering, (Los Alamitos, CA, USA), pp. 303-312, IEEE Computer Society Press, 1999.
3. "Estimating software projects," SIGSOFT Softw. Eng. Notes, vol. 26, no. 4, pp. 60-67, 2001.
4. J. W. Park R, W, Goethert, 'Software cost and schedule estimating: A process improvement initiative," tech. rep., 1994.
5. M. Shepper and C. Schofield, "Estimating software project effort using analogies." IEEE Tran. Software Engineering, vol. 23, pp. 736-743, 1997.
6. T, S. Group, CHAOS Chronicles, PhD thesis, Standish Group Internet Report, 1995.
7. M. Boraso, C. Montangero, and H. Sedehi, "Software cost estimation: An experimental study of model performances," tech. rep., 1996.
8. O. Benediktsson, D, Dalcher, K. Reed, and M. Woodman, "COCOMO based effort estimation for iterative and incremental software development," Software Quality Journal, vol. 11, pp. 265-281, 2003.
9. T. Menzies, D. Port, Z. Chen, J. Hihn, and S. Stukes, "Validation methods for calibrating software effort models," in ICSE'05: Proceedings of the 27th international conference on Software engineering, (New York, NY, USA), pp. 587-595, ACM Press, 2005,
10. S. Chulani, B. Boehm, and B. Steece, "Calibrating software cost models using bayesian analysis," IEEE Trans. Software Engr., July-August 1999, pp. 573-583, 1999.
11. B. Clark, S. Devnani-Chulani, and B. Boehm, "Calibrating the cocomo ii post-architecture model," in ICSE'98: Proceedings of the 20th international conference on Software engineering, (Washington, DC, USA), pp. 477-480, IEEE Computer Society, 1998.
12. S. Chulani and B. Boehm, "Modeling software defect introduction and removal: Coqualmo (constructive quality model)," tech. rep.
13. S. Devnani-Chulani, "Modeling software defect introduction," tech. rep.
14. G. Witting and G. Einnie, "Estimating software developemnt effort with connectionist models," in Proceedings of the Information and Software Technology Conference, pp. 469-476, 1997.
15. H. Zeng and D. Rine, "A neural network approach for software defects fix effort estimation," in Proceedings of the Eighth IASTED International Conference Software Engineering and Applications, pp. 513-517, 2004,
16. S. Kumar, B. A. Krishna, and P. Satsangi, "Fuzzy systems and neural networks in software engineering project management," Journal of Applied Intelligence, vol. 4, pp. 31-52, 1994.
17. A. C. Hodgkinson and P. W. Garratt, "A neuro-fuzzy cost estimator," in Proceedings of the Third Conference on Software Engineering and Applications, pp. 401-406, 1999.
18. J. Ryder, Fuzzy COCOMO: Software Cost Estimation. PhD thesis, Binghamton University, 1995.
19. P. Musílek, W, Pedrycz, G. Succi, and M, Reformat, "Software cost estimation with fuzzy models," SIGAPP Appl. Comput. Rev., vol. 8, no. 2, pp. 24-29, 2000.
20. J, Baik, The Effect of Case Tools on Software Development Effort. PhD thesis, University of Southern California, 2000.
21. C. J. Dolado and M. Lefley, "Can genetic programming improve software effort estimation? a comparative evaluation," Information and software technology, vol. 43, pp. 863-873, 2001,
22. M. Reyalat, "Development of a software reliability growth model using genetic programming," tech. rep., 2005.
23. A. Sheta, "Estimation of the COCOMO model parameters using genetic algorithms for NASA software projects," Journal of Computer Science, USA, vol. 2, no. 2, pp. 118-123, 2006,
24. K. Pillai and S. Nair, "A model for software development effort and cost estimation," IEEE Trans. on Software Engineering, vol. 23, p. 485497, 1997.
25. K. Peters, "Software project estimation," Methods and Tools, vol. 8, no. 2, 2000.
26. B. Boehm, Software Engineering Economics. Englewood Cliffs, NJ, Prentice-Hall, 1981.
27. B. Boehm, Cost Models for Future Software Life Cycle Process: COCOMO2. Annals of Software Engineering, 1995.
28. R. Valerdi, The Constructive Systems Engineering Cost Estimation Model (COSYSMO). PhD thesis, University of Southern California, 2005.
29. C. F. Kemere, "An empirical validation of software cost estimation models," Communication ACM, vol. 30, pp. 416-429, 1987.
30. L. X. Wang, "Fuzzy systems are universal approximators," in Proceedings of IEE Int. Conf. on Fuzzy Sxstems, San Diego, USA, pp. 1163-1170, 1992.
31. D. Dubois and H. Prade, "Fuzzy sets in approximate reasoning: part 1," Fuzzy Sets and Systems, vol. 40, pp. 143-202, 1992,
32. B. Kosko, "Fuzzy systems as universal approximators," in Proceedings of Int. Conf Fuzzy Syst., pp. 1153-1162, 1998.
33. R, Babus̃ka, Fuzzy Modeling and Identification. PhD thesis, Delft Univesrsity of Technology, 1996.
34. H. A, Babus̃ka, R, Braake, A, J. Krijgsman, and H. B. Verbruggen, "Comparison of intelligent control schemes for real-time pressure control," Control Engineering Practice, vol. 4, pp. 1585-1592, 1996.
35. A. Sheta, Modeling the Tennessee Eastman Chemical Reactor Using Fuzzy Logic. New York, USA: Book Chapter. The ISE Book Series on Fuzzy System Engineering-Theory and Practice. Nova Science. ISBN: 3-540-25322-X, 2005.
36. R. Babus̃ka, Fuzzy Modeling for Control. Klumer Academic Publishers, Boston, 1998.
37. R, Babuska, J, A, Roubos, and H. B. Verbruggen, "Identification of MIMO systems by input-output TS fuzzy models," in Proceedings of Fuzzy-IEEE'98, Anchorage, Alaska, 1998,
38. R, Babuska and H. B. Verbruggen, "Applied fuzzy modelings," in Proceedings of IFAC Symposium on Artificial Intelligence in Real Time Control, Valencia, Spain, pp. 61-66, 1994.
39. R. Babuska and H. B. Verbruggen, "Identification of composite linear models via fuzzy clustering," in Proceedings of European Control Conference, Rome, Italy, pp. 1207-1212, 1995.
40. J. M. Sosa, R. Babus̃ka, and H. B. Verbruggen, "Fuzzy predictive control applied to an air-conditioning system," Control Engineering Practice, vol. 5, pp. 1395-1406, 1997.
41. D. E. Gustafson and W. C. Kessel, "Fuzzy clustering with a fuzzy covariance matrix," in Proceedings of the IEEE CDC, San Diego, CA, USA, pp. 761-766, 1979.
42. B. Birge, PSOt, Particle Swarm Optimization Toolbox for Matlab. Available at the MATLAB Central web page, 2005.
43. R, Babus̃ka, Fuzzy Modeling and Identification Toolbox. Delft University of Technology, The Netheriand, http://lcewww.et.tudelft.nl/bubuska, 1998.
44. M. Shin and A. L. Goel, "Emprirical data modeling in software engineering using radial basis functions," IEEE Trans. on Software Engineering, pp. 567-576, 2000.