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Estimating Development Time of Software Projects Using a Neuro Fuzzy Approach

Authors: Venus Marza, Amin Seyyedi, Luiz Fernando Capretz


Software estimation accuracy is among the greatest challenges for software developers. This study aimed at building and evaluating a neuro-fuzzy model to estimate software projects development time. The forty-one modules developed from ten programs were used as dataset. Our proposed approach is compared with fuzzy logic and neural network model and Results show that the value of MMRE (Mean of Magnitude of Relative Error) applying neuro-fuzzy was substantially lower than MMRE applying fuzzy logic and neural network.

Keywords: Fuzzy Logic, Artificial Neural Network, software estimation, neuro-fuzzy

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[1] H. Park, S. Baek, "An empirical validation of a neural network model for software effort estimation", Expert Systems with Applications, 2007.
[2] C. Lopez-Martin, C.Yanez-Marquez, A.Gutierrez-Tornes, "Predictive accuracy comparison of fuzzy models for software development effort of small programs, The journal of systems and software", Vol. 81, Issue 6, 2008, pp. 949-960.
[3] J. Jantzen, "Neuro-fuzzy modeling", Report no 98-H-874, 1998.
[4] W. Xia, L.F. Capretz, D. Ho, F.Ahmed, "A new calibration for function point complexity weights", Information and Software Technology, Vol.50, Issue 7-8, 2007, pp.670-683.
[5] M. Jorgensen, B. Faugli, T. Gruschke, "Characteristics of software engineers with optimistic prediction", Journal of Systems and Software, Vol. 80, Issue. 9, 2007, pp. 1472-1482.
[6] C.L. Martin, J.L. Pasquier, M.C. Yanez, T.A. Gutierrez, "Software Development Effort Estimation Using Fuzzy Logic: A Case Study", IEEE Proceedings of the Sixth Mexican International Conference on Computer Science (ENC-05), 2005, pp. 113-120.
[7] M.T. Su, T.C.Ling, K.K.Phang, C.S.Liew, P.Y.Man, "Enhanced Software Development Effort and Cost Estimation Using Fuzzy Logic Model", Malaysian Journal of Computer Science, Vol. 20, No. 2, 2007, pp. 199-207.
[8] A. Heiat, "Comparison of artificial neural network and regression models for estimating software development effort", Information and Software Technology, Vol. 44, Issue 15, 2002, pp. 911-922.
[9] X. Huang, Danny Ho, J. Ren, L.F. Capretz, "Improving the COCOMO model using a neuro-fuzzy approach", Applied Soft Computing , Vol.7, Issue 1, 2007, pp. 29-40.
[10] A. Idri, A.Abran, "A Fuzzy Logic Based Set of Measures for Software Project Similarity: Validation and Possible Improvements", Proceedings of the seventh international software metrics symposium (METRICS -01), 2001, pp.85-96.
[11] S.N. Sivanandam, S. Sumathi, S.N. Deepa, "Introduction to fuzzy logic using MATLAB", Springer, 2007.
[12] A. Lotfi Zadeh, "From Computing with Numbers to Computing with Words - From Manipulation of Measurements to Manipulation of Perceptions", IEEE Transactions on Circuits and Systems, Fundamental Theory and Applications, Vol. 45, No 1, 1999, pp 105-119.
[13] M.R.Braz & S.R.Vergilio, "Using Fuzzy Theory for Effort Estimation of Object-Oriented Software", Proceedings of the 16th IEEE international Conference on Tools with Artificial Intelligence (ICTAI 2004), 2004, pp. 196-201.
[14] K.K.Aggarwal, Y.Singh, P.Chandra, M.Puri, "Sensitivity Analysis of Fuzzy and Neural Network Models", ACM SIGSOFT Software Engineering Notes, Vol. 30, Issue 4, 2005, pp. 1-4.
[15] A.A. Moataz, O.S.Moshood, A.Jarallah, "Adaptive fuzzy-logic-based framework for software development effort prediction", Information and Software Technology, Vol. 47, Issue 1, 2005, pp. 31-48.
[16] W.S. Humphrey, "A Discipline for Software Engineering", Addison Wesley, 2002.
[17] S. Mitra, Y.Hayashi, "Neuro-Fuzzy Rule Generation: Survey in Soft Computing Framework", IEEE Transactions on Neural Networks, Vol.11, No.3, 2000, pp. 748-768.
[18] D. Nauck, F. Klawonn, R. Kruse, "Foundations of Neuro-Fuzzy Systems", Wiley, Chichester, 1997.
[19] D. Nauck, "A Fuzzy Perceptron as a Generic Model for Neuro-Fuzzy Approaches", In Proceedings of Fuzzy-Systeme-94, 2nd GI-Workshop, Munich, Semen Corporation, 1994.
[20] M.O. Saliu, "Adaptive Fuzzy Logic Based Framework for Software Development Effort Prediction", A Thesis Presented to the DEANSHIP OF GRADUATE STUDIES, King Fahd University of Petroleum & Minerals Dhahran, April 2003.
[21] A. Abraham, "Adaptation of Fuzzy Inference System Using Neural Learning", Springer-Verlag Berlin Heidelberg, 2005, pp. 59-83.
[22] Y. Shi, M. Mizumoto, N.Yubazaki, M. Otani, "A Learning Algorithm for Tuning Fuzzy Rules Based on the Gradient Descent Method", Proceedings of Fifth IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'96), New Orleans, USA, Vol.1, 1996, pp.55-61.
[23] V. Xia, L. F. Capretz, D. Ho, "A Neuro-Fuzzy Model for Function Point Calibration", WSEAS Transactions on Information Science & Applications, Vol. 5, Issue 1, 2008, pp. 22-30.