Estimating Development Time of Software Projects Using a Neuro Fuzzy Approach
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.
[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.
[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.
@article{"International Journal of Information, Control and Computer Sciences:54822", author = "Venus Marza and Amin Seyyedi and Luiz Fernando Capretz", title = "Estimating Development Time of Software Projects Using a Neuro Fuzzy Approach", abstract = "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 = "Artificial Neural Network, Fuzzy Logic, Neuro-Fuzzy, Software Estimation", volume = "2", number = "10", pages = "3353-5", }
