Investigating Effort Prediction of Software Projects on the ISBSG Dataset

Many cost estimation models have been proposed over the last three decades. In this study, we investigate fuzzy ID3 decision tree as a method for software effort estimation. Fuzzy ID software effort estimation model is designed by incorporating the principles of ID3 decision tree and the concepts of the fuzzy settheoretic; permitting the model to handle uncertain and imprecise data when presenting the software projects. MMRE (Mean Magnitude of Relative Error) and Pred(l) (Prediction at level l) are used, as measures of prediction accuracy, for this study. A series of experiments is reported using ISBSG software projects dataset. Fuzzy trees are grown using different fuzziness control thresholds. Results showed that optimizing the fuzzy ID3 parameters can improve greatly the accuracy of the generated software cost estimate.

[1]  Bhekisipho Twala,et al.  Comparison of various methods for handling incomplete data in software engineering databases , 2005, 2005 International Symposium on Empirical Software Engineering, 2005..

[2]  Cezary Z. Janikow,et al.  Fuzzy decision trees: issues and methods , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[3]  Jean-Marc Desharnais,et al.  A comparison of software effort estimation techniques: Using function points with neural networks, case-based reasoning and regression models , 1997, J. Syst. Softw..

[4]  Martin J. Shepperd,et al.  Estimating Software Project Effort Using Analogies , 1997, IEEE Trans. Software Eng..

[5]  Kjetil Moløkken-Østvold,et al.  A review of software surveys on software effort estimation , 2003, 2003 International Symposium on Empirical Software Engineering, 2003. ISESE 2003. Proceedings..

[6]  Richard Weber,et al.  Fuzzy-ID3: A class of methods for automatic knowledge acquisition , 1992 .

[7]  Ali Idri,et al.  Applying Fuzzy ID3 Decision Tree for Software Effort Estimation , 2011, ArXiv.

[8]  Alberto Maria Segre,et al.  Programs for Machine Learning , 1994 .

[9]  Cornelio Yáñez-Márquez,et al.  Software development effort estimation using fuzzy logic: a case study , 2005, Sixth Mexican International Conference on Computer Science (ENC'05).

[10]  Wei-Yin Loh,et al.  Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..

[11]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .

[12]  Barry W. Boehm,et al.  Software Engineering Economics , 1993, IEEE Transactions on Software Engineering.

[13]  Witold Pedrycz,et al.  The design of decision trees in the framework of granular data and their application to software quality models , 2001, Fuzzy Sets Syst..

[14]  Alain Abran,et al.  COCOMO cost model using fuzzy logic , 2000 .

[15]  A. Abran,et al.  An Experiment on the Design of Radial Basis Function Neural Networks for Software Cost Estimation , 2006, 2006 2nd International Conference on Information & Communication Technologies.

[16]  Helmut Berger,et al.  Exploiting partial decision trees for feature subset selection in e-mail categorization , 2006, SAC.

[17]  W. Pedrycz,et al.  A fuzzy set approach to cost estimation of software projects , 1999, Engineering Solutions for the Next Millennium. 1999 IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.99TH8411).

[18]  Vishal Sharma,et al.  Optimized Fuzzy Logic Based Framework for Effort Estimation in Software Development , 2010, ArXiv.

[19]  Yong-Ji Wang,et al.  Software Development Effort Estimation Using Fuzzy Logic - A Survey , 2008, 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery.

[20]  C.Z. Janikow,et al.  Fuzzy decision tree FID , 2005, NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society.

[21]  Kjetil Molkken,et al.  A Review of Surveys on Software Effort Estimation , 2003 .

[22]  M. Fajfer,et al.  Fuzzy partitioning with FID3.1 , 1999, 18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397).

[23]  Marcel Korte,et al.  Confidence in software cost estimation results based on MMRE and PRED , 2008, PROMISE '08.

[24]  Adam A. Porter,et al.  Learning from Examples: Generation and Evaluation of Decision Trees for Software Resource Analysis , 1988, IEEE Trans. Software Eng..

[25]  I. Hatono,et al.  Fuzzy decision trees by fuzzy ID3 algorithm and its application to diagnosis systems , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.

[26]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.