Affiliations: [a] HSBC Bank Canada, IT Department, Vancouver, Canada | [b] NFA Estimation Inc., London, Canada | [c] University of Western Ontario, Department of Electrical & Computer Engineering, London, Canada | [d] United Arab Emirates University, College of Information Technology, Al-Ain, United Arab Emirates
Note: [1] Dr. L.F. Capretz is currently spending his sabbatical leave in the Department of Computer Science at the University of Sharjah, United Arab Emirates.
Abstract: While software development productivity has grown rapidly, the weight values assigned to count standard Function Point (FP) created at IBM twenty-five years ago have never been updated. This obsolescence raises critical questions about the validity of the weight values; it also creates other problems such as ambiguous classification, crisp boundary, as well as subjective and locally defined weight values. All of these challenges reveal the need to calibrate FP in order to reflect both the specific software application context and the trend of today's software development techniques more accurately. We have created a FP calibration model that incorporates the learning ability of neural networks as well as the capability of capturing human knowledge using fuzzy logic. The empirical validation using ISBSG Data Repository (release 8) shows an average improvement of 22% in the accuracy of software effort estimations with the new calibration.
Keywords: Function point analysis, software size measure, effort prediction model, software estimation
