  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 todays 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.
