MODELING THE PROBABILISTIC BEHAVIOR OF FUNCTION POINT ANALYSIS

Function point analysis is one of the most popular methods for estimat ing software size and, sometimes, development effort. However, accurac y for the result of estimation by using this method has not been ascer tained significantly. Depending on human professional subjective judge ment is one major reason that causes this problem. Subjective judgemen t may lead to inconsistency and inaccuracy in the estimation process. Fuzzified function point analysis model (FFPA) is proposed (C. Yau and R.H.L. Tsoi, Assessing the fuzziness of general system characteristic s for estimating software size, ANZIIS Conference, Brisbane, Australia , Nov. 1994; C. Yau and R.H.L. Tsoi, A fuzzified approach to overcome the imprecisions of software sizing, IEEE SICICI '95, Singapore, July 1995.) to help software size estimators express their judgement in a m ore realistic manner. Surely, arangements given by FFPA will provide m ore information and can reflect the real life situation, but it does n ot show the confidence interval. Therefore, it is no way to assess the confidence level of the estimate. This paper will discuss the way to use fuzzy B-spline membership function (BMF) to derive the assessment values for 14 system characteristics of FFPA model. At the end of this paper, an empirical case study will show the merits of using confiden ce level in the estimate. These results imply that there may be potent ial for improving the way of using the estimation's result in differen t application environments. (C) 1998 Elsevier Science B.V.