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• W2017197710 abstract "Function point analysis is one of the most popular methods for estimating software size and, sometimes, development effort. However, accuracy for the result of estimation by using this method has not been ascertained significantly. Depending on human professional subjective judgement is one major reason that causes this problem. Subjective judgement 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 characteristics 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 more realistic manner. Surely, arangements given by FFPA will provide more information and can reflect the real life situation, but it does not 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 confidence level in the estimate. These results imply that there may be potential for improving the way of using the estimation's result in different application environments." @default.
• W2017197710 created "2016-06-24" @default.
• W2017197710 creator A5000462019 @default.
• W2017197710 creator A5024328799 @default.
• W2017197710 date "1998-01-01" @default.
• W2017197710 modified "2023-09-27" @default.
• W2017197710 title "Modelling the probabilistic behaviour of function point analysis" @default.
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• W2017197710 doi "https://doi.org/10.1016/s0950-5849(98)00032-9" @default.
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