Improving the accuracy of CBSD effort estimation using fuzzy logic

One of the most important issues in effort estimation is accuracy of size measure methods, because accuracy of estimation depends upon the accurate prediction of size. Prediction of size is depends upon project data,Most of the time in initial stages project data is imperfect and ambiguous this leads to imprecision in its output thereby resulting in erroneous effort estimation using Constructive Cost Model (COCOMO-II) Model. Today's software development is component based and that makes effort estimation process difficult due to the black box nature of component. Also traditional method does not support the component based software development effort estimation. Now the method which support accurate size prediction in component based software development is too much important for accurate effort estimation. Fuzzy logic based cost estimation model address the imperfect and ambiguousness present in Constructive Cost Model (COCOMO-II) models to make reliable and accurate estimation of effort. Component point method supports the accurate size prediction for component based software development which leads to accurate effort estimation in CBSD. The first aim of this paper is to show with comparisons the importance of size measure methods for accurate effort estimation. Paper shows component point is the best method for accurate size prediction in component black box nature. The second aim of this paper is to analyze the use of fuzzy logic in COCOMO-II model to address the imprecision present in its input and suggested four new cost drivers to improve the accuracy of effort estimation.