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Fuzzy Identification, , EAF, Development Effort

Software development effort prediction is one of the most significant activity in software project management. The literature shows several algorithmic cost estimation models such as Boehm’s COCOMO, Albrecht's' Function Point Analysis, Putnam’s SLIM, ESTIMACS etc, but each do have their own pros and cons in estimating development cost and effort. This is because project data, available in the initial stages of project is often incomplete, inconsistent, uncertain and unclear. The need for accurate effort prediction in software project management is a challenge till today. Fuzzy logic-based estimation models are more apt when vague and inaccurate information is to be used. In the present paper software development effort prediction using Fuzzy triangular and GBell membership functions is presented and compared with COCOMO. A case study based on the COCOMO81 database compares the proposed fuzzy model with the Intermediate COCOMO. The results were analyzed using five different criterions VAF, MARE, VARE, Prediction and BRE. It is observed that the fuzzy model using triangular membership function provided better results