Software cost estimation using fuzzy logic
ACM SIGSOFT Software Engineering Notes
A new regression based software cost estimation model using power values
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
International Journal of Bio-Inspired Computation
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The accurate prediction of software development costs may have a large economic impact. As a consequence, considerable research attention is now directed to understand better the software development process. The objective of this paper is to provide an experimental evaluation of the applicability, universality, and accuracy of some algorithmic software cost estimating models (COCOMO, TUCOMO, PUTNAM, COPMO, ESSE, and Function Points). Data on nine Italian Management Information Systems projects were collected and used to evaluate the performance of the models. The evaluation of the estimates was based on the Mean Magnitude Relative Error and Prediction at level 25% criteria. Results indicated that the models provided interesting performances, better if recalibrated with local data.