期刊名称：International Journal of Software Engineering & Applications (IJSEA)
印刷版ISSN：0976-2221
电子版ISSN：0975-9018
出版年度：2012
卷号：3
期号：2
页码：119
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Accurately estimating the software size, cost, effort and schedule is probably the biggest challenge facingsoftware developers today. It has major implications for the management of software development becauseboth the overestimates and underestimates have direct impact for causing damage to software companies.Lot of models have been proposed over the years by various researchers for carrying out effort estimations.Also some of the studies for early stage effort estimations suggest the importance of early estimations. Newparadigms offer alternatives to estimate the software development effort, in particular the ComputationalIntelligence (CI) that exploits mechanisms of interaction between humans and processes domainknowledge with the intention of building intelligent systems (IS). Among IS, Artificial NeuralNetwork and Fuzzy Logic are the two most popular soft computing techniques for software developmenteffort estimation. In this paper neural network models and Mamdani FIS model have been used to predictthe early stage effort estimations using the student dataset. It has been found that Mamdani FIS was able topredict the early stage efforts more efficiently in comparison to the neural network models based models.
