A general framework to improve software estimation

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The ability of software engineers to assess projects accurately is a vital issue in the software management discipline. There have been countless attempts in software engineering to identify a specific model, tool, or technique that could be used to solve the challenges of software estimation; unfortunately, most of them have not succeeded. On the other hand, our novel approach to making effort and size estimations shows that a combination of neuro-fuzzy techniques and algorithmic models can greatly improve the accuracy of software project estimation. The results of our work over the past six years have confirmed that, as compared to the use of an algorithmic model alone, the combined neuro-fuzzy framework can produce more accurate software estimations. One paramount feature of our framework is that its architecture is inherently independent of the choice of the algorithmic models or the nature of the prediction problem.