Algorithmic Based and Non-Algorithmic Based Approaches to Estimate the Software Effort

Software effort estimation is the key task for the effective project management. It is widely used for planning and monitoring software project development as a means to deliver the product on time and within budget. So far, no model has been proved to be successful at effectively and accurately estimating software development effort. So it is useful to research a particular model for a particular type of project. This paper present an approach for small organic project, based on our previous work. Besides using GaussNewton model to calibrate the parameters of the COCOMO, using Fuzzy logic algorithm to optimize it, we also imply Deming Regression, Expert judgment, and Machine learning to improve this model. This model is based on historical project data. Experimental results show that the model is effective for software estimation. The accuracy comparison of each model is presented.

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