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Basic cocomo mmodel program in c software#
Many software models were presented in the literature to handle this task such as expert judgment, analogy-based estimation, formal estimation models and combination-based estimation models.
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To do that the expected software development size has to be estimated early in the development process. An inaccurate estimate will lead to money and market share loss. Companies have to estimate the effort, time and cost before bidding for a project. Ĭorrect cost estimates is an essential element to develop economic proposals and being competitive in the market. The validation of results is carried out based on Albrecht data set1. Developed results show that neural network models can provide competitive results compared to other reported results in the literature. One model utilizes the Kilo Line Of Code (KLOC) as input variable to estimate the Effort (E) while the second model utilizes the Inputs, Outputs, Files, and User Inquiries to estimate the Function Point (FP) of software project. In this paper, we develop two new non-parametric models for software effort estimation using Artificial Neural Networks. Non-parametric Soft Computing techniques can offer a better effort estimate compared to traditional parametric software cost-estimation models in the literature. Software size is one of the main cost drivers.
![basic cocomo mmodel program in c basic cocomo mmodel program in c](https://image.slidesharecdn.com/cocomomodel-190531183615/95/cocomo-model-8-638.jpg)
An inaccurate estimate may lead to money and market share loss. Companies should compute an effort estimate before proceeding to a competition to win a bid. Correct cost estimates are a vital component for developing economic proposals and being competitive in the market.
![Basic cocomo mmodel program in c](https://kumkoniak.com/20.jpg)