A min-max Approach for Improving the Accuracy of Effort Estimation of COCOMO
H. S. Hota1, Ramesh Pratap Singh2
1H. S. Hota, Department of CS & IT, Guru Ghasidas Vishwavidyalaya (A central university), Bilaspur, India.
2Ramesh Pratap Singh, Department of Computer Science, D. P. Vipra College, Bilaspur, India.
Manuscript received on June 18, 2011. | Revised Manuscript received on June 28, 2011. | Manuscript published on July 05, 2011. | PP: 74-79 | Volume-1 Issue-3, July 2011. | Retrieval Number: C061061311
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This study proposed to extend the Constructive Cost Model (COCOMO) by incorporating the concept of min-max approach to estimation. Formal effort estimation models like Constructive Cost Model (COCOMO) are limited by their inability to manage uncertainties and imprecision surrounding software projects early in the development life cycle. A min-max approach is suggested to rectify data uncertainties and modeling errors. The proposed method of min-max is used to improve the accuracy of effort estimation of COCOMO and its result have been compared with the gradient descent, robust fuzzy clustering, k-mean clustering methods of estimation. It has been observed that the proposed method have lowest and steady state absolute estimate error AE(k) and mean absolute estimate error MAE(k) for different value of k(time series) and different step-size s.
Keywords: Sugeno fuzzy inference system, min-max method, Constructive Cost Model (COCOMO), effort estimation, Absolute Estimate Error, Mean Absolute Estimate Error.