文章基本信息

标题：Ant Colony Optimization Based Software Effort Estimation
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作者：Nishu Dewan ; Sumeet Kaur Sehra
期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2014
卷号：5
期号：3
页码：53-56
语种：English
出版社：Ayushmaan Technologies
摘要：Accurate software development cost estimation is important for effective project management such as budgeting, project planning and control. Nowadays there are many models for software development cost estimation, providing project managers with helpful information to make the right decisions. One of such well known mathematical models is the COCOMO model. To estimate costs and time, this model uses coefficients, which were determined in 1981 by means of the regression analysis of statistical data based on 63 different types of project data. Using these coefficients for a modern project, the appraisal may not be accurate; therefore, the aim of this work is to optimize the model coefficients with ant colony optimization algorithms. Firstly, collect and clean the data. The outliers are removed during analyzing the data. Then different paths are generated by ants. The best path is selected by using Ant colony optimization algorithm. The performance of the system is analyzed by mean magnitude of relative error. The percent improvement of proposed model over COCOMO model is 92.29%.
关键词：COCOMO Model;Ant Colony Optimization;Software Effort Estimation;MMRE