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首页> 外文期刊>Journal of computer sciences >Estimation of the COCOMO Model Parameters Using Genetic Algorithms for NASA Software Projects | Science Publications
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Estimation of the COCOMO Model Parameters Using Genetic Algorithms for NASA Software Projects | Science Publications

机译:NASA软件项目使用遗传算法估算COCOMO模型参数|科学出版物

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> Defining the project estimated cost, duration and maintenance effort early in the development life cycle is a valuable goal to be achieved for software projects. Many model structures evolved in the literature. These model structures consider modeling software effort as a function of the developed line of code (DLOC). Building such a function helps project managers to accurately allocate the available resources for the project. In this study, we present two new model structures to estimate the effort required for the development of software projects using Genetic Algorithms (GAs). A modified version of the famous COCOMO model provided to explore the effect of the software development adopted methodology in effort computation. The performance of the developed models were tested on NASA software project dataset [1].The developed models were able to provide a good estimation capabilities.
机译: >在开发生命周期的早期定义项目的估计成本,持续时间和维护工作是软件项目要实现的重要目标。文献中发展了许多模型结构。这些模型结构将建模软件的工作量视为已开发代码行(DLOC)的函数。构建这样的功能有助于项目经理为项目准确分配可用资源。在这项研究中,我们提出了两个新的模型结构,以估算使用遗传算法(GA)开发软件项目所需的工作量。提供了著名的COCOMO模型的修改版本,以探索软件开发方法在工作量计算中的作用。在NASA软件项目数据集上测试了开发模型的性能[1]。开发模型能够提供良好的估计能力。

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