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首页> 外文期刊>International journal of knowledge management studies >Knowledge based non-functional software distinguishing quality effort estimation using fuzzy use case point approach
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Knowledge based non-functional software distinguishing quality effort estimation using fuzzy use case point approach

机译：基于知识的非功能软件，使用模糊用例点法来区分质量工作量估计

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摘要

Knowledge management along with data analytic process provides the collection of information which helps to examine both qualitative and quantitative software information. During the knowledge based data examination process, software effort estimation (SEE) is an organised approach to increase the efficiency of a software development process in various organisations. Software effort estimation based on use case point (UCP) methods provides only fixed estimation value which cannot deal with the uncertain and ambiguous conditions of the particular software. This work attempts to provide a fuzzy effort estimation procedure for use case model based on fuzzy inference rules. This paper also proposes a metric to calculate the enhanced UCPs with the fuzzy membership function for examining the software distinguishing quality. The proposed approach has been validated against the goal-driven UCP model, tree-boost model, Regression model and traditional use-case model. The obtained results show the better performance than those obtained by the existing methods.
机译：知识管理以及数据分析过程提供了信息收集，有助于检查定性和定量软件信息。在基于知识的数据检查过程中，软件工作量估算（SEE）是一种有组织的方法，可以提高各个组织中软件开发过程的效率。基于用例点（UCP）方法的软件工作量估计仅提供固定的估计值，而该估计值不能处理特定软件的不确定性和歧义条件。这项工作试图为基于模糊推理规则的用例模型提供一个模糊的工作量估计程序。本文还提出了一种利用模糊隶属度函数计算增强型UCP的度量方法，以检验软件的区分质量。该方法已针对目标驱动的UCP模型，树提升模型，回归模型和传统用例模型进行了验证。获得的结果显示出比通过现有方法获得的结果更好的性能。

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