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首页> 外文期刊>Procedia Computer Science >Clustering and Classification of Software Component for Efficient Component Retrieval and Building Component Reuse Libraries
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Clustering and Classification of Software Component for Efficient Component Retrieval and Building Component Reuse Libraries

机译：用于有效组件检索和构建组件复用库的软件组件的聚类和分类

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A Software Repository is a collection of library files and function codes. Programmers and Engineers design develop and build software libraries in a continuous process. Selecting suitable function code from one among many in the repository is quite challenging and cumbersome as we need to analyze semantic issues in function codes or components. Clustering and Mining Software Components for efficient reuse is the current topic of interest among researchers in Software Reuse Engineering and Information Retrieval. A relatively less research work is contributed in this field and has a good scope in the future. In this paper, the main idea is to cluster the software components and form a subset of libraries from the available repository. These clusters thus help in choosing the required component with high cohesion and low coupling quickly and efficiently. We define a similarity function and use the same for the process of clustering the software components and for estimating the cost of new project. The approach carried out is a feature vector based approach.
机译：软件库是库文件和功能代码的集合。程序员和工程师设计以连续的过程开发和构建软件库。从存储库中的众多功能中选择合适的功能代码非常具有挑战性和麻烦，因为我们需要分析功能代码或组件中的语义问题。集群和挖掘软件组件以实现有效的复用是软件复用工程和信息检索研究人员当前关注的主题。在该领域的研究工作相对较少，并且在将来具有广阔的前景。在本文中，主要思想是对软件组件进行聚类，并从可用存储库中形成库的子集。因此，这些集群有助于快速有效地选择具有高内聚力和低耦合的所需组件。我们定义一个相似性函数，并将其用于群集软件组件的过程以及估算新项目的成本。所执行的方法是基于特征向量的方法。

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