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首页> 外文期刊>International journal of system of systems engineering >Mining patterns in open source software using software metrics and neural network models
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Mining patterns in open source software using software metrics and neural network models

机译:使用软件指标和神经网络模型的开源软件中的挖掘模式

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摘要

As the complexity of a system increases, the need to develop a prototype for the problems becomes more and more prominent. To take care of different plan issues, it is seen that structure design finds a superior answer for a large number of repetitive plan issues. For the most part, design-level documents are indicated utilising semi-formal documentation, for example, unified modelling language (UML) diagrams. In any case, these kinds of semi-formal documentation lead to ambiguities and irregularities. In this paper, design level documents are retrieved by using the idea of program metrics. The proposed methodology retrieves the reusable documents from the open-source software such as PMD and JUnit. The presented method uses three kinds of neural network models to analyse the effectiveness of the pattern retrieval approach.
机译:随着系统的复杂性增加,需要开发出问题的原型变得越来越突出。为了照顾不同的计划问题,可以看出,结构设计找到了大量重复计划问题的卓越答案。在大多数情况下,使用半正式文档指示设计级别文档,例如统一建模语言(UML)图。在任何情况下,这些半正式文件都会导致歧义和违规行为。在本文中,通过使用程序度量的思想来检索设计级别文档。所提出的方法从诸如PMD和JUnit等开源软件中检索可重用文档。该方法采用三种神经网络模型来分析模式检索方法的有效性。

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