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Impact of Complexity on Reusability in OO Systems

机译:复杂性对面向对象系统中可重用性的影响

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摘要

In the position paper, we described an experiment to verify a hypothesis of correlation between reusability and a quantitative attribute of a software (volume and complexity). In the experiment, we used a machine learning approach consisting of a machine learning algorithm (C4.5). The results of our experiment show that the selected metrics can predict with a high level of accuracy the classes that can be potentially reusable. The predictive model obtained (volume and complexity) gives a very satisfactory results (89,3% of accuracy).
机译:在立场文件中,我们描述了一个实验,以验证可重用性与软件的定量属性(数量和复杂性)之间的相关关系的假设。在实验中,我们使用了包含机器学习算法(C4.5)的机器学习方法。我们的实验结果表明,选定的指标可以高度准确地预测可能可重复使用的类。获得的预测模型(数量和复杂性)给出了非常令人满意的结果(准确度为89.3%)。

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