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Standing on the Shoulders of Giants - A Data Fusion Approach to Design Pattern Detection

机译:站在巨人的肩膀上 - 一种设计模式检测的数据融合方法

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Identification of design patterns can deliver important information to designers. Therefore, automated design pattern detection (DPD) is highly desirable when it comes to understanding unknown code. In this paper, we present the results of evaluating five existing DPD tools on various Java projects. These results motivate our proposal of a novel DPD approach based on data fusion. It combines design pattern candidate sets coming from different tools implementing different DPD techniques. We show that a design pattern can be a witness for the existence of another pattern. Our approach is able (1) to provide correct diagnostics even if the inputs from the evaluated tools were partly wrong and (2) to detect patterns instances not identified by the individual tools. For the Decorator, Visitor and Observer pattern, the witness-based approach yields better precision and recall than provided by any single tool. In particular, it detects 24 out of 30 instances of these patterns missed in our experiments by the evaluated tools. We also found that on the analyzed instances of the Bridge, Mediator and Facade pattern data fusion could not improve results, demonstrating that research into improvements of the basic detection techniques is still necessary.
机译:设计模式可以识别给设计师提供重要信息。因此,自动化设计图案检测(DPD)是高度期望的,当涉及到理解未知代码。在本文中,我们提出评估各种Java项目现有五个DPD工具的结果。这些结果激励我们基于数据融合的一种新的DPD方法的建议。它结合了设计模式候选集,从不同的实现技术DPD不同的工具来。我们发现,一个设计模式可以是另一种模式的存在见证。我们的做法是能够(1)提供即使从评估工具的投入是部分错误和(2)来检测不是由单独的工具识别的模式情况下正确的诊断。对于装饰,游客和Observer模式,基于证人的做法产生比任何单一工具提供了更好的精确度和召回。特别是,它检测到24这些模式由评估工具,在我们的实验错过的30个实例。我们还发现,在桥的分析情况,调解员和Facade模式数据融合不能改善的结果,证明了研究的基本检测技术的改进仍然是必要的。

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