Design Pattern Detection Using Similarity Scoring
Design Pattern Detection Using Similarity Scoring
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DOI：
10.1109/tse.2006.112
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发表时间：
2006-11
影响因子：
7.4
通讯作者：
Nikolaos Tsantalis;A. Chatzigeorgiou;G. Stephanides;Spyros T. Halkidis
中科院分区：
文献类型：
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作者：
Nikolaos Tsantalis;A. Chatzigeorgiou;G. Stephanides;Spyros T. Halkidis
设计模式作为重新设计过程的一部分的识别可以将重要信息传达给设计师。但是，现有的模式检测方法通常在处理以下一个或多个问题时存在问题：识别修改的模式版本，大型系统的搜索空间爆炸以及对新型模式的可扩展性。在本文中，提出了一种基于图形顶点之间的相似性评分的设计模式检测方法。由于基础图算法的性质，该方法也能够识别从其标准表示形式修改的模式。此外，该方法利用了以下事实：模式位于一个或多个继承层次结构中，从而减少了应用算法的图表大小。最后，该算法不依赖于任何特定于模式的启发式，从而促进了新型设计结构的扩展。对三个开源项目的评估证明了该方法的准确性和效率
The identification of design patterns as part of the reengineering process can convey important information to the designer. However, existing pattern detection methodologies generally have problems in dealing with one or more of the following issues: identification of modified pattern versions, search space explosion for large systems and extensibility to novel patterns. In this paper, a design pattern detection methodology is proposed that is based on similarity scoring between graph vertices. Due to the nature of the underlying graph algorithm, this approach has the ability to also recognize patterns that are modified from their standard representation. Moreover, the approach exploits the fact that patterns reside in one or more inheritance hierarchies, reducing the size of the graphs to which the algorithm is applied. Finally, the algorithm does not rely on any pattern-specific heuristic, facilitating the extension to novel design structures. Evaluation on three open-source projects demonstrated the accuracy and the efficiency of the proposed method