Adaptive Design Pattern Detection Model: A Nearness Measurement Approach

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Shanker Rao A
M.A Jabbar, Srikanth. Jatla


The discovery of design pattern as part of reengineering methods will convey necessary data to the designer. However, existing pattern detection methodologies typically have issues in managing one or additional of the subsequent issues: Identification of changed pattern versions, search area explosion for big systems and extensibility to novel patterns. A style pattern detection methodology is proposed that's based mostly on match gain between graph vertices. Attributable to the character of the underlying graph algorithm, this approach has the power to conjointly acknowledge patterns that are changed from their normal illustration. Moreover, the approach exploits the very fact that patterns reside in one or additional inheritance hierarchies, reducing the dimensions of the graphs to that the algorithm is applied. Finally, the algorithm doesn't suppose any pattern-specific heuristic, facilitating the extension to novel style structures. Analysis on 3 open-source comes demonstrated the accuracy and therefore the potency of the proposed methodology.


Keywords: Design patterns, GoF, JHotDraw, jRefactory, jUnit and Decision Tree.


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