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design pattern mining Using Graph Matching

Wuhan University Journal of Natural Sciences 2004年第4期9卷 444-448页

作者： LIQing-hua ZHANGZhi-xiang BENKe-rong SchoolofComputerScienceandTechnology HuazhongUniversityofScienceandTechnologyWuhan430074HubeiChina DepartmentofComputerScience NavalUniversityofEngineeringWuhan430033HubeiChina

The identification of design pattern instances is important for program understanding and software maintenance. Aiming at the mining of design patterns in existing systems, this paper proposes a subgraph isomorphism approach to discover several design patterns in a legacy system at a time. The attributed relational graph is used to describe design patterns and legacy systems. The sub-graph isomorphism approach consists of decomposition and composition process. During the decomposition process, graphs corresponding to the design patterns are decomposed into sub-graphs, some of which are graphs corresponding to the elemental design patterns. The composition process tries to get sub-graph isomorphism of the matched graph if sub-graph isomorphism of each subgraph is obtained. Due to the common structures between design patterns, the proposed approach can reduce the matching times of entities and relations. Compared with the existing methods, the proposed algorithm is not linearly dependent on the number of design pattern graphs. Key words design pattern mining - attributed relational graph - subgraph isomorphism CLC number TP 311.5 Foundation item: Supported by the National Natural Science Foundation of China (60273075) and the Science Foundation of Naval University of Engineering (HGDJJ03019)Biography: LI Qing-hua (1940-), male, Professor, research direction: parallel computing.

关键词： design pattern mining attributed relational graph subgraph isomorphism

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Software design pattern mining using classification-based techniques

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Frontiers of Computer Science 2018年第5期12卷 908-922页

作者： Ashish Kumar DWIVEDI Anand TIRKEY Santanu Kumar RATH Department of Computer Science and Engineering National Institute of Technology Rourkela 769008 India

design patterns are often used in the development of object-oriented software. It offers reusable abstract information that is helpful in solving recurring design problems. Detecting design patterns is beneficial to the comprehension and maintenance of object-oriented software systems. Several pattern detection techniques based on static analysis often encounter problems when detecting design patterns for identical structures of patterns. In this study, we attempt to detect software design patterns by using software metrics and classification-based techniques. Our study is conducted in two phases： creation of metrics-oriented dataset and detection of software design patterns. The datasets are prepared by using software metrics for the learning of classifiers. Then, pattern detection is performed by using classification-based techniques. To evaluate the proposed method, experiments are conducted using three open source software programs, JHotDraw, QuickUML, and JUnit, and the results are analyzed.

关键词： design patterns design pattern mining machinelearning techniques object-oriented metrics

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