Software design pattern mining using classification-based techniques
Software design pattern mining using classification-based techniques作者机构：Department of Computer Science and Engineering National Institute of Technology Rourkela 769008 India
出 版 物：《Frontiers of Computer Science》 (中国计算机科学前沿（英文版）)
年 卷 期：2018年第12卷第5期
页 面：908-922页
核心收录：
学科分类：081702[工学-化学工艺] 08[工学] 0817[工学-化学工程与技术] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：Birla Institute of Technology Mesra Department of Computer Science and Engineering Petri Net Society Uttar Pradesh Technical University National Institute of Technology Rourkela, NITR
主 题：design patterns design pattern mining machinelearning techniques object-oriented metrics
摘 要：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.
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