EXTRACTOR:用于识别面向方面重构机会的可扩展框架

2011 International Conference on System science, Engineering design and Manufacturing informatization Pub Date : 2011-11-18 DOI:10.1109/ICSSEM.2011.6081283

Jin Huang, F. Carminati, L. Betev, Jianlin Zhu, C. Luzzi

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引用次数: 2

摘要

自动重构技术保证了遗留软件系统转换的正确性和有效性。由于复合重构的复杂性和面向方面重构的行为保留，现有的技术不能有效地识别重构机会。为了应对这些挑战，我们设计了EXTRACTOR，它是一个可扩展的框架，用于识别面向方面的重构机会。在框架中，臭味检测器提供了检测臭味的重要查询功能，而模板管理器支持自定义臭味和组合重构。然后使用EXTRACTOR构造器管理的逻辑转换识别重构机会。所有这些功能都基于逻辑查询引擎，该引擎管理程序的逻辑表示。最后，通过案例分析说明了该框架的有效性。

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EXTRACTOR: An extensible framework for identifying Aspect-Oriented refactoring opportunities

Automatic refactoring techniques guarantee the correctness and effectiveness for the transformation of legacy software systems. Existing techniques are not effective to identify refactoring opportunities because of the complexity of composite refactoring and the behavior preservation for Aspect-Oriented refactoring. To address these challenges, we design EXTRACTOR, which is an extensible framework to identify Aspect-Oriented refactoring opportunities. In the framework, the bad smell detector provides significant query ability to detect bad smells, while the template manager enables the customization of bad smell and composite refactoring. Then refactoring opportunities are identified using logic transformation managed by EXTRACTOR Constructor. All these functionalities are based on the logic query engine, which manages the logic representation of programs. Finally we illustrate the effectiveness of the framework using case study.

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2011 International Conference on System science, Engineering design and Manufacturing informatization

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