Jin Huang, F. Carminati, L. Betev, Jianlin Zhu, C. Luzzi
{"title":"EXTRACTOR: An extensible framework for identifying Aspect-Oriented refactoring opportunities","authors":"Jin Huang, F. Carminati, L. Betev, Jianlin Zhu, C. Luzzi","doi":"10.1109/ICSSEM.2011.6081283","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":406311,"journal":{"name":"2011 International Conference on System science, Engineering design and Manufacturing informatization","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on System science, Engineering design and Manufacturing informatization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSEM.2011.6081283","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
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.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
