We are very glad to announce that the paper ““Identifying Extract Method Refactoring Opportunities based on Functional Relevance”” (by Sofia Charalampidou, Apostolos Ampatzoglou, Alexander Chatzigeorgiou, Antonios Gkortzis and Paris Avgeriou) has been accepted for publication at the IEEE Transactions on Software Engineering

Abstract—‘Extract Method’ is considered one of the most frequently applied and beneficial refactorings, since the corresponding Long Method smell is among the most common and persistent ones. Although Long Method is conceptually related to the implementation of diverse functionalities within a method, until now, this relationship has not been utilized while identifying refactoring opportunities. In this paper we introduce an approach (accompanied by a tool) that aims at identifying source code chunks that collaborate to provide a specific functionality, and propose their extraction as separate methods. The accuracy of the proposed approach has been empirically validated both in an industrial and an open-source setting. In the former case, the approach was capable of identifying functionally related statements within two industrial long methods (approx. 500 LoC each), with a recall rate of 93%. In the latter case, based on a comparative study on open-source data, our approach ranks better compared to two well-known techniques of the literature. To assist software engineers in the prioritization of the suggested refactoring opportunities the approach ranks them based on an estimate of their fitness for extraction. The provided ranking has been validated in both settings and proved to be strongly correlated with experts’ opinion


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