Abstract
The extract method is a common way to shorten long methods in software development. Before developers can use tools that support the extract method, they need to invest time in identifying a suitable refactoring candidate. This paper addresses the problem of finding the most appropriate refactoring candidate for long methods written in Java. The approach determines valid refactoring candidates and ranks them using a scoring function that aims to improve readability and reduce code complexity. We use length and nesting reduction as complexity indicators. The number of parameters needed by the candidate influences the score. To suggest candidates that are consistent with the structure of the code, information such as comments and blank lines are also considered by the scoring function. We evaluate our approach to three open source systems using a user study with ten experienced developers. Our results show that they would actually apply 86 % of suggestions for an extract method refactoring.
This work was partially funded by the German Federal Ministry of Education and Research (BMBF), grant “Q-Effekt, 01IS15003A”. The responsibility for this article lies with the authors.
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Haas, R., Hummel, B. (2016). Deriving Extract Method Refactoring Suggestions for Long Methods. In: Winkler, D., Biffl, S., Bergsmann, J. (eds) Software Quality. The Future of Systems- and Software Development. SWQD 2016. Lecture Notes in Business Information Processing, vol 238. Springer, Cham. https://doi.org/10.1007/978-3-319-27033-3_10
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