Dynamic Ranking of Refactoring Menu Items for Integrated Development Environment | Zendy

Thida Oo | Zendy; Hui Liu | Zendy; Bridget Nyirongo | Zendy

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Dynamic Ranking of Refactoring Menu Items for Integrated Development Environment

Author(s) -

Thida Oo,

Hui Liu,

Bridget Nyirongo

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2883769

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Software refactoring is popular and thus most mainstream IDEs, e.g., Eclipse, provide a top level menu, especially for refactoring activities. The refactoring menu is designed to facilitate refactorings, and it has become one of the most commonly used menus. However, to support a large number of refactoring types, the refactoring menu contains a long list of menu items. As a result, it is tedious to select the intended menu item from the lengthy menu. To facilitate the menu selection, in this paper, we propose an approach to dynamic ranking of refactoring menu items for IDE. We put the most likely refactoring menu item on the top of the refactoring menu according to developers' source code selection and code smells associated with the selected source code. The ranking is dynamic because it changes frequently according to the context. First, we collect the refactoring history of the open source applications and detect the code smells. Based on the refactoring history, we design questionnaires and analyze the responses from developers to discover the source code selection patterns for different refactoring types. Subsequently, we analyze the relationship between code smells associated with the refactoring software entities and the corresponding refactoring types. Finally, based on the preceding analysis, we calculate the likelihood of different refactoring types to be applied when a specific part of source code is selected, and rank the menu items according to the resulting likelihood. We conduct a case study to evaluate the proposed approach. Evaluation results suggest that the proposed approach is accurate, and in most cases (95.69%), it can put the intended refactoring menu item on the top of the menu.

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