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ICSE2024顶会

Context-Aware Name Recommendation for Field Renaming

Chunhao Dong, Yanjie Jiang, Nan Niu, Yuxia Zhang, Hui Liu

2024年份
4被引次数

摘要

Renaming is one of the most popular software refactorings. Although developers may know what the new name should be when they conduct a renaming, it remains valuable for refactoring tools to recommend new names automatically so that developers can simply hit Enter and efficiently accept the recommendation to accomplish the refactoring. Consequently, most IDEs automatically recommend new names for renaming refactorings by default. However, the recommendation made by mainstream IDEs is often incorrect. For example, the precision of IntelliJ IDEA in recommending names for field renamings is as low as 6.3%. To improve the accuracy, in this paper, we propose a context-aware lightweight approach (called CARER) to recommend new names for Java field renamings. Different from mainstream IDEs that rely heavily on initializers and data types of the to-be-renamed fields, CARER exploits both dynamic and static contexts of the renamings as well as naming conventions. We evaluate CARER on 1.1K real-world field renamings discovered from open-source applications. Our evaluation results suggest that CARER can significantly improve the state of the practice in recommending new names for field renamings, improving the precision from 6.30% to 61.15%, and recall from 6.30% to 41.50%. Our evaluation results also suggest that CARER is as efficient as IntelliJ IDEA is, making it suitable to be integrated into IDEs.

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