Method name recommendation based on source code depository and feature matching

Yuan Gao, Hui Liu*, Xiao Zhong Fan, Zhen Dong Niu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Quality of method names is critical for the readability and maintainability of program. However, it is difficult for software engineers, especially non-English speaking, inexperienced engineers, to propose high quality method names. To address this issue, this paper proposes an approach to recommend method names. First, a method corpus is constructed from open source applications. For a given method f to be named, similar methods are retrieved from the method corpus. Names of these retrieved methods are divided into phrases, and features of these methods are extracted as well. A mapping between these phrases and features is also created to derive a list of candidate phrases and features for the method to be named. These phrases are finally constructed into candidate method names. The proposed approach is evaluated on 1 430 methods in open source applications. Evaluation results suggest that 22.7 percent of recommended method names are the same as original ones, and 57.9 percent has the same or almost the same keywords as original ones.

Original languageEnglish
Pages (from-to)3062-3074
Number of pages13
JournalRuan Jian Xue Bao/Journal of Software
Volume26
Issue number12
DOIs
Publication statusPublished - 1 Dec 2015

Keywords

  • Algorithm
  • Feature selection
  • Method name
  • Natural language processing
  • Recommendation

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