Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Semantic Similarity-Based Contributable Task Identification for New Participating Developers

  • Kim, Jungil (Department of Software Technology Laboratory, Kyungpook National University) ;
  • Choi, Geunho (School of Computer Science and Engineering, Kyungpook National University) ;
  • Lee, Eunjoo (School of Computer Science and Engineering, Kyungpook National University)
  • Received : 2018.06.29
  • Accepted : 2018.10.16
  • Published : 2018.12.31
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Abstract

In software development, the quality of a product often depends on whether its developers can rapidly find and contribute to the proper tasks. Currently, the word data of projects to which newcomers have previously contributed are mainly utilized to find appropriate source files in an ongoing project. However, because of the vocabulary gap between software projects, the accuracy of source file identification based on information retrieval is not guaranteed. In this paper, we propose a novel source file identification method to reduce the vocabulary gap between software projects. The proposed method employs DBPedia Spotlight to identify proper source files based on semantic similarity between source files of software projects. In an experiment based on the Spring Framework project, we evaluate the accuracy of the proposed method in the identification of contributable source files. The experimental results show that the proposed approach can achieve better accuracy than the existing method based on comparison of word vocabularies.

Keywords

E1ICAW_2018_v16n4_228_f0001.png 이미지

Fig. 1. The work flow of the proposed approach.

Table 1. Preprocessing results

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Table 2. Example of annotation

E1ICAW_2018_v16n4_228_t0002.png 이미지

Table 3. Results of Top-25 and Top-250 identification

E1ICAW_2018_v16n4_228_t0003.png 이미지

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