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Wen_2021_ICSME
Conference paper (in proceedings)

FeaRS : recommending complete Android method implementations

  • Wen, Fengcai Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
  • Ferrari, Valentina Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
  • Aghajani, Emad ORCID Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
  • Nagy, Csaba ORCID Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
  • Lanza, Michele ORCID Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
  • Bavota, Gabriele ORCID Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
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  • 2021
Published in:
  • 2021 IEEE International Conference on Software Maintenance and Evolution (ICSME). - 2021, p. 589-593
Source code recommender
Code completion
English Several techniques have been proposed in the literature to support code completion, showing excellent results in predicting the next few tokens a developer is likely to type given the current context. Only recently, approaches pushing the boundaries of code completion (e.g., by presenting entire code statements) have been proposed. In this line of research, we present FeaRS, a recommender system that, given the current code a developer is writing in the IDE, recommends the next complete method to be implemented. FeaRS has been deployed to learn “implementation patterns” (i.e., groups of methods usually implemented within the same task) by continuously mining open-source Android projects. Such knowledge is leveraged to provide method recommendations when the code written by the developer in the IDE matches an “implementation pattern”. Preliminary results of FeaRS’ accuracy show its potential as well as some open challenges to overcome.
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Language
  • English
Classification
Computer science and technology
License
License undefined
Open access status
green
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Persistent URL
https://n2t.net/ark:/12658/srd1327979
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