PYREF : refactoring detection in Python projects
- Atwi, Hassan Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
- Lin, Bin ORCID Istituto del software (SI), Facoltà di scienze informatiche, Università della Svizzera italiana, Svizzera
- Tsantalis, Nikolaos ORCID Concordia University, Canada
- Kashiwa, Yutaro ORCID Kyushu University, Japan
- Kamei, Yasutaka Kyushu University, Japan
- Ubayashi, Naoyasu ORCID Kyushu University, Japan
- Bavota, Gabriele 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
- 2021
Published in:
- 2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM), Luxembourg, 2021. - 2021, p. 136-141
English
Refactoring, the process of improving the internal code structure of a software system without altering its external behavior, is widely applied during software development. Understanding how developers refactor source code can help gain better understanding of the software development process and the relationship between various versions of a system. Refactoring detection tools have been developed for many popular programming languages, such as Java (e.g., REFACTORINGMINER and REF-FINDER) but, quite surprisingly, this is not the case for Python, a widely used programming language. Inspired by REFACTORING MINER, we present PYREF, a tool that automatically detects method-level refactoring operations in Python projects. We evaluated PYREF against a manually built oracle and compared it with a PYTHON-ADAPTED REFACTOR-INGMINER, which converts Python program to Java and detects refactoring operations with REFACTORING MINER. Our results indicate that PYREF can achieve satisfactory precision and detect more refactorings than the current state-of-the-art.
- Collections
- Language
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- English
- Classification
- Computer science and technology
- License
- License undefined
- Open access status
- green
- Identifiers
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- DOI 10.1109/SCAM52516.2021.00025
- ARK ark:/12658/srd1325322
- Persistent URL
- https://n2t.net/ark:/12658/srd1325322
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