一句话：提出面向提交历史的重构检测方法，提升准确性并降低对阈值与项目构建的依赖。
重构检测算法对代码演化实证研究、库 API 迁移、变更理解和代码审查等应用至关重要。然而，现有最先进工具的准确性受到质疑，且通常对用户提供的相似度阈值高度敏感，从而影响实际精度；同时，它们需要构建待分析的版本或修订，限制了在真实场景中的适用性。针对这些问题，本文提出一种在提交历史中准确、高效检测重构的方法，目标是在不依赖项目构建、并减少阈值敏感性的情况下识别重构，从而提高重构检测工具的可靠性与可用性。摘要未给出具体实验数据。
Refactoring detection algorithms have been crucial to a variety of applications: (i) empirical studies about the evolution of code, tests, and faults, (ii) tools for library API migration, (iii) improving the comprehension of changes and code reviews, etc. However, recent research has questioned the accuracy of the state-of-the-art refactoring detection tools, which poses threats to the reliability of their application. Moreover, previous refactoring detection tools are very sensitive to user-provided similarity thresholds, which further reduces their practical accuracy. In addition, their requirement to build the project versions/revisions under analysis makes them inapplicable in many real-world scenarios.
DOI 原文 ·
@inproceedings{paperbot4416,
title = {Accurate and efficient refactoring detection in commit history},
author = {Nikolaos Tsantalis and Matin Mansouri and Laleh M. Eshkevari and Davood Mazinanian and Danny Dig},
booktitle = {ICSE},
year = {2018},
doi = {10.1145/3180155.3180206}
}