How Much Can a Behavior-Preserving Changeset Be Decomposed into Refactoring Operations?
This program is tentative and subject to change.
Developers sometimes mix behavior-preserving modifications, such as refactorings, with behavior-altering modifications, such as feature additions. Several approaches have been proposed to support understanding such modifications by separating them into those two parts. Such refactoring-aware approaches are expected to be particularly effective when the behavior-preserving parts can be decomposed into a sequence of more primitive behavior-preserving operations, such as refactorings, but this has not been explored. In this paper, as an initial validation, we quantify how much of the behavior-preserving modifications can be decomposed into refactoring operations using a dataset of functionally-equivalent method pairs. As a result, when using an existing refactoring detector, only 33.9% of the changes could be identified as refactoring operations. In contrast, when including 67 newly defined functionally-equivalent operations, the coverage increased by over 128%. Further investigation into the remaining unexplained differences was conducted, suggesting improvement opportunities.
This program is tentative and subject to change.
Wed 10 SepDisplayed time zone: Auckland, Wellington change
13:30 - 15:00 | Session 3 - Debugging and RefactoringResearch Papers Track / Industry Track / Tool Demonstration Track / NIER Track at Case Room 3 260-055 Chair(s): Ashkan Sami Edinburgh Napier University | ||
13:30 15m | Boosting Redundancy-based Automated Program Repair by Fine-grained Pattern Mining Research Papers Track Jiajun Jiang Tianjin University, Fengjie Li Tianjin University, Zijie Zhao Tianjin University, Zhirui Ye Tianjin University, Mengjiao Liu Tianjin University, Bo Wang Beijing Jiaotong University, Hongyu Zhang Chongqing University, Junjie Chen Tianjin University | ||
13:45 10m | LadyBug: A GitHub Bot for UI-Enhanced Bug Localization in Mobile Apps Tool Demonstration Track Junayed Mahmud University of Central Florida, James Chen University of Toronto, Terry Achille University of Central Florida, Camilo Alvarez-Velez University of Central Florida, Darren Dean Bansil University of Central Florida, Patrick Ijieh University of Central Florida, Samar Karanch University of Central Florida, Nadeeshan De Silva William & Mary, Oscar Chaparro William & Mary, Andrian Marcus George Mason University, Kevin Moran University of Central Florida | ||
13:55 15m | Together We Are Better: LLM, IDE and Semantic Embedding to Assist Move Method Refactoring Research Papers Track Abhiram Bellur University of Colorado Boulder, Fraol Batole Tulane University, Malinda Dilhara Amazon Web Services, USA, Mohammed Raihan Ullah University of Colorado Boulder, Yaroslav Zharov JetBrains Research, Timofey Bryksin JetBrains Research, Kai Ishikawa NEC Corporation, Haifeng Chen NEC Laboratories America, Masaharu Morimoto NEC Corporation, Shota Motoura NEC Corporation, Takeo Hosomi NEC Corporation, Tien N. Nguyen University of Texas at Dallas, Hridesh Rajan Tulane University, Nikolaos Tsantalis Concordia University, Danny Dig University of Colorado Boulder, JetBrains Research | ||
14:10 10m | COB2PY - A Non-AI, Rule-Based COBOL to Python Translator Tool Demonstration Track Kowshik Reddy Challa Indian Institute of Technology, Tirupati, Sonith M V Indian Institute of Technology, Tirupati, Chiranjeevi B S Indian Institute of Technology Tirupati, Sridhar Chimalakonda Indian Institute of Technology Tirupati | ||
14:20 10m | How Does Test Code Differ From Production Code in Terms of Refactoring? An Empirical Study NIER Track Kosei Horikawa Nara Institute of Science and Technology, Yutaro Kashiwa Nara Institute of Science and Technology, Bin Lin Hangzhou Dianzi University, Kenji Fujiwara Nara Women’s University, Hajimu Iida Nara Institute of Science and Technology Pre-print | ||
14:30 10m | How Much Can a Behavior-Preserving Changeset Be Decomposed into Refactoring Operations? NIER Track Kota Someya Institute of Science Tokyo, Lei Chen Institute of Science Tokyo, Michael J. Decker Bowling Green State University, Shinpei Hayashi Institute of Science Tokyo Pre-print | ||
14:40 15m | Governance Matters: Lessons from Restructuring the data.table OSS Project Industry Track Pedro Arantes RESHAPE LAB, Northern Arizona University, USA, Doris Amoakohene Northern Arizona University, Toby Hocking Université de Sherbrooke, Marco Gerosa Northern Arizona University, Igor Steinmacher NAU RESHAPE LAB | ||