The untold story of code refactoring customizations in practice
Refactoring is a common software maintenance practice. While the literature defines standard code modifications for each refactoring type, popular IDEs provide refactoring tools aiming to support these standard modifications. However, previous studies indicated that developers either frequently avoid using these tools or end up modifying and even reversing the code automatically refactored by IDEs. Thus, developers are forced to manually apply refactorings, which is cumbersome and error-prone. This means that refactoring support may not be entirely aligned with practical needs. The improvement of tooling support for refactoring in practice requires understanding in what ways developers tailor refactoring modifications. To address this issue, we conduct an analysis of 1,162 refactorings composed of more than 100k program modifications from 13 software projects. The results reveal that developers recurrently apply patterns of additional modifications along with the standard ones, from here on called patterns of \textit{customized refactorings}. For instance, we found customized refactorings in 80.77% of the \textit{Move Method} instances observed in the software projects. We also investigated the features of refactoring tools in popular IDEs and observed that most of the customization patterns are not fully supported by them. Additionally, to understand the relevance of these customizations, we conducted a survey with 40 developers about the most frequent customization patterns we found. Developers confirm the relevance of customization patterns and agree that improvements in IDE’s refactoring support are needed. These observations highlight that refactoring guidelines must be updated to reflect typical refactoring customizations. Also, IDE builders can use our results as a basis to enable a more flexible application of automated refactorings. For example, developers should be able to choose which method must handle exceptions when extracting an exception code into a new method.
Wed 17 MayDisplayed time zone: Hobart change
11:00 - 12:30 | Mining software repositoriesTechnical Track / Journal-First Papers / DEMO - Demonstrations at Meeting Room 102 Chair(s): Brittany Johnson George Mason University | ||
11:00 15mTalk | The untold story of code refactoring customizations in practice Technical Track Daniel Oliveira PUC-Rio, Wesley Assunção Johannes Kepler University Linz, Austria & Pontifical Catholic University of Rio de Janeiro, Brazil, Alessandro Garcia PUC-Rio, Ana Carla Bibiano PUC-Rio, Márcio Ribeiro Federal University of Alagoas, Brazil, Rohit Gheyi Federal University of Campina Grande, Baldoino Fonseca Federal University of Alagoas (UFAL) Pre-print | ||
11:15 15mTalk | Data Quality for Software Vulnerability Datasets Technical Track Roland Croft The University of Adelaide, Muhammad Ali Babar University of Adelaide, M. Mehdi Kholoosi University of Adelaide Pre-print | ||
11:30 15mTalk | Do code refactorings influence the merge effort? Technical Track André Oliveira Federal Fluminense University, Vania Neves Universidade Federal Fluminense (UFF), Alexandre Plastino Federal Fluminense University, Ana Carla Bibiano PUC-Rio, Alessandro Garcia PUC-Rio, Leonardo Murta Universidade Federal Fluminense (UFF) | ||
11:45 7mTalk | ActionsRemaker: Reproducing GitHub Actions DEMO - Demonstrations Hao-Nan Zhu University of California, Davis, Kevin Z. Guan University of California, Davis, Robert M. Furth University of California, Davis, Cindy Rubio-González University of California at Davis | ||
11:52 7mTalk | Problems with with SZZ and Features: An empirical assessment of the state of practice of defect prediction data collection Journal-First Papers Steffen Herbold University of Passau, Alexander Trautsch University of Passau, Alexander Trautsch Germany, Benjamin Ledel None | ||
12:00 7mTalk | An empirical study of issue-link algorithms: which issue-link algorithms should we use? Journal-First Papers Masanari Kondo Kyushu University, Yutaro Kashiwa Nara Institute of Science and Technology, Yasutaka Kamei Kyushu University, Osamu Mizuno Kyoto Institute of Technology | ||
12:07 7mTalk | SCS-Gan: Learning Functionality-Agnostic Stylometric Representations for Source Code Authorship Verification Journal-First Papers Weihan Ou Queen's University at Kingston, Ding Steven, H., H. Queen’s University at Kingston, Yuan Tian Queens University, Kingston, Canada, Leo Song Queen’s University at Kingston | ||
12:15 15mTalk | A Comprehensive Study of Real-World Bugs in Machine Learning Model Optimization Technical Track Hao Guan The University of Queensland, Ying Xiao Southern University of Science and Technology, Jiaying LI Microsoft, Yepang Liu Southern University of Science and Technology, Guangdong Bai University of Queensland | ||