Automated Refactoring of Non-Idiomatic Python Code: A Differentiated Replication with LLMs
This program is tentative and subject to change.
In the Python ecosystem, the adoption of idiomatic constructs has been fostered because of their expressiveness, increasing productivity and even efficiency, despite controversial arguments concerning familiarity or understandability issues. Recent research contributions have proposed approaches—based on static code analysis and transformation—to automatically identify and enact refactoring opportunities of non-idiomatic code into idiomatic ones. Given the potential recently offered by Large Language Models (LLMs) for code-related tasks, in this paper, we present the results of a replication study in which we investigate GPT-4 effectiveness in recommending and suggesting idiomatic refactoring actions. Our results reveal that GPT-4 not only identifies idiomatic constructs effectively but frequently exceeds the benchmark in proposing refactoring actions where the existing baseline failed. A manual analysis of a random sample shows the correctness of the obtained recommendations. Overall, our findings underscore the potential of LLMs to achieve tasks where, in the past, implementing recommenders based on complex code analyses was required.
This program is tentative and subject to change.
Sun 27 AprDisplayed time zone: Eastern Time (US & Canada) change
11:00 - 12:30 | Vulnerabilities, Technical Debt, DefectsEarly Research Achievements (ERA) / Research Track / Replications and Negative Results (RENE) at 205 | ||
11:00 10mTalk | CalmDroid: Core-Set Based Active Learning for Multi-Label Android Malware Detection Research Track Minhong Dong Tiangong University, Liyuan Liu Tiangong University, Mengting Zhang Tiangong University, Sen Chen Tianjin University, Wenying He Hebei University of Technology, Ze Wang Tiangong University, Yude Bai Tianjin University | ||
11:10 10mTalk | Towards Task-Harmonious Vulnerability Assessment based on LLM Research Track Zaixing Zhang Southeast University, Chang Jianming , Tianyuan Hu Southeast University, Lulu Wang Southeast University, Bixin Li Southeast University | ||
11:20 10mTalk | Slicing-Based Approach for Detecting and Patching Vulnerable Code Clones Research Track Hakam W. Alomari Miami University, Christopher Vendome Miami University, Himal Gyawali Miami University | ||
11:30 6mTalk | Revisiting Security Practices for GitHub Actions Workflows Early Research Achievements (ERA) | ||
11:36 6mTalk | Leveraging multi-task learning to improve the detection of SATD and vulnerability Replications and Negative Results (RENE) Barbara Russo Free University of Bolzano, Jorge Melegati Free University of Bozen-Bolzano, Moritz Mock Free University of Bozen-Bolzano Pre-print | ||
11:42 10mTalk | Leveraging Context Information for Self-Admitted Technical Debt Detection Research Track Miki Yonekura Nara Institute of Science and Technology, Yutaro Kashiwa Nara Institute of Science and Technology, Bin Lin Radboud University, Kenji Fujiwara Nara Women’s University, Hajimu Iida Nara Institute of Science and Technology | ||
11:52 6mTalk | Personalized Code Readability Assessment: Are We There Yet? Replications and Negative Results (RENE) Antonio Vitale Politecnico di Torino, University of Molise, Emanuela Guglielmi University of Molise, Rocco Oliveto University of Molise, Simone Scalabrino University of Molise | ||
11:58 6mTalk | Automated Refactoring of Non-Idiomatic Python Code: A Differentiated Replication with LLMs Replications and Negative Results (RENE) Pre-print | ||
12:04 10mResearch paper | Sonar: Detecting Logic Bugs in DBMS through Generating Semantic-aware Non-Optimizing Query Research Track Shiyang Ye Zhejiang University, Chao Ni Zhejiang University, Jue Wang Nanjing University, Qianqian Pang zhejang university, Xinrui Li School of Software Technology, Zhejiang University, xiaodanxu College of Computer Science and Technology, Zhejiang university | ||
12:14 6mTalk | A Study on Applying Large Language Models to Issue Classification Replications and Negative Results (RENE) | ||
12:20 10mLive Q&A | Session's Discussion: "Vulnerabilities, Technical Debt, Defects" Research Track | ||