ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal
Wed 17 Apr 2024 12:00 - 12:07 at Pequeno Auditório - Program Repair 1 Chair(s): Sergey Mechtaev

Contextual information plays a vital role for software developers when understanding and fixing a bug. Consequently, deep learning-based program repair techniques leverage context for bug fixes. However, existing techniques treat context in an arbitrary manner, by extracting code in close proximity of the buggy statement within the enclosing file, class, or method, without any analysis to find actual relations with the bug. To reduce noise, they use a predefined maximum limit on the number of tokens to be used as context. We present a program slicing-based approach, in which instead of arbitrarily including code as context, we analyze statements that have a control or data dependency on the buggy statement. We propose a novel concept called dual slicing, which leverages the context of both buggy and fixed versions of the code to capture relevant repair ingredients. We present our technique and tool called Katana, the first to apply slicing-based context for a program repair task. The results show Katana effectively preserves sufficient information for a model to choose contextual information while reducing noise. We compare against four recent state-of-the-art context-aware program repair techniques. Our results show Katana fixes between 1.5 to 3.7 times more bugs than existing techniques.

Wed 17 Apr

Displayed time zone: Lisbon change

11:00 - 12:30
Program Repair 1Research Track / Journal-first Papers / Industry Challenge Track at Pequeno Auditório
Chair(s): Sergey Mechtaev University College London
11:00
15m
Talk
Domain Knowledge Matters: Improving Prompts with Fix Templates for Repairing Python Type Errors
Research Track
Yun Peng The Chinese University of Hong Kong, Shuzheng Gao The Chinese University of Hong Kong, Cuiyun Gao Harbin Institute of Technology, Yintong Huo The Chinese University of Hong Kong, Michael Lyu The Chinese University of Hong Kong
11:15
15m
Talk
VeRe: Verification Guided Synthesis for Repairing Deep Neural Networks
Research Track
Jianan Ma Hangzhou Dianzi University, China; Zhejiang University, Hangzhou, China, Pengfei Yang Institute of Software at Chinese Academy of Sciences, China, Jingyi Wang Zhejiang University, Youcheng Sun The University of Manchester, Cheng-Chao Huang Nanjing Institute of Software Technology, ISCAS, Zhen Wang Hangzhou Dianzi University, China
11:30
15m
Talk
Automated Program Repair, What Is It Good For? Not Absolutely Nothing!
Research Track
Hadeel Eladawy University of Massachusetts, Claire Le Goues Carnegie Mellon University, Yuriy Brun University of Massachusetts
Pre-print
11:45
15m
Talk
When Large Language Models Confront Repository-Level Automatic Program Repair: How Well They Done?
Industry Challenge Track
YuXiao Chen Institute of Software, Chinese Academy of Sciences, Jingzheng Wu Institute of Software, The Chinese Academy of Sciences, Xiang Ling Institute of Software, Chinese Academy of Sciences, Changjiang Li Penn State, ZHIQING RUI Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences, Tianyue Luo Institute of Software, Chinese Academy of Sciences, Yanjun Wu Institute of Software, Chinese Academy of Sciences
12:00
7m
Talk
Katana: Dual Slicing Based Context for Learning Bug Fixes
Journal-first Papers
Mifta Sintaha University of British Columbia, Noor Nashid University of British Columbia, Ali Mesbah University of British Columbia (UBC)
Link to publication Pre-print
12:07
7m
Talk
Poracle: Testing Patches Under Preservation Conditions to Combat the Overfitting Problem of Program Repair
Journal-first Papers
Elkhan Ismayilzada UNIST, Md Mazba Ur Rahman UNIST, Dongsun Kim Kyungpook National University, Jooyong Yi UNIST
12:14
7m
Talk
APR4Vul: An empirical study of automatic program repair techniques on real-world Java vulnerabilities
Journal-first Papers
Quang-Cuong Bui Hamburg University of Technology, Ranindya Paramitha University of Trento, Duc-Ly Vu University of Information Technology, Ho Chi Minh City, Fabio Massacci University of Trento; Vrije Universiteit Amsterdam, Riccardo Scandariato Hamburg University of Technology
DOI Pre-print
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