ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal
Wed 17 Apr 2024 11:15 - 11:30 at Pequeno Auditório - Program Repair 1 Chair(s): Sergey Mechtaev

Neural network repair aims to fix the ‘bugs’ of neural networks by modifying the model’s architecture or parameters. However, due to the data-driven nature of neural networks, it is difficult to explain the relationship between the internal neurons and erroneous behaviors, making further repair challenging. While several work exists to identify responsible neurons based on gradient or causality analysis, their effectiveness heavily rely on the quality of available `bugged’ data and multiple heuristics in layer or neuron selection. In this work, we address the issue utilizing the power of formal verification (in particular for neural networks). Specifically, we propose VeRe, a verification-guided neural network repair framework that performs fault localization based on linear relaxation to symbolically calculate the repair significance of neurons and furthermore optimize the parameters of problematic neurons to repair erroneous behaviors. We evaluated VeRe on various repair tasks, and our experimental results show that VeRe can efficiently and effectively repair all neural networks without degrading the model’s performance. For the task of removing backdoors, VeRe successfully reduces attack success rate from 98.47% to 0.38% on average, while causing an average performance drop of 0.9%. For the task of repairing safety properties, VeRe successfully repairs all the 36 tasks and achieves 99.87% generalization on average.

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 (Ulsan National Institute of Science and Technology)
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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