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ICSE 2023
Sun 14 - Sat 20 May 2023 Melbourne, Australia

The Linux Kernel is a world-class operating system controlling most of our computing infrastructure: mobile devices, Internet routers and services, and most of the supercomputers. Linux is also an example of low-level software with no comprehensive regression test suite (for good reasons). The kernel’s tremendous societal importance imposes strict stability and correctness requirements. These properties make Linux a challenging and relevant target for static automated program repair (APR).

Over the last decade, a significant progress has been made in dynamic APR. However, dynamic APR techniques do not translate naturally to systems without tests. We present a static APR technique addressing sequential locking API misuse bugs in the Linux Kernel. We attack the key challenge of static APR, namely the lack of detailed program specification, by combining static analysis with machine learning to complement the information presented by the static analyzer. In experiments on historical real-world bugs in the kernel, we were able to automatically re-produce or propose equivalent patches in 85% of the human made patches, and automatically rank them among the top three candidates for 64% of the cases and among the top five for 74%.

Thu 18 May

Displayed time zone: Hobart change

11:00 - 12:30
Program repair techniques and applicationsTechnical Track / Journal-First Papers / DEMO - Demonstrations at Meeting Room 104
Chair(s): Xuan-Bach D. Le University of Melbourne
11:00
15m
Talk
Better Automatic Program Repair by Using Bug Reports and Tests Together
Technical Track
Manish Motwani Georgia Institute of Technology, Yuriy Brun University of Massachusetts
Pre-print
11:15
15m
Talk
CCTEST: Testing and Repairing Code Completion Systems
Technical Track
Li Zongjie , Chaozheng Wang Harbin Institute of Technology, Zhibo Liu Hong Kong University of Science and Technology, Haoxuan Wang EPFL, Dong Chen HKUST, Shuai Wang Hong Kong University of Science and Technology, Cuiyun Gao Harbin Institute of Technology
11:30
7m
Talk
A Controlled Experiment of Different Code Representations for Learning-Based Program Repair
Journal-First Papers
Marjane Namavar University of British Columbia, Noor Nashid University of British Columbia, Ali Mesbah University of British Columbia (UBC)
Link to publication Pre-print
11:37
7m
Talk
Patching Locking Bugs Statically with Crayons
Journal-First Papers
Juan Alfredo Cruz-Carlon IT University of Copenhagen, Mahsa Varshosaz IT University of Copenhagen, Denmark, Claire Le Goues Carnegie Mellon University, Andrzej Wąsowski IT University of Copenhagen, Denmark
11:45
15m
Talk
KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair
Technical Track
Nan Jiang Purdue University, Thibaud Lutellier University of Alberta, Yiling Lou Fudan University, Lin Tan Purdue University, Dan Goldwasser Purdue University, Xiangyu Zhang Purdue University
Pre-print
12:00
15m
Talk
Rete: Learning Namespace Representation for Program RepairDistinguished Paper Award
Technical Track
Nikhil Parasaram University College London, Earl T. Barr University College London, Sergey Mechtaev University College London
Link to publication Pre-print
12:15
7m
Talk
Cerberus: a Program Repair Framework
DEMO - Demonstrations
Ridwan Salihin Shariffdeen National University of Singapore, Martin Mirchev National University of Singapore, Yannic Noller National University of Singapore, Abhik Roychoudhury National University of Singapore
12:22
7m
Talk
Predicting Patch Correctness Based on the Similarity of Failing Test Cases
Journal-First Papers
Haoye Tian University of Luxembourg, Yinghua LI University of Luxembourg, Weiguo PIAN University of Luxembourg, Abdoul Kader Kaboré SnT, University of Luxembourg, Kui Liu Huawei Software Engineering Application Technology Lab, Andrew Habib SnT, University of Luxembourg, Jacques Klein University of Luxembourg, Tegawendé F. Bissyandé SnT, University of Luxembourg