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 MayDisplayed 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 15mTalk | Better Automatic Program Repair by Using Bug Reports and Tests Together Technical Track Pre-print | ||
11:15 15mTalk | 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 7mTalk | 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 7mTalk | 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 15mTalk | 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 15mTalk | Rete: Learning Namespace Representation for Program Repair 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 7mTalk | 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 7mTalk | 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 | ||