A key challenge of automated program repair is finding correct patches in the vast search space of candidate patches. Real-world programs define large namespaces of variables that considerably contributes to the search space explosion. Existing program repair approaches neglect information about the program namespace, which makes them inefficient and increases the chance of test-overfitting. We propose Rete, a new program repair technique, that learns project-independent information about program namespace and uses it to navigate the search space of patches. Rete uses a neural network to extract project-independent information about variable CDU chains, def-use chains augmented with control flow. Then, it ranks patches by jointly ranking variables and the patch templates into which the variables are inserted. We evaluated Rete on 142 bugs extracted from two datasets, ManyBugs and BugsInPy. Our experiments demonstrate that Rete generates six new correct patches that fix bugs that previous tools did not repair, an improvement of 31% and 59% over the existing state of the art.
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 | ||