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ESEC/FSE 2021
Thu 19 - Sat 28 August 2021 Clowdr Platform
Thu 26 Aug 2021 09:20 - 09:30 - Testing—Program Repair 1 Chair(s): Santanu Dash
Thu 26 Aug 2021 21:20 - 21:30 - Testing—Program Repair 1 Chair(s): Lingming Zhang

Automated Program Repair (APR) helps improve the efficiency of software development and maintenance. Recent APR techniques use deep learning, particularly the encoder-decoder architecture, to generate patches.
Though existing DL-based APR approaches have proposed different encoder architectures, the decoder remains to be the standard one, which generates a sequence of tokens one by one to replace the faulty statement.
This decoder has multiple limitations: 1) allowing to generate syntactically incorrect programs, 2) inefficiently representing small edits, and 3) not being able to generate project-specific identifiers.

In this paper, we propose Recoder, a syntax-guided edit decoder with placeholder generation. Recoder is novel in multiple aspects: 1) Recoder generates edits rather than modified code, allowing efficient representation of small edits; 2) Recoder is syntax-guided, with the novel provider/decider architecture to ensure the syntactic correctness of the patched program and accurate generation; 3) Recoder generates placeholders that could be instantiated as project-specific identifiers later.

We conduct experiments to evaluate Recoder on 395 bugs from Defects4J v1.2, 420 additional bugs from Defects4J v2.0, 297 bugs from IntroClassJava and 40 bugs from QuixBugs. Our results show that Recoder repairs 53 bugs on Defects4J v1.2, which achieves 26.2% (11 bugs) improvement over the previous state-of-the-art approach for single-hunk bugs (TBar). Importantly, to our knowledge, Recoder is the first DL-based APR approach that has outperformed the traditional APR approaches on this benchmark. Furthermore, Recoder repairs 19 bugs on the additional bugs from Defects4J v2.0, which is 137.5% (11 bugs) more than TBar and 850% (17 bugs) more than SimFix. Recoder also achieves 775% (31 bugs) and 30.8% (4 bugs) improvement on IntroClassJava and QuixBugs over the baselines respectively. These results suggest that Recoder has better generalizability than existing APR approaches.

Thu 26 Aug

Displayed time zone: Athens change

09:00 - 10:00
Testing—Program Repair 1Research Papers / Journal First +12h
Chair(s): Santanu Dash University of Surrey
09:00
10m
Paper
Beyond Tests: Program Vulnerability Repair via Crash Constraint Extraction
Journal First
Xiang Gao National University of Singapore, Bo Wang Peking University, China, Gregory J. Duck National University of Singapore, Ruyi Ji Peking University, Yingfei Xiong Peking University, Abhik Roychoudhury National University of Singapore
09:10
10m
Paper
Context-Aware and Data-Driven Feedback Generation for Programming AssignmentsArtifacts AvailableArtifacts Reusable
Research Papers
Dowon Song Korea University, Woosuk Lee Hanyang University, Hakjoo Oh Korea University
DOI
09:20
10m
Paper
A Syntax-Guided Edit Decoder for Neural Program RepairArtifacts Available
Research Papers
Qihao Zhu Peking University, Zeyu Sun Peking University, Yuan-An Xiao Peking University, Wenjie Zhang Peking University, Kang Yuan Stony Brook University, Yingfei Xiong Peking University, Lu Zhang Peking University
DOI
09:30
30m
Live Q&A
Q&A (Testing—Program Repair 1)
Research Papers

21:00 - 22:00
Testing—Program Repair 1Research Papers / Journal First
Chair(s): Lingming Zhang University of Illinois at Urbana-Champaign
21:00
10m
Paper
Beyond Tests: Program Vulnerability Repair via Crash Constraint Extraction
Journal First
Xiang Gao National University of Singapore, Bo Wang Peking University, China, Gregory J. Duck National University of Singapore, Ruyi Ji Peking University, Yingfei Xiong Peking University, Abhik Roychoudhury National University of Singapore
21:10
10m
Paper
Context-Aware and Data-Driven Feedback Generation for Programming AssignmentsArtifacts AvailableArtifacts Reusable
Research Papers
Dowon Song Korea University, Woosuk Lee Hanyang University, Hakjoo Oh Korea University
DOI
21:20
10m
Paper
A Syntax-Guided Edit Decoder for Neural Program RepairArtifacts Available
Research Papers
Qihao Zhu Peking University, Zeyu Sun Peking University, Yuan-An Xiao Peking University, Wenjie Zhang Peking University, Kang Yuan Stony Brook University, Yingfei Xiong Peking University, Lu Zhang Peking University
DOI
21:30
30m
Live Q&A
Q&A (Testing—Program Repair 1)
Research Papers