Conference proceeding
TransRepair: Context-aware Program Repair for Compilation Errors
Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineerin, ASE 2022, pp.1-13
IEEE ACM International Conference on Automated Software Engineering
ASE '22: 37th IEEE/ACM International Conference on Automated Software Engineering, 37 (Rochester, MI, United States, 10/10/2022–14/10/2022)
05/01/2023
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Abstract
Automatically fixing compilation errors can greatly raise the productivity of software development, by guiding the novice or AI programmers to write and debug code. Recently, learning-based program repair has gained extensive attention and became the state-of-the-art in practice. But it still leaves plenty of space for improvement. In this paper, we propose an end-to-end solution TransRepair to locate the error lines and create the correct substitute for a C program simultaneously. Superior to the counterpart, our approach takes into account the context of erroneous code and diagnostic compilation feedback. Then we devise a Transformer-based neural network to learn the ways of repair from the erroneous code as well as its context and the diagnostic feedback. To increase the effectiveness of TransRepair, we summarize 5 types and 74 fine-grained sub-types of compilations errors from two real-world program datasets and the Internet. Then a program corruption technique is developed to synthesize a large dataset with 1,821,275 erroneous C programs. Through the extensive experiments, we demonstrate that TransRepair outperforms the state-of-the-art in both single repair accuracy and full repair accuracy. Further analysis sheds light on the strengths and weaknesses in the contemporary solutions for future improvement.
Details
- Title
- TransRepair: Context-aware Program Repair for Compilation Errors
- Creators
- Xueyang Li - Institute of Information EngineeringShangqing Liu - Nanyang Technological UniversityRuitao Feng - Univ New South Wales, Sydney, NSW 2052, AustraliaGuozhu Meng - Institute of Information EngineeringXiaofei Xie - Singapore Management UniversityKai Chen - Institute of Information EngineeringYang Liu - Nanyang Technological University
- Publication Details
- Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineerin, ASE 2022, pp.1-13
- Conference
- ASE '22: 37th IEEE/ACM International Conference on Automated Software Engineering, 37 (Rochester, MI, United States, 10/10/2022–14/10/2022)
- Series
- IEEE ACM International Conference on Automated Software Engineering
- Publisher
- Association for Computing Machinery (ACM); New York, NY, United States
- Number of pages
- 13
- Grant note
- 61902395; U1836211 / NSFC; National Natural Science Foundation of China (NSFC) M22004 / Beijing Natural Science Foundation 202103a05020009 / Anhui Department of Science and Technology Beijing Academy of Artificial Intelligence (BAAI) NRF-NRFI06-2020-0001 / NRF Investigatorship NRF2018NCR-NSOE003-0001 / National Research Foundation through its National Satellite of Excellence in Trustworthy Software Systems (NSOE-TSS) project under the National Cybersecurity RD (NCR) MOET32020-0004 / Ministry of Education, Singapore NRF2018NCR-NCR005-0001 / National Research Foundation, Prime Ministers Office, Singapore under its National Cybersecurity RD Program; National Research Foundation, Singapore Youth Innovation Promotion Association CAS AISG2-RP-2020-019 / National Research Foundation, Singapore under its the AI Singapore Programme
- Identifiers
- 991013245451102368
- Copyright
- © 2022 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License.
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Conference proceeding