An empirical study of deep transfer learning-based program repair for Kotlin projects
Author:
Affiliation:
1. Sungkyunkwan University, South Korea
2. Samsung Electronics, South Korea
Funder
Samsung electronics
National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3540250.3558967
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3. 2022. NLTK Tokenizer. https://www.nltk.org/api/nltk.tokenize.html Accessed: 2022-05-19 2022. NLTK Tokenizer. https://www.nltk.org/api/nltk.tokenize.html Accessed: 2022-05-19
4. Gunnar Applelid. 2021. Evaluating template-based automatic program repair in industry. Gunnar Applelid. 2021. Evaluating template-based automatic program repair in industry.
5. Getafix: learning to fix bugs automatically
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1. A Survey of Learning-based Automated Program Repair;ACM Transactions on Software Engineering and Methodology;2023-12-23
2. Evolution of Kotlin Apps in terms of Energy Consumption: An Exploratory Study;2023 International Conference on ICT for Sustainability (ICT4S);2023-06-05
3. REFERENT: Transformer-based Feedback Generation using Assignment Information for Programming Course;2023 IEEE/ACM 45th International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET);2023-05
4. Patch It If You Can: Increasing the Efficiency of Patch Generation Using Context;Electronics;2022-12-30
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