SEQUENCER: Sequence-to-Sequence Learning for End-to-End Program Repair
نویسندگان
چکیده
This paper presents a novel end-to-end approach to program repair based on sequence-to-sequence learning. We devise, implement, and evaluate system, called SequenceR, for fixing bugs learning source code. uses the copy mechanism overcome unlimited vocabulary problem that occurs with big Our system is data-driven; we train it 35,578 samples, carefully curated from commits open-source repositories. 4,711 independent real bug fixes, as well Defects4J benchmark used in research. SequenceR able perfectly predict fixed line 950/4711 testing find correct patches 14 Defects4J. It captures wide range of operators without any domain-specific top-down design.
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ژورنال
عنوان ژورنال: IEEE Transactions on Software Engineering
سال: 2021
ISSN: ['0098-5589', '1939-3520', '2326-3881']
DOI: https://doi.org/10.1109/tse.2019.2940179