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This paper presents a systematic literature review of learning-based Automated Program Repair (APR) techniques, categorizing them into five main types: supervised learning, unsupervised learning, transfer learning, ensemble learning, and language model learning. It discusses the evolution of these methods, highlighting their advantages and challenges, particularly in the patch generation process, which is critical for effective program repair. The review aims to provide insights for future research directio

Author

jashwanthneelam856

Language

EN