@article{Chen2025, 
author = {Qijia Chen and Dongcheng Li and Man Zhao and W. Eric Wong and Hui Li},
title = {Learning-Based Automated Program Repair: A Systematic Literature Review},
year = {2025},
journal = {Complex System Modeling and Simulation},
volume = {5},
number = {4},
pages = {305-322},
keywords = {Automated Program Repair (APR), software testing, patch generation, Machine Learning (ML), Deep Learning (DL)},
url = {https://www.sciopen.com/article/10.23919/CSMS.2025.0004},
doi = {10.23919/CSMS.2025.0004},
abstract = {Software often contains defects, and automated repair techniques offer a promising way to address these issues. This paper examines the current state of research in learning-based Automated Program Repair (APR). It reviews existing learning-based APR approaches and systematically categorizes them into five major types: supervised learning, unsupervised learning, transfer learning, ensemble learning, and language model learning. Finally, the paper discusses the challenges faced in this field, providing valuable insights for future research.}
}