Work

Learning-Based Automated Program Repair: A Systematic Literature Review

Year: 2025

Type: review

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.

Source: Complex System Modeling and Simulation

DOI: 10.23919/csms.2025.0004

Authors: Qijia Chen, Dongcheng Li, Man Zhao, W. Eric Wong, Hui Li

Institutions: China University of Geosciences, Cal Poly Humboldt, California State Polytechnic University, The University of Texas at Dallas

Language: English

Topic: Software Testing and Debugging Techniques

Subfield: Software

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4409560177

FWCI: 2.435

Cites: 62

Cited by: 4

Related to: 10