RAP-Gen: Retrieval-Augmented Patch Generation with CodeT5 for Automatic Program Repair
Weishi Wang, Yue Wang, Shafiq Joty, Steven C. H. Hoi
Abstract
Automatic program repair (APR) is crucial to reduce manual debugging efforts for developers and improve software reliability. While conventional search-based techniques typically rely on heuristic rules or a redundancy assumption to mine fix patterns, recent years have witnessed the surge of deep learning (DL) based approaches to automate the program repair process in a data-driven manner. However, their performance is often limited by a fixed set of parameters to model the highly complex search space of APR.
Topics & Concepts
DebuggingComputer scienceRedundancy (engineering)Process (computing)SoftwareSet (abstract data type)HeuristicReliability (semiconductor)Software engineeringArtificial intelligenceProgramming languageOperating systemPower (physics)PhysicsQuantum mechanicsSoftware Testing and Debugging TechniquesSoftware Engineering ResearchSoftware Reliability and Analysis Research