Researchers have recently achieved significant advances in deep learning techniques,
which in turn has substantially advanced other research disciplines, such as natural …

Automated program repair (APR) aims to fix software bugs automatically and plays a crucial
role in software development and maintenance. With the recent advances in deep learning …

Learning-based program repair has achieved good results in a recent series of papers. Yet,
we observe that the related work fails to repair some bugs because of a lack of knowledge …

Automated Program Repair (APR) has garnered significant attention due to its potential to
streamline the bug repair process for human developers. Recently, LLM-based APR …

Patch correctness has been the focus of automated program repair (APR) in recent years
due to the propensity of APR tools to generate overfitting patches. Given a generated patch …

A large body of the literature on automated program repair develops approaches where
patches are automatically generated to be validated against an oracle (eg, a test suite) …

The heavy fragmentation of the Android ecosystem has led to severe compatibility issues
with apps, including those that crash at runtime or cannot be installed on certain devices but …

Automated program repair (APR) holds the promise of aiding manual debugging activities.
Over a decade of evolution, a broad range of APR techniques have been proposed and …

Most automated program repair methods rely on test cases to determine the correctness of
the generated patches. However, due to the incompleteness of available test suites, some …

Abstract Representation learning of source code is essential for applying machine learning
to software engineering tasks. Learning code representation from a multilingual source code …