With the proven effectiveness of L arge L anguage M odels (LLMs) in code-related tasks,
researchers have explored their potential for program repair. However, existing repair …

Code understanding and generation have fast become some of the most popular
applications of language models (LMs). Nonetheless, research on multilingual aspects of …

Context: Neural code generation aims to automatically generate code snippets guided by
Natural Language Descriptions (NLDs). In recent years, various neural code generation …

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) …

Neural Code Intelligence--leveraging deep learning to understand, generate, and optimize
code--holds immense potential for transformative impacts on the whole society. Bridging the …

Learning to edit code automatically is becoming more and more feasible. Thanks to recent
advances in Neural Machine Translation (NMT), various case studies are being investigated …

Large language models (LLMs) have recently become remarkably good at improving
developer productivity for high-resource programming languages. These models use two …

Software systems have been evolving rapidly and inevitably introducing bugs at an
increasing rate, leading to significant losses in resources consumed by software …

We propose Patcherizer, a novel patch representation methodology that combines context
and structure intention features to capture the semantic changes in Abstract Syntax Trees …

Recent advances in deep learning have significantly improved the understanding of source
code by leveraging large amounts of open-source software data. Thanks to the larger …