Pre-trained large language models (LLMs) have recently emerged as a breakthrough
technology in natural language processing and artificial intelligence, with the ability to …

This paper provides a comprehensive review of the literature concerning the utilization of
Natural Language Processing (NLP) techniques, with a particular focus on transformer …

To support software developers in finding and fixing software bugs, several automated
program repair techniques have been introduced. Given a test suite, standard methods …

Automated program repair (APR) aims to help developers improve software reliability by
generating patches for buggy programs. Although many code language models (CLM) are …

Large language models such as Codex, have shown the capability to produce code for
many programming tasks. However, the success rate of existing models is low, especially for …

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 …

Automatic program repair (APR) is crucial to improve software reliability. Recently, neural
machine translation (NMT) techniques have been used to automatically fix software bugs …

Automated Program Repair (APR) helps improve the efficiency of software development and
maintenance. Recent APR techniques use deep learning, particularly the encoder-decoder …

Automated generate-and-validate (GV) program repair techniques (APR) typically rely on
hard-coded rules, thus only fixing bugs following specific fix patterns. These rules require a …

Neural machine translation (NMT) architectures have achieved promising results for
automatic program repair. Yet, they have the limitation of generating low-quality patches (eg …