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 …

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

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

Automatic Program Repair (APR) aims at fixing buggy source code with less manual
debugging efforts, which plays a vital role in improving software reliability and development …

Bug fixing is generally a manually-intensive task. However, recent work has proposed the
idea of automated program repair, which aims to repair (at least a subset of) bugs in different …

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

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

Automated Program Repair (APR) is very useful in helping developers in the process of
software development and maintenance. Despite recent advances in deep learning (DL) …

The goal of Automated Program Repair (APR) is to find a fix to software bugs, without human
intervention. The so-called Generate and Validate (G&V) approach deemed to be the most …

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 …