In the past decade, research on test-suite-based automatic program repair has grown
significantly. Each year, new approaches and implementations are featured in major …

Abstract Automated Program Repair (APR) has attracted significant attention from software
engineering research and practice communities in the last decade. Several teams have …

Automated Program Repair (APR) aims to help developers automatically patch software
bugs. However, current state-of-the-art traditional and learning-based APR techniques face …

Automated Program Repair (APR) aims to automatically generate patches for buggy
programs. Recent APR work has been focused on leveraging modern Large Language …

Due to the promising future of Automated Program Repair (APR), researchers have
proposed various APR techniques, including heuristic-based, template-based, and …

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

During Automated Program Repair (APR), it can be challenging to synthesize correct
patches for real-world systems in general-purpose programming languages. Recent Large …

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 …

Formally verifying software is a highly desirable but labor-intensive task. Recent work has
developed methods to automate formal verification using proof assistants, such as Coq and …