Since 2009, the deep learning revolution, which was triggered by the introduction of
ImageNet, has stimulated the synergy between Software Engineering (SE) and Machine …

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 …

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 …

With the rapid development and large-scale popularity of program software, modern society
increasingly relies on software systems. However, the problems exposed by software have …

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

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 …

Smart contracts with natural economic attributes have been widely and rapidly developed in
various fields. However, the bugs and vulnerabilities in smart contracts have brought huge …

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

Despite the capability in successfully fixing more and more real-world bugs, existing
Automated Program Repair (APR) techniques are still challenged by the long-standing …

Automated program repair aims to automate bug correction and alleviate the burden of
manual debugging, which plays a crucial role in software development and maintenance …