Neurosymbolic programming
We survey recent work on neurosymbolic programming, an emerging area that bridges the
areas of deep learning and program synthesis. Like in classic machine learning, the goal …
areas of deep learning and program synthesis. Like in classic machine learning, the goal …
Automatic software repair: A bibliography
M Monperrus - ACM Computing Surveys (CSUR), 2018 - dl.acm.org
This article presents a survey on automatic software repair. Automatic software repair
consists of automatically finding a solution to software bugs without human intervention. This …
consists of automatically finding a solution to software bugs without human intervention. This …
An analysis of the automatic bug fixing performance of chatgpt
To support software developers in finding and fixing software bugs, several automated
program repair techniques have been introduced. Given a test suite, standard methods …
program repair techniques have been introduced. Given a test suite, standard methods …
Automated program repair in the era of large pre-trained language models
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 …
bugs. However, current state-of-the-art traditional and learning-based APR techniques face …
Keep the Conversation Going: Fixing 162 out of 337 bugs for $0.42 each using ChatGPT
Automated Program Repair (APR) aims to automatically generate patches for buggy
programs. Recent APR work has been focused on leveraging modern Large Language …
programs. Recent APR work has been focused on leveraging modern Large Language …
Large language models for software engineering: Survey and open problems
This paper provides a survey of the emerging area of Large Language Models (LLMs) for
Software Engineering (SE). It also sets out open research challenges for the application of …
Software Engineering (SE). It also sets out open research challenges for the application of …
Program synthesis with large language models
This paper explores the limits of the current generation of large language models for
program synthesis in general purpose programming languages. We evaluate a collection of …
program synthesis in general purpose programming languages. We evaluate a collection of …
Automated repair of programs from large language models
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 …
many programming tasks. However, the success rate of existing models is low, especially for …
Examining zero-shot vulnerability repair with large language models
Human developers can produce code with cybersecurity bugs. Can emerging 'smart'code
completion tools help repair those bugs? In this work, we examine the use of large language …
completion tools help repair those bugs? In this work, we examine the use of large language …
Less training, more repairing please: revisiting automated program repair via zero-shot learning
Due to the promising future of Automated Program Repair (APR), researchers have
proposed various APR techniques, including heuristic-based, template-based, and …
proposed various APR techniques, including heuristic-based, template-based, and …