Software testing with large language models: Survey, landscape, and vision

J Wang, Y Huang, C Chen, Z Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Pre-trained large language models (LLMs) have recently emerged as a breakthrough
technology in natural language processing and artificial intelligence, with the ability to …

Natural language generation and understanding of big code for AI-assisted programming: A review

MF Wong, S Guo, CN Hang, SW Ho, CW Tan - Entropy, 2023 - mdpi.com
This paper provides a comprehensive review of the literature concerning the utilization of
Natural Language Processing (NLP) techniques, with a particular focus on transformer …

Impact of code language models on automated program repair

N Jiang, K Liu, T Lutellier, L Tan - 2023 IEEE/ACM 45th …, 2023 - ieeexplore.ieee.org
Automated program repair (APR) aims to help developers improve software reliability by
generating patches for buggy programs. Although many code language models (CLM) are …

Less training, more repairing please: revisiting automated program repair via zero-shot learning

CS Xia, L Zhang - Proceedings of the 30th ACM Joint European …, 2022 - dl.acm.org
Due to the promising future of Automated Program Repair (APR), researchers have
proposed various APR techniques, including heuristic-based, template-based, and …

Cure: Code-aware neural machine translation for automatic program repair

N Jiang, T Lutellier, L Tan - 2021 IEEE/ACM 43rd International …, 2021 - ieeexplore.ieee.org
Automatic program repair (APR) is crucial to improve software reliability. Recently, neural
machine translation (NMT) techniques have been used to automatically fix software bugs …

Large language models are few-shot testers: Exploring llm-based general bug reproduction

S Kang, J Yoon, S Yoo - 2023 IEEE/ACM 45th International …, 2023 - ieeexplore.ieee.org
Many automated test generation techniques have been developed to aid developers with
writing tests. To facilitate full automation, most existing techniques aim to either increase …

A syntax-guided edit decoder for neural program repair

Q Zhu, Z Sun, Y Xiao, W Zhang, K Yuan… - Proceedings of the 29th …, 2021 - dl.acm.org
Automated Program Repair (APR) helps improve the efficiency of software development and
maintenance. Recent APR techniques use deep learning, particularly the encoder-decoder …

Dlfix: Context-based code transformation learning for automated program repair

Y Li, S Wang, TN Nguyen - Proceedings of the ACM/IEEE 42nd …, 2020 - dl.acm.org
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) …

Coconut: combining context-aware neural translation models using ensemble for program repair

T Lutellier, HV Pham, L Pang, Y Li, M Wei… - Proceedings of the 29th …, 2020 - dl.acm.org
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 program repair with execution-based backpropagation

H Ye, M Martinez, M Monperrus - … of the 44th international conference on …, 2022 - dl.acm.org
Neural machine translation (NMT) architectures have achieved promising results for
automatic program repair. Yet, they have the limitation of generating low-quality patches (eg …