A survey on deep learning for software engineering

Y Yang, X **a, D Lo, J Grundy - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)”
and an improved model training method to break the bottleneck of neural network …

A systematic literature review on the use of deep learning in software engineering research

C Watson, N Cooper, DN Palacio, K Moran… - ACM Transactions on …, 2022 - dl.acm.org
An increasingly popular set of techniques adopted by software engineering (SE)
researchers to automate development tasks are those rooted in the concept of Deep …

Using large language models to enhance programming error messages

J Leinonen, A Hellas, S Sarsa, B Reeves… - Proceedings of the 54th …, 2023 - dl.acm.org
A key part of learning to program is learning to understand programming error messages.
They can be hard to interpret and identifying the cause of errors can be time-consuming …

A survey of learning-based automated program repair

Q Zhang, C Fang, Y Ma, W Sun, Z Chen - ACM Transactions on Software …, 2023 - dl.acm.org
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 …

Repairagent: An autonomous, llm-based agent for program repair

I Bouzenia, P Devanbu, M Pradel - arxiv preprint arxiv:2403.17134, 2024 - arxiv.org
Automated program repair has emerged as a powerful technique to mitigate the impact of
software bugs on system reliability and user experience. This paper introduces RepairAgent …

Generating high-precision feedback for programming syntax errors using large language models

T Phung, J Cambronero, S Gulwani, T Kohn… - arxiv preprint arxiv …, 2023 - arxiv.org
Large language models (LLMs), such as Codex, hold great promise in enhancing
programming education by automatically generating feedback for students. We investigate …

[HTML][HTML] A survey on machine learning techniques applied to source code

T Sharma, M Kechagia, S Georgiou, R Tiwari… - Journal of Systems and …, 2024 - Elsevier
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …

A survey on machine learning techniques for source code analysis

T Sharma, M Kechagia, S Georgiou, R Tiwari… - arxiv preprint arxiv …, 2021 - arxiv.org
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …

Reimagining the machine learning life cycle to improve educational outcomes of students

LT Liu, S Wang, T Britton, R Abebe - … of the National Academy of Sciences, 2023 - pnas.org
Machine learning (ML) techniques are increasingly prevalent in education, from their use in
predicting student dropout to assisting in university admissions and facilitating the rise of …

Deep learning-based software engineering: progress, challenges, and opportunities

X Chen, X Hu, Y Huang, H Jiang, W Ji, Y Jiang… - Science China …, 2025 - Springer
Researchers have recently achieved significant advances in deep learning techniques,
which in turn has substantially advanced other research disciplines, such as natural …