A survey on large language models for code generation

J Jiang, F Wang, J Shen, S Kim, S Kim - ar** study of source code representation for deep learning in software engineering
HP Samoaa, F Bayram, P Salza, P Leitner - IET Software, 2022 - Wiley Online Library
The usage of deep learning (DL) approaches for software engineering has attracted much
attention, particularly in source code modelling and analysis. However, in order to use DL …

Deep learning based program generation from requirements text: Are we there yet?

H Liu, M Shen, J Zhu, N Niu, G Li… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
To release developers from time-consuming software development, many approaches have
been proposed to generate source code automatically according to software requirements …

Suggesting accurate method and class names

M Allamanis, ET Barr, C Bird, C Sutton - … of the 2015 10th joint meeting …, 2015 - dl.acm.org
Descriptive names are a vital part of readable, and hence maintainable, code. Recent
progress on automatically suggesting names for local variables tantalizes with the prospect …

Towards automated reentrancy detection for smart contracts based on sequential models

P Qian, Z Liu, Q He, R Zimmermann, X Wang - IEEE access, 2020 - ieeexplore.ieee.org
In the last decade, smart contract security issues lead to tremendous losses, which has
attracted increasing public attention both in industry and in academia. Researchers have …

API code recommendation using statistical learning from fine-grained changes

AT Nguyen, M Hilton, M Codoban, HA Nguyen… - Proceedings of the …, 2016 - dl.acm.org
Learning and remembering how to use APIs is difficult. While code-completion tools can
recommend API methods, browsing a long list of API method names and their …