Large language models for software engineering: A systematic literature review

X Hou, Y Zhao, Y Liu, Z Yang, K Wang, L Li… - arXiv preprint arXiv …, 2023 - arxiv.org
Large Language Models (LLMs) have significantly impacted numerous domains, notably
including Software Engineering (SE). Nevertheless, a well-rounded understanding of the …

A survey of large language models for code: Evolution, benchmarking, and future trends

Z Zheng, K Ning, Y Wang, J Zhang, D Zheng… - arXiv preprint arXiv …, 2023 - arxiv.org
General large language models (LLMs), represented by ChatGPT, have demonstrated
significant potential in tasks such as code generation in software engineering. This has led …

Retrieval-augmented generation for ai-generated content: A survey

P Zhao, H Zhang, Q Yu, Z Wang, Y Geng, F Fu… - arXiv preprint arXiv …, 2024 - arxiv.org
The development of Artificial Intelligence Generated Content (AIGC) has been facilitated by
advancements in model algorithms, scalable foundation model architectures, and the …

Context-aware code generation framework for code repositories: Local, global, and third-party library awareness

D Liao, S Pan, Q Huang, X Ren, Z Xing, H Jin… - arXiv preprint arXiv …, 2023 - arxiv.org
Code generation tools are essential to help developers in the software development
process. Existing tools often disconnect with the working context, ie, the code repository …

Codegen4libs: A two-stage approach for library-oriented code generation

M Liu, T Yang, Y Lou, X Du, Y Wang… - 2023 38th IEEE/ACM …, 2023 - ieeexplore.ieee.org
Automated code generation has been extensively studied in recent literature. In this work,
we first survey 66 participants to motivate a more pragmatic code generation scenario, ie …

Beyond Functional Correctness: Investigating Coding Style Inconsistencies in Large Language Models

Y Wang, T Jiang, M Liu, J Chen, Z Zheng - arXiv preprint arXiv:2407.00456, 2024 - arxiv.org
Large language models (LLMs) have brought a paradigm shift to the field of code
generation, offering the potential to enhance the software development process. However …

Enhancing LLM-Based Coding Tools through Native Integration of IDE-Derived Static Context

Y Li, Y Peng, Y Huo, MR Lyu - arXiv preprint arXiv:2402.03630, 2024 - arxiv.org
Large Language Models (LLMs) have achieved remarkable success in code completion, as
evidenced by their essential roles in developing code assistant services such as Copilot …

When to Stop? Towards Efficient Code Generation in LLMs with Excess Token Prevention

L Guo, Y Wang, E Shi, W Zhong, H Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
Code generation aims to automatically generate code snippets that meet given natural
language requirements and plays an important role in software development. Although …

Compositional API Recommendation for Library-Oriented Code Generation

Z Ma, S An, B Xie, Z Lin - Proceedings of the 32nd IEEE/ACM …, 2024 - dl.acm.org
Large language models (LLMs) have achieved exceptional performance in code generation.
However, the performance remains unsatisfactory in generating library-oriented code …

How to Understand Whole Software Repository?

Y Ma, Q Yang, R Cao, B Li, F Huang, Y Li - arXiv preprint arXiv …, 2024 - arxiv.org
Recently, Large Language Model (LLM) based agents have advanced the significant
development of Automatic Software Engineering (ASE). Although verified effectiveness, the …