Large language models for software engineering: A systematic literature review

X Hou, Y Zhao, Y Liu, Z Yang, K Wang, L Li… - ACM Transactions on …, 2023 - dl.acm.org
Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …

Efficient and green large language models for software engineering: Vision and the road ahead

J Shi, Z Yang, D Lo - ACM Transactions on Software Engineering and …, 2024 - dl.acm.org
Large Language Models (LLMs) have recently shown remarkable capabilities in various
software engineering tasks, spurring the rapid growth of the Large Language Models for …

Robustness, security, privacy, explainability, efficiency, and usability of large language models for code

Z Yang, Z Sun, TZ Yue, P Devanbu, D Lo - arXiv preprint arXiv:2403.07506, 2024 - arxiv.org
Large language models for code (LLM4Code), which demonstrate strong performance (eg,
high accuracy) in processing source code, have significantly transformed software …

When to stop? towards efficient code generation in llms with excess token prevention

L Guo, Y Wang, E Shi, W Zhong, H Zhang… - Proceedings of the 33rd …, 2024 - dl.acm.org
Code generation aims to automatically generate code snippets that meet given natural
language requirements and plays an important role in software development. Although …

Anchor Attention, Small Cache: Code Generation with Large Language Models

X Zhang, Y Zhou, G Yang, HC Gall, T Chen - arXiv preprint arXiv …, 2024 - arxiv.org
The development of large language models (LLMs) has revolutionized automated code
generation. However, their high demand of computation resources has hindered a broader …

Smart Software Analysis for Software Quality Assurance

L Li - Proceedings of the ACM Turing Award Celebration …, 2024 - dl.acm.org
In this position paper, we introduce our research objective in applying smart software
analysis for software quality assurance. We start by introducing the concepts of software …

On the Compression of Language Models for Code: An Empirical Study on CodeBERT

G d'Aloisio, L Traini, F Sarro, A Di Marco - arXiv preprint arXiv:2412.13737, 2024 - arxiv.org
Language models have proven successful across a wide range of software engineering
tasks, but their significant computational costs often hinder their practical adoption. To …

API-guided Dataset Synthesis to Finetune Large Code Models

Z Li, D Wu, S Wang, Z Su - arXiv preprint arXiv:2408.08343, 2024 - arxiv.org
Large code models (LCMs), pre-trained on vast code corpora, have demonstrated
remarkable performance across a wide array of code-related tasks. Supervised fine-tuning …