most citedLarge Language Models for Software Engineering: Survey and Open Problems

33 citations · 58 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SE2024

Research Artifacts in Software Engineering Publications: Status and Trends

Mugeng Liu, Xiaolong Huang, Wei He +5

The Software Engineering (SE) community has been embracing the open science policy and encouraging researchers to disclose artifacts in their publications. However, the status and…

cs.SE202333 cited

Large Language Models for Software Engineering: Survey and Open Problems

Angela Fan, Beliz Gokkaya, Mark Harman +4

This paper provides a survey of the emerging area of Large Language Models (LLMs) for Software Engineering (SE). It also sets out open research challenges for the application of LL…

cs.SE20233 cited

ConDefects: A New Dataset to Address the Data Leakage Concern for LLM-based Fault Localization and Program Repair

Yonghao Wu, Zheng Li, Jie M. Zhang +1

With the growing interest on Large Language Models (LLMs) for fault localization and program repair, ensuring the integrity and generalizability of the LLM-based methods becomes pa…

cs.SE202320 cited

Large Language Models in Fault Localisation

Yonghao Wu, Zheng Li, Jie M. Zhang +3

Large Language Models (LLMs) have shown promise in multiple software engineering tasks including code generation, program repair, code summarisation, and test generation. Fault loc…

cs.SE20231 cited

COCO: Testing Code Generation Systems via Concretized Instructions

Ming Yan, Junjie Chen, Jie M. Zhang +3

Code generation systems have been extensively developed in recent years to generate source code based on natural language instructions. However, despite their advancements, these s…

cs.SE20231 cited

Vulnerability Detection with Graph Simplification and Enhanced Graph Representation Learning

Xin-Cheng Wen, Yupan Chen, Cuiyun Gao +3

Prior studies have demonstrated the effectiveness of Deep Learning (DL) in automated software vulnerability detection. Graph Neural Networks (GNNs) have proven effective in learnin…