8 citations · 8 across the 1 of their papers we have counts for
4 papers
Code Graph Model (CGM): A Graph-Integrated Large Language Model for Repository-Level Software Engineering Tasks
Hongyuan Tao, Ying Zhang, Zhenhao Tang +12
Recent advances in Large Language Models (LLMs) have shown promise in function-level code generation, yet repository-level software engineering tasks remain challenging. Current so…
MicroFuzz: An Efficient Fuzzing Framework for Microservices
Peng Di, Bingchang Liu, Yiyi Gao
This paper presents a novel fuzzing framework, called MicroFuzz, specifically designed for Microservices. Mocking-Assisted Seed Execution, Distributed Tracing, Seed Refresh and Pip…
Harnessing the Power of LLM to Support Binary Taint Analysis
Puzhuo Liu, Chengnian Sun, Yaowen Zheng +8
This paper proposes LATTE, the first static binary taint analysis that is powered by a large language model (LLM). LATTE is superior to the state of the art (e.g., Emtaint, Arbiter…
CodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model
Peng Di, Jianguo Li, Hang Yu +35
Code Large Language Models (Code LLMs) have gained significant attention in the industry due to their wide applications in the full lifecycle of software engineering. However, the…