60 citations · 167 across the 21 of their papers we have counts for
7 papers · 1 filter
SECRET: Towards Scalable and Efficient Code Retrieval via Segmented Deep Hashing
Wenchao Gu, Ensheng Shi, Yanlin Wang +5
Code retrieval, which retrieves code snippets based on users' natural language descriptions, is widely used by developers and plays a pivotal role in real-world software developmen…
CoCoST: Automatic Complex Code Generation with Online Searching and Correctness Testing
Xinyi He, Jiaru Zou, Yun Lin +4
Large Language Models have revolutionized code generation ability by converting natural language descriptions into executable code. However, generating complex code within real-wor…
SoTaNa: The Open-Source Software Development Assistant
Ensheng Shi, Fengji Zhang, Yanlin Wang +6
Software development plays a crucial role in driving innovation and efficiency across modern societies. To meet the demands of this dynamic field, there is a growing need for an ef…
Towards Efficient Fine-tuning of Pre-trained Code Models: An Experimental Study and Beyond
Ensheng Shi, Yanlin Wang, Hongyu Zhang +4
Recently, fine-tuning pre-trained code models such as CodeBERT on downstream tasks has achieved great success in many software testing and analysis tasks. While effective and preva…
Accelerating Code Search with Deep Hashing and Code Classification
Wenchao Gu, Yanlin Wang, Lun Du +4
Code search is to search reusable code snippets from source code corpus based on natural languages queries. Deep learning-based methods of code search have shown promising results.…
Is a Single Model Enough? MuCoS: A Multi-Model Ensemble Learning for Semantic Code Search
Lun Du, Xiaozhou Shi, Yanlin Wang +3
Recently, deep learning methods have become mainstream in code search since they do better at capturing semantic correlations between code snippets and search queries and have prom…