87 citations · 170 across the 19 of their papers we have counts for
21 papers
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…
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…
EALink: An Efficient and Accurate Pre-trained Framework for Issue-Commit Link Recovery
Chenyuan Zhang, Yanlin Wang, Zhao Wei +4
Issue-commit links, as a type of software traceability links, play a vital role in various software development and maintenance tasks. However, they are typically deficient, as dev…
RefBERT: A Two-Stage Pre-trained Framework for Automatic Rename Refactoring
Hao Liu, Yanlin Wang, Zhao Wei +4
Refactoring is an indispensable practice of improving the quality and maintainability of source code in software evolution. Rename refactoring is the most frequently performed refa…
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…
Exploring Representation-Level Augmentation for Code Search
Haochen Li, Chunyan Miao, Cyril Leung +4
Code search, which aims at retrieving the most relevant code fragment for a given natural language query, is a common activity in software development practice. Recently, contrasti…
Unveiling the Black Box of PLMs with Semantic Anchors: Towards Interpretable Neural Semantic Parsing
Lunyiu Nie, Jiuding Sun, Yanlin Wang +6
The recent prevalence of pretrained language models (PLMs) has dramatically shifted the paradigm of semantic parsing, where the mapping from natural language utterances to structur…
Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach
Wendong Bi, Lun Du, Qiang Fu +3
Graph Neural Networks (GNNs) are popular machine learning methods for modeling graph data. A lot of GNNs perform well on homophily graphs while having unsatisfactory performance on…
Revisiting Code Search in a Two-Stage Paradigm
Fan Hu, Yanlin Wang, Lun Du +4
With a good code search engine, developers can reuse existing code snippets and accelerate software development process. Current code search methods can be divided into two categor…
Tackling Long Code Search with Splitting, Encoding, and Aggregating
Fan Hu, Yanlin Wang, Lun Du +4
Code search with natural language helps us reuse existing code snippets. Thanks to the Transformer-based pretraining models, the performance of code search has been improved signif…
MM-GNN: Mix-Moment Graph Neural Network towards Modeling Neighborhood Feature Distribution
Wendong Bi, Lun Du, Qiang Fu +3
Graph Neural Networks (GNNs) have shown expressive performance on graph representation learning by aggregating information from neighbors. Recently, some studies have discussed the…
CoCoSoDa: Effective Contrastive Learning for Code Search
Ensheng Shi, Yanlin Wang, Wenchao Gu +5
Code search aims to retrieve semantically relevant code snippets for a given natural language query. Recently, many approaches employing contrastive learning have shown promising r…
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.…
UniXcoder: Unified Cross-Modal Pre-training for Code Representation
Daya Guo, Shuai Lu, Nan Duan +3
Pre-trained models for programming languages have recently demonstrated great success on code intelligence. To support both code-related understanding and generation tasks, recent…
RACE: Retrieval-Augmented Commit Message Generation
Ensheng Shi, Yanlin Wang, Wei Tao +5
Commit messages are important for software development and maintenance. Many neural network-based approaches have been proposed and shown promising results on automatic commit mess…
CAST: Enhancing Code Summarization with Hierarchical Splitting and Reconstruction of Abstract Syntax Trees
Ensheng Shi, Yanlin Wang, Lun Du +4
Code summarization aims to generate concise natural language descriptions of source code, which can help improve program comprehension and maintenance. Recent studies show that syn…
On the Evaluation of Commit Message Generation Models: An Experimental Study
Wei Tao, Yanlin Wang, Ensheng Shi +5
Commit messages are natural language descriptions of code changes, which are important for program understanding and maintenance. However, writing commit messages manually is time-…
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…
CoCoSum: Contextual Code Summarization with Multi-Relational Graph Neural Network
Yanlin Wang, Ensheng Shi, Lun Du +5
Source code summaries are short natural language descriptions of code snippets that help developers better understand and maintain source code. There has been a surge of work on au…
On the Evaluation of Neural Code Summarization
Ensheng Shi, Yanlin Wang, Lun Du +5
Source code summaries are important for program comprehension and maintenance. However, there are plenty of programs with missing, outdated, or mismatched summaries. Recently, deep…
Code Completion by Modeling Flattened Abstract Syntax Trees as Graphs
Yanlin Wang, Hui Li
Code completion has become an essential component of integrated development environments. Contemporary code completion methods rely on the abstract syntax tree (AST) to generate sy…