most citedWhere is Your App Frustrating Users?

25 citations · 45 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SE2022

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…

cs.SE202225 cited

Where is Your App Frustrating Users?

Yawen Wang, Junjie Wang, Hongyu Zhang +3

User reviews of mobile apps provide a communication channel for developers to perceive user satisfaction. Many app features that users have problems with are usually expressed by k…

cs.SE2022

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.…

cs.SE20224 cited

HELoC: Hierarchical Contrastive Learning of Source Code Representation

Xiao Wang, Qiong Wu, Hongyu Zhang +5

Abstract syntax trees (ASTs) play a crucial role in source code representation. However, due to the large number of nodes in an AST and the typically deep AST hierarchy, it is chal…

cs.SE202216 cited

What Do They Capture? -- A Structural Analysis of Pre-Trained Language Models for Source Code

Yao Wan, Wei Zhao, Hongyu Zhang +3

Recently, many pre-trained language models for source code have been proposed to model the context of code and serve as a basis for downstream code intelligence tasks such as code…

cs.SE2022

Cross-Language Binary-Source Code Matching with Intermediate Representations

Yi Gui, Yao Wan, Hongyu Zhang +5

Binary-source code matching plays an important role in many security and software engineering related tasks such as malware detection, reverse engineering and vulnerability assessm…