activity
20182023
most citedOwl Eyes: Spotting UI Display Issues via Visual Understanding

81 citations · 440 across the 31 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

cs.SE2021★ 8 cited

Explainable Software Defect Prediction: Are We There Yet?

Jiho Shin, Reem Aleithan, Jaechang Nam +2

Explaining the prediction results of software defect prediction models is a challenging while practical task, which can provide useful information for developers to understand and…

cs.SE2021★ 1 cited

An Approach to Detecting Bugs in Pattern-Based Bug Detectors

Junjie Wang, Yuchao Huang, Song Wang +1

Static bug finders have been widely-adopted by developers to find bugs in real world software projects. They leverage predefined heuristic static analysis rules to scan source code…

cs.SE2021

Yet Another Combination of IR- and Neural-based Comment Generation

Huang Yuchao, Wei Moshi, Wang Song +2

Code comment generation techniques aim to generate natural language descriptions for source code. There are two orthogonal approaches for this task, i.e., information retrieval (IR…

cs.SE2021★ 15 cited

OwlEyes-Online: A Fully Automated Platform for Detecting and Localizing UI Display Issues

Yuhui Su, Zhe Liu, Chunyang Chen +2

Graphical User Interface (GUI) provides visual bridges between software apps and end users. However, due to the compatibility of software or hardware, UI display issues such as tex…

cs.SE2021★ 7 cited

CoCoFuzzing: Testing Neural Code Models with Coverage-Guided Fuzzing

Moshi Wei, Yuchao Huang, Jinqiu Yang +2

Deep learning-based code processing models have shown good performance for tasks such as predicting method names, summarizing programs, and comment generation. However, despite the…