81 citations · 440 across the 31 of their papers we have counts for
31 papers
Make LLM a Testing Expert: Bringing Human-like Interaction to Mobile GUI Testing via Functionality-aware Decisions
Zhe Liu, Chunyang Chen, Junjie Wang +5
Automated Graphical User Interface (GUI) testing plays a crucial role in ensuring app quality, especially as mobile applications have become an integral part of our daily lives. De…
Testing the Limits: Unusual Text Inputs Generation for Mobile App Crash Detection with Large Language Model
Zhe Liu, Chunyang Chen, Junjie Wang +5
Mobile applications have become a ubiquitous part of our daily life, providing users with access to various services and utilities. Text input, as an important interaction channel…
CrashTranslator: Automatically Reproducing Mobile Application Crashes Directly from Stack Trace
Yuchao Huang, Junjie Wang, Zhe Liu +5
Crash reports are vital for software maintenance since they allow the developers to be informed of the problems encountered in the mobile application. Before fixing, developers nee…
A First Look at Fairness of Machine Learning Based Code Reviewer Recommendation
Mohammad Mahdi Mohajer, Alvine Boaye Belle, Nima Shiri harzevili +5
The fairness of machine learning (ML) approaches is critical to the reliability of modern artificial intelligence systems. Despite extensive study on this topic, the fairness of ML…
Automatic Static Bug Detection for Machine Learning Libraries: Are We There Yet?
Nima Shiri harzevili, Jiho Shin, Junjie Wang +2
Automatic detection of software bugs is a critical task in software security. Many static tools that can help detect bugs have been proposed. While these static bug detectors are m…
Software Testing with Large Language Models: Survey, Landscape, and Vision
Junjie Wang, Yuchao Huang, Chunyang Chen +3
Pre-trained large language models (LLMs) have recently emerged as a breakthrough technology in natural language processing and artificial intelligence, with the ability to handle l…