most citedSoftware Testing with Large Language Models: Survey, Landscape, and Vision

28 citations · 39 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.SE2023★ 3 cited

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…

cs.SE2023★ 28 cited

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…

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★ 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…