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From Prompts to Templates: A Systematic Prompt Template Analysis for Real-world LLMapps
Yuetian Mao, Junjie He, Chunyang Chen
Large Language Models (LLMs) have revolutionized human-AI interaction by enabling intuitive task execution through natural language prompts. Despite their potential, designing effe…
An Empirical Study on Challenges for LLM Application Developers
Xiang Chen, Chaoyang Gao, Chunyang Chen +2
In recent years, large language models (LLMs) have seen rapid advancements, significantly impacting various fields such as computer vision, natural language processing, and softwar…
Large Language Models for Mobile GUI Text Input Generation: An Empirical Study
Chenhui Cui, Tao Li, Junjie Wang +3
Mobile apps have become essential, making quality assurance increasingly important. GUI testing is widely used for automated exploration, yet text-input components remain a major o…
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…