4 papers
Compiling Code LLMs into Lightweight Executables
Jieke Shi, Junda He, Zhou Yang +6
The demand for better prediction accuracy and higher execution performance in neural networks continues to grow. The emergence and success of Large Language Models (LLMs) have prod…
Still Manual? Automated Linter Configuration via DSL-Based LLM Compilation of Coding Standards
Zejun Zhang, Yixin Gan, Zhenchang Xing +5
Coding standards are essential for maintaining consistent and high-quality code across teams and projects. Linters help developers enforce these standards by detecting code violati…
LLMAID: Identifying AI Capabilities in Android Apps with LLMs
Pei Liu, Terry Zhuo, Jiawei Deng +7
Recent advancements in artificial intelligence (AI) and its widespread integration into mobile software applications have received significant attention, highlighting the growing p…
Automated Soap Opera Testing Directed by LLMs and Scenario Knowledge: Feasibility, Challenges, and Road Ahead
Yanqi Su, Zhenchang Xing, Chong Wang +4
Exploratory testing (ET) harnesses tester's knowledge, creativity, and experience to create varying tests that uncover unexpected bugs from the end-user's perspective. Although ET…