Work

TAIiST CPS-UAV at the SBFT Tool Competition 2024

Year: 2024

Type: conference-paper

Abstract: This paper presents an innovative approach to testing Cyber-Physical Systems (CPS) with a specific focus on Unmanned Aerial Vehicles (UAVs) using Large Language Models (LLMs). In the rapidly evolving field of UAV technology, ensuring the reliability and safety of these systems is of utmost importance. Traditional testing methods often fall short in addressing the complex, dynamic, and stateful environments in which UAVs operate. To bridge this gap, we propose the use of state-of-the-art LLMs.

Source: IEEE/ACM International Workshop on Search-Based Software Testing (SBST)

DOI: 10.1145/3643659.3643936

Authors: Taohong Zhu, William Newton, Suzanne Embury, Youcheng Sun

Institution: University of Manchester

Language: English

Topic: Software Testing and Debugging Techniques

Subfield: Software

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4402407014

FWCI: 0.481

Cites: 2

Cited by: 2

Related to: 10