Identifying safety–critical concerns in unmanned aerial vehicle software platforms with SALIENT

Identifying safety–critical concerns in unmanned aerial vehicle software platforms with SALIENT

Safety-related concerns may emerge during the operation of unmanned aerial vehicles (UAVs), reported by users and developers in the form of issue reports and pull requests. To help UAV developers identify safety-related concerns, we propose SALIENT, a machine learning (ML)-enabled tool that analyzes...

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Bibliographic Details
Main Authors: Sajad Khatiri, Andrea Di Sorbo, Fiorella Zampetti, Corrado A. Visaggio, Massimiliano Di Penta, Sebastiano Panichella
Format: Article
Language:English
Published: Elsevier 2024-09-01
Series:SoftwareX
Subjects:
Unmanned aerial vehicles
Issue management
Safety issues
Machine learning
Empirical study
Online Access:http://www.sciencedirect.com/science/article/pii/S2352711024001195

Internet

http://www.sciencedirect.com/science/article/pii/S2352711024001195

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